{"topic":"Risk, Credit & Banking","items":[{"title":"Financial Tail Risk Beyond Lipschitz Continuity via Semi-Discrete Optimal Transport","url":"/papers/arxiv/2609.27785/","summary":"Proposes semi-discrete optimal transport to capture heavy tails in financial returns, maintaining stable tail ratio estimates across diverse neural generators when standard Lipschitz methods fail.","featured":"2026-09-25","label":"arXiv","topic":"Risk, Credit & Banking","cites":0,"score":4,"scale":"fanfare"},{"title":"DefaultGNN: A Dual-Perspective GNN Framework for Predicting Corporate Default from Buyer-Seller Transaction Networks","url":"/papers/arxiv/2609.25542/","summary":"A dual-perspective graph neural network framework predicts corporate defaults from buyer-seller transaction networks, improving approval rates by 7-11 percentage points without increasing default risk.","featured":"2026-09-25","label":"arXiv","topic":"Risk, Credit & Banking","cites":0,"score":3,"scale":"fanfare"},{"title":"Risk Measures under Paired-Ambiguity: A Deep Learning Reflected BSDE Framework","url":"/papers/arxiv/2609.23768/","summary":"Develops a deep learning scheme for optimal stopping under simultaneous model and discount-rate ambiguity, with application to American option valuation under uncertainty.","featured":"2026-09-25","label":"arXiv","topic":"Risk, Credit & Banking","cites":0,"score":2,"scale":"fanfare"},{"title":"Forward Guidance and the Dynamics of Bank Credit: The Bank Balance-Sheet Channel of Monetary News","url":"/papers/ssrn/7514178/","summary":"High-frequency analysis reveals contractionary forward guidance immediately cuts bank lending, while expansionary guidance produces weak stimulus, driven by binding capital constraints.","featured":"2026-09-25","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":3,"scale":"fanfare"},{"title":"Monetary policy transmission by securitising banks","url":"/papers/ssrn/7515879/","summary":"Banks engaged in securitization contract lending more sharply after monetary tightening because their investor base demands higher returns and cuts risk exposure when rates rise.","featured":"2026-09-25","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":3,"scale":"fanfare"},{"title":"Hedge Fund Performance and Interest Rate Conditions: Evidence from Regulatory Data","url":"/papers/ssrn/7493702/","summary":"Using SEC filings from 2013-2021, the paper finds hedge fund returns show heterogeneous sensitivity to interest rates, with effects varying by strategy, leverage, and derivative exposure.","featured":"2026-09-25","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":3,"scale":"fanfare"},{"title":"State-dependent global banking systemic risk: An integrated framework of network connectedness, tail risk, and global financial conditions","url":"/papers/ssrn/7493706/","summary":"Combining quantile-connectedness, tail-risk measures, and network analysis, the research shows tail connectedness exceeds median levels and lower-tail effects persist longer, with the VIX alone reliably predicting next-week systemic risk.","featured":"2026-09-25","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"fanfare"},{"title":"The Low Return Channel of Negative Interest Rates in Bank Lending","url":"/papers/ssrn/7489554/","summary":"Japan's 2016 negative-rate policy reduced lending from low-profitability banks holding reserves, consistent with lower expected returns on bank assets rather than deposit-side stress.","featured":"2026-09-25","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"fanfare"},{"title":"Signature-Based Structural Models and Applications in Credit Markets","url":"/papers/ssrn/7498599/","summary":"The study develops a time-varying signature asset model for structural credit that improves calibration across CDS maturities and equity option prices, especially for high-yield firms.","featured":"2026-09-25","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"fanfare"},{"title":"Sell, Hold Out, or Accept: The Creditor's Trilemma in Distressed Debt Exchanges","url":"/papers/ssrn/7502204/","summary":"Analysis of 284 distressed exchanges from 2009-2022 reveals over 50% of firms face subsequent default, with large illiquid creditors trapped in a prisoner's dilemma explaining high acceptance rates.","featured":"2026-09-25","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":3,"scale":"fanfare"},{"title":"The Global Credit Cycle","url":"/papers/repec/cpr-ceprdp-21268/","summary":"A nonlinear factor constructed from credit spreads and equity volatility prices global corporate bond returns, explaining up to 13% of three-month-ahead return variation across markets.","featured":"2026-09-25","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":3,"scale":"fanfare"},{"title":"The credit channel of monetary policy: direct survey evidence from UK firms","url":"/papers/repec/boe-boeewp-023260/","summary":"UK firm survey data validates that external borrowers face larger cost-of-capital increases and cut investment more than internal funders when rates rise, accounting for a quarter of monetary policy's total effect.","featured":"2026-09-25","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":3,"scale":"fanfare"},{"title":"Credit Card Banking","url":"/papers/repec/nbr-nberwo-35607/","summary":"Analysis of 550 million US credit card accounts shows that despite high charge-off rates, card lenders earn 1.5% alpha and 6.8% return on assets through pricing power and non-interest income.","featured":"2026-09-25","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":3,"scale":"fanfare"},{"title":"Bank Runs With and Without Bank Failure","url":"/papers/repec/nbr-nberwo-35504/","summary":"A database of 3,984 historical US bank runs shows runs are more likely in weak banks but often occur in strong banks; failures concentrate in fundamentally weak institutions.","featured":"2026-09-25","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":3,"scale":"fanfare"},{"title":"LASH Risk and Interest Rates","url":"/papers/repec/cpr-ceprdp-20158/","summary":"The study measures liquidity risk from solvency hedging in sterling repo and swaps, finding that pre-crisis LASH risk predicted pension fund bond sales during the 2022 UK market stress.","featured":"2026-09-25","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"fanfare"},{"title":"Sovereign vs. Corporate Debt and Default: More Similar Than You Think","url":"/papers/repec/cpr-ceprdp-20100/","summary":"Analysis of 20 years of US junk bonds and emerging market sovereign debt reveals surprisingly similar average returns, Sharpe ratios, default frequencies, and haircuts across the two asset classes.","featured":"2026-09-25","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"fanfare"},{"title":"Collateral policy surprises","url":"/papers/repec/zbw-bubdps-343110/","summary":"Expansionary central bank collateral policy surprises reduce bank default risk and volatility while compressing government bond spreads, transmitting effects distinctly from asset purchases.","featured":"2026-09-25","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"fanfare"},{"title":"Pension Liquidity Risk","url":"/papers/repec/cpr-ceprdp-21095/","summary":"Dutch pension funds use interest rate swaps more aggressively when underfunded, exposing themselves to margin calls exceeding 6% of assets and forcing procyclical sales of government bonds.","featured":"2026-09-25","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"fanfare"},{"title":"A theory of bank liquidity requirements","url":"/papers/repec/ecb-ecbwps-20263252/","summary":"The study develops a general equilibrium model of financial intermediation showing that liquidity regulation alone cannot achieve efficient allocations and requires complementary policies like bank size limits.","featured":"2026-09-25","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"fanfare"},{"title":"Systemic at Home: the Persistence of a Too-Big-to-Fail Premium in Europe","url":"/papers/repec/dnb-dnbwpp-868/","summary":"European banks with assets exceeding half of home GDP enjoy at least 30 percent lower credit spreads, and this implicit subsidy persists and depends on sovereign fiscal strength.","featured":"2026-09-25","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"fanfare"},{"title":"Lambda R{\\'e}nyi entropic value-at-risk","url":"/papers/arxiv/2604.10657/","summary":"A New Measure: The article introduces the Lambda extension of Rényi entropic value-at-risk (Λ-EVaR), a new risk measure designed for better risk management by allowing adjustable confidence levels and sensitivity to higher moments.","featured":"2026-04-16","label":"arXiv","topic":"Risk, Credit & Banking","cites":0,"score":0,"scale":"shares"},{"title":"AI Agents in Financial Markets: Architecture, Applications, and Systemic Implications","url":"/papers/arxiv/2603.13942/","summary":"Recent AI advancements are enhancing financial automation by creating integrated systems that use autonomous agents for better decision-making and processing, highlighting the need for effective agent governance.","featured":"2026-04-16","label":"arXiv","topic":"Risk, Credit & Banking","cites":9,"score":1,"scale":"shares"},{"title":"Mean-field approximations in insurance","url":"/papers/arxiv/2511.04198/","summary":"A mean-field model simplifies complex insurance liabilities into manageable solutions, showing that large groups of interdependent individuals can be effectively analyzed in both life and non-life insurance scenarios.","featured":"2026-04-16","label":"arXiv","topic":"Risk, Credit & Banking","cites":0,"score":0,"scale":"shares"},{"title":"Asset Prices, Collateral and Bank Lending: The Case of COVID-19 and Real Estate","url":"/papers/ssrn/4470421/","summary":"The paper investigates the euro area's banking system's role in transmitting asset price shocks to credit during the Covid-19 crisis, highlighting significant frictions and a decrease in lending related to real estate collateral.","featured":"2025-12-28","label":"SSRN","topic":"Risk, Credit & Banking","cites":3,"score":132,"scale":"shares"},{"title":"Bias in Credit Ratings","url":"/papers/ssrn/4478090/","summary":"Subscription-based credit rating agencies may have biases that lead to overly optimistic ratings, complicating conflict resolution.","featured":"2025-12-28","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":447,"scale":"shares"},{"title":"Financial Fragilities and Risk-taking of Corporate Bond Funds in the Aftermath of Central Bank Policy Interventions","url":"/papers/ssrn/4463970/","summary":"It finds that central bank asset purchases during the pandemic led corporate bond fund managers to take more risks, affecting market stability.","featured":"2025-12-28","label":"SSRN","topic":"Risk, Credit & Banking","cites":1,"score":51,"scale":"shares"},{"title":"Financial Instruments for Decarbonization: Likely Pathways for the Romanian Economy","url":"/papers/ssrn/4440511/","summary":"The study highlights key financial tools in Romania, like green bonds and loans, which can help transition to a low-carbon economy, with banks playing a major role.","featured":"2025-12-19","label":"SSRN","topic":"Risk, Credit & Banking","cites":1,"score":117,"scale":"shares"},{"title":"Extending the application of dynamic Bayesian networks in calculating market risk: Standard and stressed expected shortfall","url":"/papers/arxiv/2512.12334/","summary":"The study enhances dynamic Bayesian networks for estimating expected shortfall, revealing that traditional models struggle in tail predictions and proposing methods for better forecasting.","featured":"2025-12-19","label":"arXiv","topic":"Risk, Credit & Banking","cites":0,"score":1,"scale":"shares"},{"title":"Optimal Investment, Consumption, and Insurance with Durable Goods under Stochastic Depreciation Risk","url":"/papers/arxiv/1903.00631/","summary":"An economic agent makes choices to maximize utility by adjusting consumption, investing in safe and risky assets, and insuring against losses on a depreciating good, using a strategy from the Hamilton-Jacobi-Bellman equation.","featured":"2025-12-14","label":"arXiv","topic":"Risk, Credit & Banking","cites":0,"score":1,"scale":"shares"},{"title":"Market Reactions and Information Spillovers in Bank Mergers: A Multi-Method Analysis of the Japanese Banking Sector","url":"/papers/arxiv/2512.06550/","summary":"This study analyzes how the market responds to major bank mergers in Japan, finding significant positive abnormal returns and lasting effects, indicating that banks benefit from synergies after merging.","featured":"2025-12-14","label":"arXiv","topic":"Risk, Credit & Banking","cites":0,"score":1,"scale":"shares"},{"title":"Informative Risk Measures in the Banking Industry: A Proposal based on the Magnitude-Propensity Approach","url":"/papers/arxiv/2511.21556/","summary":"A new approach to representing risk in portfolios improves loss analysis for regulatory and managerial purposes beyond traditional methods.","featured":"2025-12-01","label":"arXiv","topic":"Risk, Credit & Banking","cites":0,"score":0,"scale":"shares"},{"title":"Statistics of Extremes for the Insurance Industry","url":"/papers/arxiv/2511.22272/","summary":"The survey explains how extreme modeling techniques can be applied in insurance, using real-world data examples.","featured":"2025-12-01","label":"arXiv","topic":"Risk, Credit & Banking","cites":0,"score":0,"scale":"shares"},{"title":"Extended Convolution Bounds on the Fr\\'{e}chet Problem: Robust Risk Aggregation and Risk Sharing","url":"/papers/arxiv/2511.21929/","summary":"This paper introduces new bounds for the Fréchet problem and examines effective methods for risk aggregation and sharing in risk management.","featured":"2025-12-01","label":"arXiv","topic":"Risk, Credit & Banking","cites":0,"score":0,"scale":"shares"},{"title":"Early Crash Signal (AE)","url":"/papers/ssrn/4930925/","summary":"The paper proposes a simple early-warning signal that watches hidden market patterns found by a neural network (an autoencoder); when those patterns start moving together it warns of systemic market risk, helping investors time sell-offs and improve returns.","featured":"2025-11-19","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":565,"scale":"shares"},{"title":"Probabilistic Rule Models as Diagnostic Layers: Interpreting Structural Concept Drift in Post-Crisis Finance","url":"/papers/arxiv/2510.26627/","summary":"Presents a simple, interpretable rule-based correction layer that detects and explains shifts in credit-risk scores, validated on 2008 mortgage data.","featured":"2025-11-04","label":"arXiv","topic":"Risk, Credit & Banking","cites":0,"score":4,"scale":"shares"},{"title":"Implicit quantile preferences of the Fed and the Taylor rule","url":"/papers/arxiv/2510.24362/","summary":"Models a central bank that maximizes a quantile (not expected) utility, linking hawkish/dovish leanings to that quantile and finding the Fed is mostly dovish.","featured":"2025-11-04","label":"arXiv","topic":"Risk, Credit & Banking","cites":0,"score":14,"scale":"shares"},{"title":"Optimized Multi-Level Monte Carlo Parametrization and Antithetic Sampling for Nested Simulations","url":"/papers/arxiv/2510.18995/","summary":"Proposes an improved multilevel Monte Carlo with antithetic sampling to estimate loss probabilities and Value‑at‑Risk more efficiently for irregular payoffs, illustrated in life insurance.","featured":"2025-10-27","label":"arXiv","topic":"Risk, Credit & Banking","cites":1,"score":5,"scale":"shares"},{"title":"Centered‐Innovation MA for Bayesian Dirichlet ARMA: Theoretical Equivalence and an Application to Bank‐Asset Shares","url":"/papers/arxiv/2510.18903/","summary":"We remove bias in Dirichlet compositional time series by centering MA innovations using digamma adjustments, yielding unbiased MA terms, better forecasts, and cleaner MCMC diagnostics.","featured":"2025-10-27","label":"arXiv","topic":"Risk, Credit & Banking","cites":2,"score":11,"scale":"shares"},{"title":"Bank Failure Prediction","url":"/papers/repec/bba-j00001-v-3-y-2024-i-1-p-129-144-d-169/","summary":"The study uses machine learning survival models to predict US bank failures, offering insights to enhance risk management in the banking sector.","featured":"2025-10-24","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":17,"scale":"shares"},{"title":"Model Monitoring: A General Framework with an Application to Non-life Insurance Pricing","url":"/papers/arxiv/2510.04556/","summary":"The research explores concept drift in non-life insurance pricing, offering an overview of methods, performance metrics, and a monitoring process to determine when model adjustments are required.","featured":"2025-10-09","label":"arXiv","topic":"Risk, Credit & Banking","cites":1,"score":10,"scale":"shares"},{"title":"A Unified Framework for Spatial and Temporal Treatment Effect Boundaries: Theory and Identification","url":"/papers/arxiv/2510.00754/","summary":"The paper introduces a theoretical framework for detecting and estimating treatment effect boundaries across space and time, offering tools to identify when local treatments become systemic and require policy intervention.","featured":"2025-10-03","label":"arXiv","topic":"Risk, Credit & Banking","cites":0,"score":10,"scale":"shares"},{"title":"A note on subadditivity of value at risks (VaRs): A new connection to comonotonicity","url":"/papers/doi/10-1017-jpr-2025-31/","summary":"The research reveals a new characteristic of value at risk (VaR), stating that its subadditivity holds for any confidence level only if the loss random variables are comonotonic.","featured":"2025-09-22","label":"arXiv","topic":"Risk, Credit & Banking","cites":5,"score":6,"scale":"shares"},{"title":"Why Bonds Fail Differently? Explainable Multimodal Learning for Multi-Class Default Prediction","url":"/papers/arxiv/2509.10802/","summary":"The study introduces EMDLOT, a new framework for predicting multi-class bond defaults in China's bond market, which outperforms traditional and deep learning models by combining numerical and textual data.","featured":"2025-09-22","label":"arXiv","topic":"Risk, Credit & Banking","cites":0,"score":12,"scale":"shares"},{"title":"An Interpretable Deep Learning Model for General Insurance Pricing","url":"/papers/arxiv/2509.08467/","summary":"The paper presents the Actuarial Neural Additive Model, a transparent deep learning model for insurance pricing that provides superior prediction accuracy and full transparency in its internal workings.","featured":"2025-09-13","label":"arXiv","topic":"Risk, Credit & Banking","cites":1,"score":6,"scale":"shares"},{"title":"Combining a Large Pool of Forecasts of Value-at-Risk and Expected Shortfall","url":"/papers/arxiv/2508.16919/","summary":"The article discusses various methods for predicting Value-at-Risk and Expected Shortfall, highlighting the effectiveness of a trimmed mean approach, probability averaging method, and performance-based weighting combining.","featured":"2025-08-29","label":"arXiv","topic":"Risk, Credit & Banking","cites":0,"score":8,"scale":"shares"},{"title":"From Coverage to Consequences: BMI, Health Behaviors, and Self-rated Health After Medicaid Contraction","url":"/papers/arxiv/2508.19155/","summary":"A study on Tennessee's 2005 Medicaid contraction found that loss of public health insurance led to increased Body Mass Index and prevalence of overweight or obesity among childless adults, possibly due to unmanaged health conditions.","featured":"2025-08-29","label":"arXiv","topic":"Risk, Credit & Banking","cites":0,"score":6,"scale":"shares"},{"title":"Propagation of carbon price shocks through the value chain: the mean-field game of defaults","url":"/papers/arxiv/2507.11353/","summary":"The study introduces a new framework to analyze the impact of carbon pricing in a multi-sector economy, highlighting the significant spillover effects and the importance of sectoral interdependencies in decarbonization.","featured":"2025-07-17","label":"arXiv","topic":"Risk, Credit & Banking","cites":1,"score":8,"scale":"shares"},{"title":"Potential Customer Lifetime Value in Financial Institutions: The Usage Of Open Banking Data to Improve CLV Estimation","url":"/papers/arxiv/2506.22711/","summary":"The research presents a framework that uses Open Banking data to estimate customer value across firms, potentially boosting profitability by 21.06%.","featured":"2025-07-03","label":"arXiv","topic":"Risk, Credit & Banking","cites":0,"score":4,"scale":"shares"},{"title":"Ambiguity Preference in Credit","url":"/papers/ssrn/5246313/","summary":"Ambiguity preference variables can forecast credit asset comovements, with lower-rated US credit assets being more affected by ambiguity aversion.","featured":"2025-06-25","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":44,"scale":"shares"},{"title":"EVT-Based Rate-Preserving Distributional Robustness for Tail Risk Functionals","url":"/papers/arxiv/2506.16230/","summary":"The study uses extreme value theory to create a Distributionally Robust Optimization formulation for worst-case Conditional Value-at-Risk evaluations, demonstrating its usefulness on both synthetic and real-world data.","featured":"2025-06-25","label":"arXiv","topic":"Risk, Credit & Banking","cites":0,"score":9,"scale":"shares"},{"title":"Benchmark-Neutral Risk-Minimization for insurance products and nonreplicable claims","url":"/papers/arxiv/2506.19494/","summary":"The research investigates the pricing and hedging of nonreplicable contingent claims like long-term insurance contracts using a benchmark-neutral pricing framework, suggesting an algorithmic refinancing strategy for working capital modeling.","featured":"2025-06-25","label":"arXiv","topic":"Risk, Credit & Banking","cites":3,"score":4,"scale":"shares"},{"title":"Optimal regulation and investment incentives in financial networks","url":"/papers/arxiv/2506.16648/","summary":"The research suggests financial regulation should be based on a firm's financial centrality and investment opportunities, and sometimes it's beneficial to limit one core bank's investments while allowing another to invest freely.","featured":"2025-06-25","label":"arXiv","topic":"Risk, Credit & Banking","cites":0,"score":16,"scale":"shares"},{"title":"Dynamic Reinsurance Treaty Bidding via Multi-Agent Reinforcement Learning","url":"/papers/arxiv/2506.13113/","summary":"The paper introduces a multi-agent reinforcement learning framework for reinsurance treaty bidding, showing its ability to enhance risk transfer efficiency and surpass traditional pricing methods in reinsurance markets.","featured":"2025-06-18","label":"arXiv","topic":"Risk, Credit & Banking","cites":2,"score":6,"scale":"shares"},{"title":"Failing Banks","url":"/papers/arxiv/2506.06082/","summary":"A study reveals that US bank failures from 1863 to 2024 are mainly due to worsening bank fundamentals like increasing asset losses and reliance on costly noncore funding.","featured":"2025-06-11","label":"arXiv","topic":"Risk, Credit & Banking","cites":18,"score":11,"scale":"shares"},{"title":"The Determinants of Net Interest Margin in the Turkish Banking Sector: Does Bank Ownership Matter?","url":"/papers/arxiv/2506.04384/","summary":"A study on the Turkish banking sector identifies operation diversity, credit risk, and operating costs as key factors influencing net interest margin, with impacts varying across different bank types.","featured":"2025-06-11","label":"arXiv","topic":"Risk, Credit & Banking","cites":15,"score":14,"scale":"shares"},{"title":"Enterprise Risk Management Mergers & Acquisitions","url":"/papers/ssrn/5275009/","summary":"The article discusses the discrepancy between the theoretical and practical value of Enterprise Risk Management, emphasizing the need to concentrate on ERM's potential to improve strategic decision-making.","featured":"2025-06-04","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"Big Data Analytics in Finance","url":"/papers/ssrn/5275567/","summary":"The piece highlights the benefits of using Big Data Analytics and predictive modeling in Risk Management within Banks and Financial Services Companies.","featured":"2025-06-04","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"Central Bank Communication with Public: Bank of England and Twitter (X)","url":"/papers/arxiv/2506.02559/","summary":"Research on 3.13 million tweets related to the Bank of England shows that content quality, timing, and media-rich posts are more effective in engaging audiences than post frequency, indicating that central banks need to update their digital communication strategies.","featured":"2025-06-04","label":"arXiv","topic":"Risk, Credit & Banking","cites":0,"score":13,"scale":"shares"},{"title":"Balancing Profit and Fairness in Risk-Based Pricing Markets","url":"/papers/arxiv/2506.00140/","summary":"The study introduces a new tax schedule and an open-source simulator, MarketSim, aimed at improving fairness in markets like health insurance and consumer credit by aligning private incentives with social objectives.","featured":"2025-06-04","label":"arXiv","topic":"Risk, Credit & Banking","cites":1,"score":19,"scale":"shares"},{"title":"The Bank of Italy’s Statistical Model for the Credit Assessment of Non-Financial Firms","url":"/papers/ssrn/5270521/","summary":"The Bank of Italy uses a combination of statistical models and expert assessments in its in-house credit assessment system to predict default probabilities of non-financial firms, aiding in monetary policy.","featured":"2025-05-30","label":"SSRN","topic":"Risk, Credit & Banking","cites":1,"score":4,"scale":"shares"},{"title":"Quantum Credit Default Prediction","url":"/papers/ssrn/5273166/","summary":"A new model combining quantum and classical machine learning has been proposed to improve the accuracy of credit default predictions in emerging markets.","featured":"2025-05-30","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"How important are ESG factors for banks' cost of debt? An empirical investigation","url":"/papers/ssrn/5270535/","summary":"The paper explores the link between banks' ESG scores and their funding costs, concluding that higher ESG ratings positively influence funding costs and that changes in ESG ratings significantly impact banks' bond yields.","featured":"2025-05-30","label":"SSRN","topic":"Risk, Credit & Banking","cites":7,"score":4,"scale":"shares"},{"title":"Data Governance for Global Banks","url":"/papers/ssrn/5263917/","summary":"The paper highlights the importance of robust data governance in banks for regulatory alignment, operational resilience, and accurate decision-making.","featured":"2025-05-30","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":3,"scale":"shares"},{"title":"Ukrainian Banks in Bond Market","url":"/papers/ssrn/5268333/","summary":"The article explores the paradox of Ukrainian banks' excessive activity in the government bonds market despite ample liquidity and positive financial results.","featured":"2025-05-30","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":3,"scale":"shares"},{"title":"Marginal Fairness: Fair Decision-Making under Risk Measures","url":"/papers/arxiv/2505.18895/","summary":"The article introduces a concept of marginal fairness for unbiased decision-making in sectors like insurance and finance, disregarding protected attributes such as race, gender, and religion.","featured":"2025-05-30","label":"arXiv","topic":"Risk, Credit & Banking","cites":2,"score":23,"scale":"shares"},{"title":"Recalibrating binary probabilistic classifiers","url":"/papers/arxiv/2505.19068/","summary":"The article discusses recalibrating binary probabilistic classifiers from a distribution shift perspective, introducing two new methods for conservative results in credit risk assessments.","featured":"2025-05-30","label":"arXiv","topic":"Risk, Credit & Banking","cites":1,"score":12,"scale":"shares"},{"title":"Financing Costs","url":"/papers/ssrn/5261698/","summary":"Family-owned firms' financing costs and credit ratings are more sensitive to market stress levels, with costs fluctuating more compared to non-family-owned firms.","featured":"2025-05-21","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"Advancements in Credit Score Analytics using Deep Learning and Predictive Modeling Techniques","url":"/papers/ssrn/5255128/","summary":"The article discusses the application of machine learning techniques, specifically Artificial Neural Networks, in credit scoring, allowing efficient management of large, complex datasets and in-depth analysis.","featured":"2025-05-21","label":"SSRN","topic":"Risk, Credit & Banking","cites":0,"score":2,"scale":"shares"},{"title":"Filtering in a hazard rate change-point model with financial and life-insurance applications","url":"/papers/arxiv/2505.13185/","summary":"The paper presents a new framework for estimating a hazard rate with an unobservable change-point, demonstrating its application in pricing credit-sensitive financial instruments and the potential for mispricing due to partial information.","featured":"2025-05-21","label":"arXiv","topic":"Risk, Credit & Banking","cites":0,"score":16,"scale":"shares"},{"title":"Ambiguity in Insurance","url":"/papers/ssrn/5250219/","summary":"Price movements in catastrophe bonds can be predicted by ambiguity preference in economic outlook and natural disasters, especially during crises and geopolitical conflicts.","featured":"2025-05-14","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":3,"scale":"shares"},{"title":"AI for Specialty Insurance Analytics","url":"/papers/ssrn/5238912/","summary":"The creation of AI solutions for specific insurance predictions is vital due to industry consolidation and the rise of InsurTech startups, with gaps in domain knowledge and machine learning guidance.","featured":"2025-05-14","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"AI in Financial Risk Management","url":"/papers/ssrn/5243241/","summary":"The paper explores the use of artificial intelligence in improving financial risk management in financial institutions, focusing on its application in various risk types.","featured":"2025-05-07","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":3,"scale":"shares"},{"title":"Study on Negative Treasury Haircuts","url":"/papers/ssrn/5239611/","summary":"The research investigates the supply of leverage in the Treasury market by large dealer banks, showing that their balance sheet capacity significantly influences the market's fragility.","featured":"2025-05-07","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"A stochastic Gordon–Loeb model for optimal cybersecurity investment under clustered attacks","url":"/papers/arxiv/2505.01221/","summary":"A model is developed for optimal cybersecurity investment, showing that considering attack clustering improves investment policies and risk management.","featured":"2025-05-07","label":"arXiv","topic":"Risk, Credit & Banking","cites":4,"score":15,"scale":"shares"},{"title":"Exploring different subtypes of recurrent event Cox-regression models in modelling lifetime default risk: A tutorial","url":"/papers/arxiv/2505.01044/","summary":"The study examines Cox-models in loan default estimates, suggesting that ignoring recurrent defaults may not significantly impact estimates depending on their frequency.","featured":"2025-05-07","label":"arXiv","topic":"Risk, Credit & Banking","cites":0,"score":11,"scale":"shares"},{"title":"Systemic Risk in the European Insurance Sector","url":"/papers/arxiv/2505.02635/","summary":"The study investigates the relationship between the European insurance sector and financial markets, finding that the insurance market contributes to systemic risk, especially during financial crises.","featured":"2025-05-07","label":"arXiv","topic":"Risk, Credit & Banking","cites":2,"score":10,"scale":"shares"},{"title":"DebtStreamness: an ecological approach to credit flows in interfirm networks","url":"/papers/arxiv/2505.01326/","summary":"Ecological Credit Flows: The research introduces DebtStreamness, a new metric to analyze firms' positions in credit chains, showing that these chains are typically short and some firms serve as lenders to others in the chain.","featured":"2025-05-07","label":"arXiv","topic":"Risk, Credit & Banking","cites":0,"score":23,"scale":"shares"},{"title":"Credit Risk in Supply Chain Finance of Chinese Enterprises","url":"/papers/ssrn/5234377/","summary":"The research uses machine learning to predict credit risk in supply chain financial services and examines the influence of supply chains on listed service companies.","featured":"2025-04-30","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"Can Nash inform capital requirements? Allocating systemic risk measures","url":"/papers/arxiv/2504.20413/","summary":"The study introduces a Nash allocation rule, based on game theory, for distributing systemic risk among financial institutions, proving its effectiveness with numerical case studies.","featured":"2025-04-30","label":"arXiv","topic":"Risk, Credit & Banking","cites":0,"score":17,"scale":"shares"},{"title":"Banks and Insurers Response to Rate Hikes","url":"/papers/ssrn/5226193/","summary":"Interest rate hikes by central banks due to COVID19 and Ukraine crisis significantly impact Eurozone and U.S. banks and insurers' stocks and credit default swaps.","featured":"2025-04-23","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":3,"scale":"shares"},{"title":"Optimal Capital Structure for Life Insurance Companies Offering Surplus Participation","url":"/papers/arxiv/2504.12851/","summary":"The study modifies Leland's dynamic capital structure model to explain life insurance contracts with guaranteed payment and surplus participation, emphasizing the impact of contract duration and tax rate on the optimal participation rate.","featured":"2025-04-23","label":"arXiv","topic":"Risk, Credit & Banking","cites":0,"score":12,"scale":"shares"},{"title":"Systemic risk mitigation in supply chains through network rewiring","url":"/papers/arxiv/2504.12955/","summary":"Research shows that strategically rearranging supplier-customer connections can significantly lower supply chain risk by 16-50% without affecting production.","featured":"2025-04-23","label":"arXiv","topic":"Risk, Credit & Banking","cites":5,"score":17,"scale":"shares"},{"title":"Impact of Open Government Data on Default in China","url":"/papers/ssrn/5218902/","summary":"Open Government Data (OGD) has helped decrease personal default rates in China, especially in high-risk areas and among younger and middle-aged people.","featured":"2025-04-16","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":5,"scale":"shares"},{"title":"Optimal Investment in Equity and Credit Default Swaps in the Presence of Default","url":"/papers/arxiv/2504.08085/","summary":"The study investigates the use of credit default swaps (CDS) to reduce default risk in the equity market, indicating that optimal CDS policies cover both immediate equity losses and future trading losses.","featured":"2025-04-16","label":"arXiv","topic":"Risk, Credit & Banking","cites":0,"score":22,"scale":"shares"},{"title":"Structural robustness of the international food supply network under external shocks and its determinants","url":"/papers/arxiv/2504.08857/","summary":"Research on the global food supply network shows its increased robustness over time, but warns that severe shocks to key suppliers like the US and India could cause a systemic collapse.","featured":"2025-04-16","label":"arXiv","topic":"Risk, Credit & Banking","cites":1,"score":12,"scale":"shares"},{"title":"Total Return Swap Shareholder Wealth Impact","url":"/papers/ssrn/5206488/","summary":"Research indicates that total return swaps used for corporate governance can negatively affect minority shareholders, but can be beneficial when used for risk management.","featured":"2025-04-09","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":7,"scale":"shares"},{"title":"Comparative Credit Risk Model Analysis","url":"/papers/ssrn/5204562/","summary":"The analysis reveals that gradient boosting models, specifically CatBoost and LightGBM, are more effective than traditional models in assessing credit risk.","featured":"2025-04-09","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"Community Bank Impact","url":"/papers/ssrn/5202564/","summary":"The Community Bank Leverage Ratio (CBLR) increases risk-taking and profitability of small U.S. community banks, primarily through asset contraction, a study finds.","featured":"2025-04-09","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":3,"scale":"shares"},{"title":"Optimal macroprudential policy with preemptive bailouts","url":"/papers/arxiv/2504.04636/","summary":"Optimal financial sector regulation can improve stability by considering the impact of banks' decisions and redistributing future net worth, reducing the likelihood of banking crises. Macroprudential policy should include both taxes and subsidies.","featured":"2025-04-09","label":"arXiv","topic":"Risk, Credit & Banking","cites":0,"score":10,"scale":"shares"},{"title":"Geopolitical Risk in Banks","url":"/papers/ssrn/5198995/","summary":"The Russia-Ukraine conflict has increased geopolitical risk premiums in European banks' debt and equity markets, especially for banks with significant credit exposures to Russia.","featured":"2025-04-02","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":3,"scale":"shares"},{"title":"A cost of capital approach to determining the LGD discount rate","url":"/papers/arxiv/2503.23992/","summary":"The paper introduces a new method for estimating banking losses, using a market-consistent price for defaulted loans.","featured":"2025-04-02","label":"arXiv","topic":"Risk, Credit & Banking","cites":1,"score":12,"scale":"shares"},{"title":"Russian Banks Efficiency","url":"/papers/ssrn/5193312/","summary":"The research assesses the efficiency of Russian banks from 2000 to 2023, identifying influencing factors and future trends, and notes a general decline in bank efficiency due to economic and political crises.","featured":"2025-03-26","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":3,"scale":"shares"},{"title":"Feds SMCCF Analysis","url":"/papers/ssrn/5194501/","summary":"The effectiveness of the Secondary Market Corporate Credit Facility in stabilizing the US corporate bond market during the COVID-19 pandemic is analyzed, highlighting the positive impact of the Federal Reserve's actions.","featured":"2025-03-26","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":4,"scale":"shares"},{"title":"Unleashing the power of text for credit default prediction: Comparing human-written and generative AI-refined texts","url":"/papers/arxiv/2503.18029/","summary":"The study shows that using AI language model, ChatGPT, in lending decisions can improve credit default predictions and increase profitability in finance.","featured":"2025-03-26","label":"arXiv","topic":"Risk, Credit & Banking","cites":19,"score":13,"scale":"shares"},{"title":"Big data in relationship banking","url":"/papers/ssrn/5178356/","summary":"A credit market competition model suggests that Big Data screening can reduce bank profits and increase consumer surplus.","featured":"2025-03-20","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"Risk Management Mistakes with Correlation","url":"/papers/ssrn/5155665/","summary":"The article points out common errors in using Pearson's correlation in risk management, offering counterexamples and R code for clarity.","featured":"2025-03-20","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":81,"scale":"shares"},{"title":"Trade Credit Default *","url":"/papers/ssrn/5153753/","summary":"The study investigates the role of trade-credit default in the transmission of macro shocks, introducing two new mechanisms - a markup effect and an insurance effect.","featured":"2025-03-20","label":"SSRN","topic":"Risk, Credit & Banking","cites":0,"score":20,"scale":"shares"},{"title":"A Study on the Impact of Environmental Liability Insurance on Industrial Carbon Emissions","url":"/papers/arxiv/2503.15445/","summary":"Research shows environmental liability insurance can lower industrial carbon emissions, especially in developed industrial regions.","featured":"2025-03-20","label":"arXiv","topic":"Risk, Credit & Banking","cites":0,"score":14,"scale":"shares"},{"title":"Rolling Forward: Enhancing LightGCN with Causal Graph Convolution for Credit Bond Recommendation","url":"/papers/doi/10-1145-3677052-3698683/","summary":"The study presents an improved version of the Light Graph Convolutional Network that learns over time, enhancing its performance in time-sensitive applications, especially in recommending financial products.","featured":"2025-03-20","label":"arXiv","topic":"Risk, Credit & Banking","cites":2,"score":13,"scale":"shares"},{"title":"XVA modelling: validation, performance and model risk management","url":"/papers/doi/10-1007-s10479-023-05323-4/","summary":"The article explores the impact of XVA on derivatives pricing, emphasizing its model risk and computational effort, and offers a guide for creating a strong model for collateralized exposure and XVA.","featured":"2025-03-12","label":"arXiv","topic":"Risk, Credit & Banking","cites":4,"score":312,"scale":"shares"},{"title":"DEEP LEARNING FOR FINANCIAL STRESS TESTING: A DATA-DRIVEN APPROACH TO RISK MANAGEMENT","url":"/papers/ssrn/5146509/","summary":"A new deep learning-based framework for financial stress testing is introduced, combining financial indicators to improve risk prediction accuracy and reduce financial risks.","featured":"2025-03-05","label":"SSRN","topic":"Risk, Credit & Banking","cites":15,"score":31,"scale":"shares"},{"title":"Investor Structure and Credit Spreads","url":"/papers/ssrn/5145282/","summary":"The article provides new insights into the factors affecting bond credit spreads in China, with a focus on wealth management products and central bank policies.","featured":"2025-03-05","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":12,"scale":"shares"},{"title":"The Effect of Financial Risks on the Financial Performance of Banks listed on Bahrain Bourse: An Empirical Stud","url":"/papers/ssrn/5147102/","summary":"Capital risks significantly impact the financial performance of banks listed on the Bahrain Bourse.","featured":"2025-03-05","label":"SSRN","topic":"Risk, Credit & Banking","cites":1,"score":8,"scale":"shares"},{"title":"Multi-Layer Deep xVA Credit Models","url":"/papers/ssrn/5147413/","summary":"The authors suggest a structural default model for portfolio-wide valuation adjustments, using a deep BSDE approach to handle each layer sequentially, making the computation manageable.","featured":"2025-03-05","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":75,"scale":"shares"},{"title":"Tail Risk Management","url":"/papers/repec/eee-jomega-v-133-y-2025-i-c-s0305048324002135/","summary":"Two new deep learning frameworks have been proposed for estimating financial risk measures, which are more efficient than existing methods.","featured":"2025-03-05","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":27,"scale":"shares"},{"title":"Determinants of Bank Performance","url":"/papers/repec/bco-ncafaa-v-9-y-2023-p-26-41/","summary":"The paper suggests new research areas in understanding banks' performance, focusing on digital transformation, AI, and the effects of COVID-19.","featured":"2025-03-05","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":1,"scale":"shares"},{"title":"Credit Risk Classification using ML","url":"/papers/ssrn/5138444/","summary":"The paper uses a machine learning approach to estimate credit risk and classify bond price risk based on financial metric fluctuations.","featured":"2025-02-26","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":22,"scale":"shares"},{"title":"Multi-Layer Deep xVA: Structural Credit Models, Measure Changes and Convergence Analysis","url":"/papers/arxiv/2502.14766/","summary":"The article suggests a new model for portfolio valuation adjustments that uses a deep BSDE approach to handle each layer separately, making it more computationally efficient and adaptable to complex portfolios.","featured":"2025-02-26","label":"arXiv","topic":"Risk, Credit & Banking","cites":3,"score":20,"scale":"shares"},{"title":"A data-driven econo-financial stress-testing framework to estimate the effect of supply chain networks on financial systemic risk","url":"/papers/arxiv/2502.17044/","summary":"The research investigates how systemic risk in production networks can lead to financial systemic risk through supply chain contagion, and proposes a financial stress-testing framework that combines supply chain and interbank network layers.","featured":"2025-02-26","label":"arXiv","topic":"Risk, Credit & Banking","cites":3,"score":14,"scale":"shares"},{"title":"Decoding Financial Health in Kenyas' Medical Insurance Sector: A Data-Driven Cluster Analysis","url":"/papers/arxiv/2502.17072/","summary":"A study using advanced clustering techniques emphasizes the need for transparency and timely reporting in the financial performance of medical sector insurance companies.","featured":"2025-02-26","label":"arXiv","topic":"Risk, Credit & Banking","cites":1,"score":12,"scale":"shares"},{"title":"Modelling the term-structure of default risk under IFRS 9 within a multistate regression framework","url":"/papers/arxiv/2502.14479/","summary":"A study comparing three loan behavior modeling techniques finds multinomial logistic regression to be the most effective, potentially improving loss reserve estimates in banking.","featured":"2025-02-26","label":"arXiv","topic":"Risk, Credit & Banking","cites":4,"score":11,"scale":"shares"},{"title":"Community Bank Establishment and Consumption Growth: Evidence from Panel Study of Income Dynamics in USA","url":"/papers/arxiv/2502.14257/","summary":"Data from 1980 to 1990 shows that the creation of community banks boosts local household consumption by increasing income and reducing precautionary savings.","featured":"2025-02-26","label":"arXiv","topic":"Risk, Credit & Banking","cites":0,"score":13,"scale":"shares"},{"title":"Credit Risk Upgrade","url":"/papers/ssrn/5129785/","summary":"The piece suggests that data from US corporate bond holdings can provide more accurate and timely information than traditional credit ratings in fixed income markets.","featured":"2025-02-19","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":40,"scale":"shares"},{"title":"Climate Risks in Real Estate","url":"/papers/ssrn/5120353/","summary":"The study shows how physical climate risks, specifically river floodings, can affect the credit risk parameters and internal capital calibration of banks.","featured":"2025-02-19","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":94,"scale":"shares"},{"title":"Simple Climate Stress Testing","url":"/papers/ssrn/5130573/","summary":"The BKMN model is presented to help financial institutions perform climate stress tests, connecting temperature and CO2 prices to financial market effects.","featured":"2025-02-19","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":116,"scale":"shares"},{"title":"The Relative Entropy of Expectation and Price","url":"/papers/arxiv/2502.08613/","summary":"The article explores the non-linear pricing in incomplete securities markets, measuring strategic risks using an entropic risk metric and adjusting the price for market incompleteness and default risk.","featured":"2025-02-19","label":"arXiv","topic":"Risk, Credit & Banking","cites":1,"score":15,"scale":"shares"},{"title":"Stock Price Prediction in Eurozone Banks","url":"/papers/repec/vls-finstu-v-28-y-2024-i-4-p-29-42/","summary":"The paper compares the effectiveness of different models in predicting European banking sector stock prices, concluding that traditional machine learning models outperform advanced deep learning models.","featured":"2025-02-19","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":13,"scale":"shares"},{"title":"Credit Risk Modeling Optimization","url":"/papers/ssrn/5113745/","summary":"The study uses Genetic Algorithms to simplify and improve accuracy in Credit Risk Modeling, particularly for default prediction and reducing Loss Given Default.","featured":"2025-02-05","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":11,"scale":"shares"},{"title":"Predicting Bank Distress in Europe: Using Machine Learning and a Novel Definition of Distress","url":"/papers/ssrn/5098026/","summary":"The paper presents a machine learning-based early warning system to predict distress in large European banks, with the random forest model performing best.","featured":"2025-01-23","label":"SSRN","topic":"Risk, Credit & Banking","cites":1,"score":23,"scale":"shares"},{"title":"Machine Learning Based Risk Assessment for Financial Management in Big Data IoT Credit","url":"/papers/ssrn/5086671/","summary":"The article highlights the importance of machine learning in evaluating financial management in big data and IoT in the credit industry, improving creditworthiness accuracy.","featured":"2025-01-23","label":"SSRN","topic":"Risk, Credit & Banking","cites":27,"score":5,"scale":"shares"},{"title":"Loss of earning capacity in Denmark – an actuarial perspective","url":"/papers/arxiv/2501.11578/","summary":"The article explores the challenges and opportunities in risk assessment and mitigation for loss of earning capacity insurance in Denmark, highlighting the need for innovative actuarial approaches.","featured":"2025-01-23","label":"arXiv","topic":"Risk, Credit & Banking","cites":1,"score":2,"scale":"shares"},{"title":"Sovereign Debt Default and Climate Risk","url":"/papers/arxiv/2501.11552/","summary":"The paper investigates the link between sovereign debt default and environmental factors, concluding that climate risk does not significantly affect the decision to default in developing and low-income countries.","featured":"2025-01-23","label":"arXiv","topic":"Risk, Credit & Banking","cites":1,"score":6,"scale":"shares"},{"title":"Implementation of an Asymmetric Adjusted Activation Function for Class Imbalance Credit Scoring","url":"/papers/arxiv/2501.12285/","summary":"The new ASIG activation function improves credit scoring by adjusting to imbalanced datasets, outperforming traditional methods in the financial industry.","featured":"2025-01-23","label":"arXiv","topic":"Risk, Credit & Banking","cites":2,"score":3,"scale":"shares"},{"title":"Class-Imbalanced-Aware Adaptive Dataset Distillation for Scalable Pretrained Model on Credit Scoring","url":"/papers/arxiv/2501.10677/","summary":"A new framework that combines dataset distillation techniques with pretrained models improves credit scoring technologies, expanding the use of large models in finance.","featured":"2025-01-23","label":"arXiv","topic":"Risk, Credit & Banking","cites":0,"score":2,"scale":"shares"},{"title":"Neural Networks for Insurance Pricing with Frequency and Severity Data: A Benchmark Study from Data Preprocessing to Technical Tariff","url":"/papers/doi/10-1080-10920277-2025-2451860/","summary":"The article discusses the application of deep learning in insurance pricing, comparing different models and offering a method to interpret neural network insights through generalized linear models.","featured":"2025-01-23","label":"arXiv","topic":"Risk, Credit & Banking","cites":16,"score":27,"scale":"shares"},{"title":"Credit Risk Modeling","url":"/papers/ssrn/5093887/","summary":"The article discusses the use of normalizing flows and invertible neural networks in credit risk modeling to enhance default time estimation and portfolio risk assessment.","featured":"2025-01-15","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":28,"scale":"shares"},{"title":"Use of AI and ML in Banking & Finance to Improve Decision-Making, Automate Processes, and Enhance Customer Experiences","url":"/papers/ssrn/5086625/","summary":"The manuscript discusses the potential of AI and ML in finance and regulatory compliance, but also points out challenges related to data privacy, algorithmic bias, and model explainability.","featured":"2025-01-08","label":"SSRN","topic":"Risk, Credit & Banking","cites":5,"score":3,"scale":"shares"},{"title":"BANKRL: Hierarchical Reinforcement Learning for Banks","url":"/papers/ssrn/5071840/","summary":"Hierarchical Reinforcement Learning for Banks: BANKRL, a new framework for bank management using multiagent reinforcement learning, balances profitability, risk, and regulatory compliance.","featured":"2025-01-08","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":41,"scale":"shares"},{"title":"Bank Capital and XVAs","url":"/papers/ssrn/5065834/","summary":"The study investigates the impact of valuation adjustments on systemic US banks' derivatives portfolios, providing insights into how banks manage these adjustments and their effects on balance sheets.","featured":"2025-01-01","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":4,"scale":"shares"},{"title":"Machine and Deep Learning for Credit Scoring: A compliant approach","url":"/papers/arxiv/2412.20225/","summary":"The research proposes new BASEL 2 and 3 compliant techniques for credit scoring in banks, demonstrating improved performance and default capture rate with Gradient Boosting Machines.","featured":"2025-01-01","label":"arXiv","topic":"Risk, Credit & Banking","cites":6,"score":3,"scale":"shares"},{"title":"Quantiles under ambiguity and risk sharing","url":"/papers/arxiv/2412.19546/","summary":"The study introduces Choquet Expected Shortfall, a new class of risk measures, and provides optimization algorithms and examples using financial data.","featured":"2025-01-01","label":"arXiv","topic":"Risk, Credit & Banking","cites":2,"score":2,"scale":"shares"},{"title":"Mitigating optimistic bias in entropic risk estimation and optimization","url":"/papers/arxiv/2409.19926/","summary":"A novel bootstrapping method is suggested to reduce bias in the empirical entropic risk estimator, a tool used in high-stakes decision making, and is applied to insurance contract design.","featured":"2025-01-01","label":"Machine learning","topic":"Risk, Credit & Banking","cites":1,"score":18,"scale":"shares"},{"title":"Creditor Rights and Corporate Investment in India","url":"/papers/ssrn/5056284/","summary":"The introduction of the Insolvency and Bankruptcy Code in India has improved investment efficiency and eased financial constraints, especially for business group-linked firms.","featured":"2024-12-18","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"Reciprocity in Interbank Markets","url":"/papers/arxiv/2412.10329/","summary":"The research explores the interdependence of banks in financial networks, revealing that smaller banks withdrew from high-value trades during the financial crisis.","featured":"2024-12-18","label":"arXiv","topic":"Risk, Credit & Banking","cites":1,"score":5,"scale":"shares"},{"title":"Machine Learning in Credit Scoring","url":"/papers/repec/eee-aosoci-v-113-y-2024-i-c-s0361368224000278/","summary":"Research in a Chinese internet company shows machine learning credit scoring models prioritize data trails over default risk, reducing human experts' role to machine learning facilitators.","featured":"2024-12-18","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":43,"scale":"shares"},{"title":"Global Debt Management","url":"/papers/ssrn/5045732/","summary":"The study reveals that active debt management decisions, such as prepayment, are less beneficial for firms in emerging markets, particularly under tight global credit conditions.","featured":"2024-12-12","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":14,"scale":"shares"},{"title":"Systemic Risk in FinTech and Traditional Finance","url":"/papers/repec/taf-eurjfi-v-30-y-2024-i-18-p-2157-2190/","summary":"The study uses machine learning to identify key factors affecting systemic risk in FinTech and traditional financial institutions, including market volatility, individual stock volatility, and market capitalization, especially under extreme market conditions.","featured":"2024-12-12","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":14,"scale":"shares"},{"title":"Self-Protection and Insurance Demand with Convex Premium Principles","url":"/papers/arxiv/2411.19436/","summary":"The article investigates the relationship between self-protection and insurance demand, indicating that while they usually complement each other, moral hazard can turn this into a substitution effect.","featured":"2024-12-04","label":"arXiv","topic":"Risk, Credit & Banking","cites":3,"score":2,"scale":"shares"},{"title":"Model Comparison","url":"/papers/repec/ora-journl-v-2-y-2023-i-2-p-67-75/","summary":"The study finds logistic regression more efficient than decision tree models in identifying defaulted loans in Central Credit Information System data.","featured":"2024-12-04","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":4,"scale":"shares"},{"title":"Bond Defaults in China: Prediction using Machine Learning","url":"/papers/ssrn/5030065/","summary":"A machine learning model has been developed that can predict credit bond defaults in the Chinese market with over 90% accuracy, surpassing traditional methods.","featured":"2024-11-27","label":"SSRN","topic":"Risk, Credit & Banking","cites":0,"score":2,"scale":"shares"},{"title":"CDO Exposure Regulation","url":"/papers/ssrn/5029178/","summary":"The Recourse Rule, which reduced capital requirements for top-rated ABS CDO tranches, contributed to the financial distress of large commercial banks during the 2007-2009 crisis.","featured":"2024-11-27","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":62,"scale":"shares"},{"title":"Digital Assets Financial Stability Risks","url":"/papers/ssrn/5029118/","summary":"The financial stability risks posed by the rapid growth of digital assets are minimal due to the small size of the digital ecosystem and its limited links with the traditional financial system.","featured":"2024-11-27","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":10,"scale":"shares"},{"title":"Systemic Risk Measures from 1927-2023","url":"/papers/ssrn/5030262/","summary":"Measures of systemic risk based on the comovements of US financial firms' stock returns under stress can predict market outcomes, bank failures, and balance-sheet results from 1927 to 2023.","featured":"2024-11-27","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":3,"scale":"shares"},{"title":"Some remarks on the effect of risk sharing and diversification for infinite mean risks","url":"/papers/arxiv/2411.10139/","summary":"The research explores the negative impact of risk sharing in insurance models with infinite mean, particularly in distributions more skewed than a Cauchy distribution.","featured":"2024-11-20","label":"arXiv","topic":"Risk, Credit & Banking","cites":13,"score":2,"scale":"shares"},{"title":"Peer-to-peer Risk-sharing with Losses","url":"/papers/ssrn/5013193/","summary":"A study on catastrophic loss insurance suggested that diversifying such losses could be detrimental, recommending no diversification instead.","featured":"2024-11-13","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":4,"scale":"shares"},{"title":"Stress Testing US Banks with ML","url":"/papers/repec/eee-finana-v-95-y-2024-i-pc-s1057521924004083/","summary":"The article highlights the role of machine learning in improving risk analysis during stress tests, uncovering complex macro-financial connections and enhancing risk evaluation in economic downturns.","featured":"2024-11-13","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":17,"scale":"shares"},{"title":"Decomposing the Greenium","url":"/papers/ssrn/5006876/","summary":"The greenium, or yield difference between green and conventional bonds, is primarily paid by investment funds, banks, and insurance companies, with their decisions influenced by various motivations and financial frictions.","featured":"2024-11-06","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":3,"scale":"shares"},{"title":"A Personal Data Value at Risk (Pd-VaR) Approach","url":"/papers/arxiv/2411.03217/","summary":"The second article proposes a quantitative method for risk-based compliance in data protection, highlighting the need for a shift towards using data protection analytics and quantitative risk analysis.","featured":"2024-11-06","label":"arXiv","topic":"Risk, Credit & Banking","cites":0,"score":6,"scale":"shares"},{"title":"It Takes Three to Ceilidh: Pension System and Multidimensional Poverty Mitigation in China","url":"/papers/arxiv/2411.02807/","summary":"Research indicates that greater involvement in China's three-pillar pension system from 2012-2020 has helped decrease multidimensional poverty, emphasizing the significance of state social insurance, enterprise annuity, and individual commercial insurance.","featured":"2024-11-06","label":"arXiv","topic":"Risk, Credit & Banking","cites":0,"score":2,"scale":"shares"},{"title":"Assessing the regulatory framework of financial institutions in Canada in the context of international climate risk management practices and Canadian net zero emission targets","url":"/papers/arxiv/2411.02668/","summary":"An evaluation of Canada's financial regulatory frameworks for climate risk disclosure identifies areas for improvement to meet energy net zero targets, comparing it to international standards.","featured":"2024-11-06","label":"arXiv","topic":"Risk, Credit & Banking","cites":0,"score":2,"scale":"shares"},{"title":"Machine Learning in Banking","url":"/papers/repec/kap-compec-v-64-y-2024-i-3-d-10-1007-s10614-023-10514-z/","summary":"Machine learning was used to predict default risk in financial institutions, with bailout probability, market share, and market-to-book ratio being key variables.","featured":"2024-11-06","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":24,"scale":"shares"},{"title":"Time-Series Foundation AI Model for Value-at-Risk Forecasting","url":"/papers/arxiv/2410.11773/","summary":"The research highlights the superior performance of a time-series model, TimesFM, in forecasting Value-at-Risk, with fine-tuning further enhancing the results.","featured":"2024-10-31","label":"arXiv","topic":"Risk, Credit & Banking","cites":8,"score":5,"scale":"shares"},{"title":"Accounting Comparability","url":"/papers/ssrn/4993512/","summary":"The research indicates that firms with higher accounting comparability have lower ESG reputational risk, reduced capital costs, and increased investment activity, emphasizing the role of comparability in financial decision-making and risk management.","featured":"2024-10-23","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":3,"scale":"shares"},{"title":"Bank Securities Management","url":"/papers/ssrn/4991701/","summary":"A study reveals that US banks increased their interest rate risk in 2022-23 due to rapid rate changes and reluctance to sell bonds at a discount.","featured":"2024-10-23","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":6,"scale":"shares"},{"title":"Activist Investing: Credit Effects","url":"/papers/ssrn/4991711/","summary":"Credit Effects: Hedge fund activism increases firm value but negatively impacts existing bondholders, with those selling target firm debt post-intervention experiencing higher losses.","featured":"2024-10-23","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"CSFs in Risk Management in Nigerian Banks","url":"/papers/ssrn/4989226/","summary":"The study explores key success factors in risk management within the Nigerian banking system from 1960 to now, using interviews and questionnaires.","featured":"2024-10-17","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":6,"scale":"shares"},{"title":"Big Data Analytics for Risk Management","url":"/papers/ssrn/4982774/","summary":"Big Data analytics enhances IT service delivery risk management by enabling real-time risk identification, assessment, and mitigation.","featured":"2024-10-17","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"Optimal mutual insurance against systematic longevity risk","url":"/papers/arxiv/2410.07749/","summary":"The article discusses how two collective pension funds can mutually insure each other against systematic longevity risk, with the success of this insurance depending on how similar their risk preferences are.","featured":"2024-10-17","label":"arXiv","topic":"Risk, Credit & Banking","cites":2,"score":2,"scale":"shares"},{"title":"ERM Impact on Performance","url":"/papers/repec/pal-palcom-v-11-y-2024-i-1-d-10-1057-s41599-024-03871-z/","summary":"A study finds that Turkish banking firms adopting enterprise risk management see improved performance and value, and reduced risks, suggesting the use of a partial least squares regression model for predictions.","featured":"2024-10-17","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":12,"scale":"shares"},{"title":"Spatio-Temporal Machine Learning for Mortgage Credit Risk","url":"/papers/ssrn/4975440/","summary":"A new machine learning model for credit risk combines tree-boosting with a latent spatiotemporal Gaussian process model, offering more accurate predictions of default probabilities and loan portfolio losses.","featured":"2024-10-09","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"Drivers of Credited Interest Rate on UL Insurance","url":"/papers/ssrn/4977807/","summary":"The research explores the factors influencing the credited interest rate on universal life insurance in China, showing a positive long-term effect of insurance company operations and market interest rate trends on credited interest rates.","featured":"2024-10-09","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"Capital Requirements in Pillar 1 or Pillar 2: Does it Matter for Market Discipline?","url":"/papers/ssrn/4979554/","summary":"The research shows that bank Credit Default Swaps (CDS) are influenced by regulatory capital ratios, with markets reacting more to changes in capital requirements if implemented via Pillar 1 risk weights.","featured":"2024-10-09","label":"SSRN","topic":"Risk, Credit & Banking","cites":0,"score":3,"scale":"shares"},{"title":"Bank Credit Lines","url":"/papers/ssrn/4979396/","summary":"The research contradicts previous theories, stating that non-retail funding, particularly wholesale funding, significantly drives banks' contingent commitments, not traditional retail deposits.","featured":"2024-10-09","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"Caution with Credit-Sensitive Rates","url":"/papers/ssrn/4971400/","summary":"The article discusses the pros and cons of credit-sensitive rates as alternatives to LIBOR, emphasizing their risk management benefits and vulnerability during market stress.","featured":"2024-10-03","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"The Interdependent Relationship between Interest and Non-Interest Income of Indian Banks: A Study of Diversification of Income, Risk, and Traditional vs. Non-Traditional Banking Activities","url":"/papers/ssrn/4972716/","summary":"Diversification and Risk: The article studies the transition of Indian banks from earning through interest to non-interest sources, and how this diversification affects risk in both traditional and non-traditional banking.","featured":"2024-10-03","label":"SSRN","topic":"Risk, Credit & Banking","cites":2,"score":5,"scale":"shares"},{"title":"Improved Hardness Results for the Clearing Problem in Financial Networks with Credit Default Swaps","url":"/papers/arxiv/2409.18717/","summary":"The study investigates computational issues in banking networks, particularly in calculating clearing payments after financial shocks. It offers enhanced solutions, including two that are proven to be complete in the realm of real numbers.","featured":"2024-10-03","label":"arXiv","topic":"Risk, Credit & Banking","cites":3,"score":2,"scale":"shares"},{"title":"The Impact of Implicit Government Guarantee on Credit Rating of Municipal Investment Bonds","url":"/papers/arxiv/2409.13957/","summary":"The study reveals that implicit government guarantees can improve municipal investment bond ratings, especially in less developed areas, based on text mining analysis.","featured":"2024-09-25","label":"arXiv","topic":"Risk, Credit & Banking","cites":0,"score":5,"scale":"shares"},{"title":"Credit Risk Management","url":"/papers/repec/ids-ijmpra-v-17-y-2024-i-5-p-509-521/","summary":"The article examines the application of AI in creating credit scoring models by banks to assess the creditworthiness of borrowers.","featured":"2024-09-25","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":14,"scale":"shares"},{"title":"Sovereign vs. Corporate Debt and Default: More Similar than You Think","url":"/papers/ssrn/4955265/","summary":"Despite their fundamental differences, high-yield corporate and emerging market sovereign bonds have displayed similar risk-return patterns, default rates, and haircuts over the past two decades.","featured":"2024-09-18","label":"SSRN","topic":"Risk, Credit & Banking","cites":2,"score":4,"scale":"shares"},{"title":"Bank Leverage Risk","url":"/papers/ssrn/4956226/","summary":"Silicon Valley Bank, Signature Bank, and First Republic Bank experienced a loss of trust due to poor management of their liquidity, capital, and interest rate risk.","featured":"2024-09-18","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"Enterprise Risk Management and Management Earnings Forecasts","url":"/papers/ssrn/4959367/","summary":"The use of Enterprise Risk Management (ERM) enhances the likelihood and precision of management earnings forecasts by reducing fundamental volatility and improving managers' information assessment skills.","featured":"2024-09-18","label":"SSRN","topic":"Risk, Credit & Banking","cites":2,"score":2,"scale":"shares"},{"title":"XAI Framework for Risk Management","url":"/papers/repec/wsi-wschap-9781800615212-0004/","summary":"The article highlights the difficulties of using machine learning models in practical risk management in banking due to their opacity and lack of explainability, and introduces a framework for leading eXplainable AI methods.","featured":"2024-09-18","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":20,"scale":"shares"},{"title":"Satellite Data for Climate Finance","url":"/papers/ssrn/4948587/","summary":"Satellite data from Earth Observation systems could aid in creating green financial products by filling data gaps, as per a central banking viewpoint.","featured":"2024-09-10","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":3,"scale":"shares"},{"title":"Lapse-supported life insurance and adverse selection","url":"/papers/arxiv/2409.01843/","summary":"The article talks about how lapse-supported premiums can raise the costs of adverse selection in life insurance, especially when high-risk individuals keep their policies longer. It also proposes three ways to handle surplus from policy lapses.","featured":"2024-09-05","label":"arXiv","topic":"Risk, Credit & Banking","cites":1,"score":4,"scale":"shares"},{"title":"Unlocking The Potential: Enhancing Insurtech Innovation and Efficiency with a Data Analytics Approach","url":"/papers/ssrn/4938167/","summary":"The article highlights how data analytics and digitalization are fostering innovation in the insurance sector, based on a study involving 230 customers and various secondary data sources.","featured":"2024-08-28","label":"SSRN","topic":"Risk, Credit & Banking","cites":3,"score":2,"scale":"shares"},{"title":"AI Risk Management in Global Banking","url":"/papers/ssrn/4938239/","summary":"The paper discusses the use of AI in risk management in global banking, offering real-world examples and suggestions for financial institutions to utilize AI for better risk management.","featured":"2024-08-28","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"Banks' Funding in Coal Exit Era","url":"/papers/ssrn/4938516/","summary":"The paper shows that despite Germany's move away from coal power, global banks continue to fund coal companies, emphasizing the importance of bank funding decisions in achieving an emission-free economy.","featured":"2024-08-28","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"A novel k-generation propagation model for cyber risk and its application to cyber insurance","url":"/papers/arxiv/2408.14151/","summary":"The research proposes a new model for calculating aggregate losses in cyber insurance pricing, considering the origin contagion location and varying security levels in a network.","featured":"2024-08-28","label":"arXiv","topic":"Risk, Credit & Banking","cites":1,"score":2,"scale":"shares"},{"title":"Central Bank Policies","url":"/papers/ssrn/4927384/","summary":"The study examines the effects of central bank balance sheet policies on financial stability, concluding that while they help stabilize the economy during financial stress, they also prolong and increase the likelihood of such episodes.","featured":"2024-08-21","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":15,"scale":"shares"},{"title":"Economic Policy Uncertainty and Sovereign Credit Risk","url":"/papers/ssrn/4927956/","summary":"The research shows that domestic economic policy uncertainty greatly affects sovereign credit risk, but has a minor impact on sovereign bond yields and consumer confidence.","featured":"2024-08-21","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":4,"scale":"shares"},{"title":"Infinite-mean models in risk management: Discussions and recent advances","url":"/papers/arxiv/2408.08678/","summary":"The article explores the importance and challenges of using infinite-mean models in economics and finance, particularly when dealing with heavy-tailed datasets.","featured":"2024-08-21","label":"arXiv","topic":"Risk, Credit & Banking","cites":16,"score":3,"scale":"shares"},{"title":"Optimal insurance design with Lambda-Value-at-Risk","url":"/papers/arxiv/2408.09799/","summary":"The paper studies optimal insurance solutions using the Lambda-Value-at-Risk model, revealing that a truncated stop-loss indemnity is ideal under certain conditions and discusses the effect of model uncertainty.","featured":"2024-08-21","label":"arXiv","topic":"Risk, Credit & Banking","cites":7,"score":2,"scale":"shares"},{"title":"Capital Market Reforms for Economic Stability","url":"/papers/ssrn/4925670/","summary":"The article underscores the role of capital market reforms in fostering economic stability, enhancing investor confidence, and mitigating systemic risks.","featured":"2024-08-15","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":3,"scale":"shares"},{"title":"Bank Positions and Interest Parity","url":"/papers/ssrn/4920349/","summary":"Banks' positions regarding covered-interest parity deviations are affected by foreign safe asset scarcity, market power and segmentation, and demand concentration, as per a study using confidential supervisory data.","featured":"2024-08-15","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":3,"scale":"shares"},{"title":"Private Equity Life Insurance","url":"/papers/ssrn/4922345/","summary":"Private equity firms are increasingly buying life insurance companies and investing in riskier assets, sparking worries about potential failures akin to previous incidents.","featured":"2024-08-15","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"Central Bank Communications on Financial Stability","url":"/papers/ssrn/4924953/","summary":"The research investigates how central bank communications impact volatility in different markets, offering valuable information for investors and policy makers about the potential and limitations of monetary policy communications.","featured":"2024-08-15","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"Optimal Risk Mitigation by Deep Reinsurance","url":"/papers/arxiv/2408.06168/","summary":"An insurance company uses neural networks to find the best reinsurance strategy to manage its financial risk and control its terminal wealth and ruin probability.","featured":"2024-08-15","label":"arXiv","topic":"Risk, Credit & Banking","cites":0,"score":5,"scale":"shares"},{"title":"Adaptive Multilevel Stochastic Approximation of the Value-at-Risk","url":"/papers/arxiv/2408.06531/","summary":"The paper introduces a multilevel stochastic approximation algorithm that adaptively selects the number of inner samples to compute the value-at-risk of a financial loss, improving the previous scheme's complexity.","featured":"2024-08-15","label":"arXiv","topic":"Risk, Credit & Banking","cites":5,"score":3,"scale":"shares"},{"title":"Predicting US Bank Failures with ML","url":"/papers/repec/taf-apeclt-v-31-y-2024-i-15-p-1353-1359/","summary":"The research shows that simple machine learning methods like the KNN model, combined with PCA, can effectively predict bank failures.","featured":"2024-08-15","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":20,"scale":"shares"},{"title":"Uninsured Depositors and Banks Risk","url":"/papers/ssrn/4918096/","summary":"A study reveals that uninsured depositors react to changes in banks' economic value of equity and income-related interest rate risk, but not equity-related interest rate risk.","featured":"2024-08-07","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":3,"scale":"shares"},{"title":"Dutch Book Argument for Banks","url":"/papers/ssrn/4912406/","summary":"The paper outlines seven mathematical rules to prevent bank arbitrage, pointing out that existing models like Black-Scholes and the Heston model violate these rules.","featured":"2024-08-07","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"Risk sharing with lambda value-at-risk under heterogeneous beliefs","url":"/papers/arxiv/2408.03147/","summary":"The research investigates risk distribution among multiple parties using Lambda value at risk, offering formulas for optimal allocations under differing beliefs.","featured":"2024-08-07","label":"arXiv","topic":"Risk, Credit & Banking","cites":5,"score":5,"scale":"shares"},{"title":"Fintech Lending Impact on Small Business Credit","url":"/papers/repec/eee-finsta-v-73-y-2024-i-c-s1572308924000755/","summary":"Fintech lenders are using alternative data and complex models to provide loans to small businesses in high-risk areas, potentially filling the credit void left by traditional lenders.","featured":"2024-08-07","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":22,"scale":"shares"},{"title":"Machine Learning in Credit Scoring","url":"/papers/repec/eee-finsta-v-73-y-2024-i-c-s157230892400069x/","summary":"A study reveals that machine learning models using unconventional data are more efficient in predicting credit losses and defaults, particularly during economic crises.","featured":"2024-08-07","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":30,"scale":"shares"},{"title":"Global balance and systemic risk in financial correlation networks","url":"/papers/arxiv/2407.14272/","summary":"The study proves that the global balance index of financial correlation networks can effectively measure systemic risk, as confirmed by its application to real financial data.","featured":"2024-07-24","label":"arXiv","topic":"Risk, Credit & Banking","cites":10,"score":8,"scale":"shares"},{"title":"Novel Banking Loss Model","url":"/papers/repec/bgo-journl-v-8-y-2024-i-1-p-91-105/","summary":"The study uses a hybrid approach with historical financial ratios to predict US bank failures, showing better performance than existing methods with a low Mean Squared Error and high R-squared value.","featured":"2024-07-24","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":10,"scale":"shares"},{"title":"Credit Risk Management in Microfinance Institutions","url":"/papers/ssrn/4896689/","summary":"The article emphasizes the need for strategic goals and advanced decision-making tools in managing credit risk in microfinance institutions.","featured":"2024-07-17","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"Foreign Exchange Risk Management in U.S. & China","url":"/papers/ssrn/4893363/","summary":"The research shows that Chinese enterprises face more foreign exchange exposure than American companies due to different risk management practices.","featured":"2024-07-17","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"Insider Ownership in Japan","url":"/papers/ssrn/4892565/","summary":"A study reveals that insider ownership significantly increases default risk in Japanese firms, based on data from 2004-2019.","featured":"2024-07-17","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"Assesment of Degree of Monopolization of Insurance Sector in Serbia in the Period 2011-2022","url":"/papers/ssrn/4896834/","summary":"The insurance market in Central Serbia from 2011-2022 is highly concentrated, with a decreasing trend in market monopolization.","featured":"2024-07-17","label":"SSRN","topic":"Risk, Credit & Banking","cites":0,"score":2,"scale":"shares"},{"title":"Firm Default Risks and Exchange Rates","url":"/papers/ssrn/4886183/","summary":"The author integrates financial frictions from company default choices into an open-economy model to create realistic exchange rate patterns, solving the BackusSmith puzzle.","featured":"2024-07-10","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"CAESar: Conditional Autoregressive Expected Shortfall","url":"/papers/arxiv/2407.06619/","summary":"Conditional Autoregressive Expected Shortfall: The Conditional Autoregressive Expected Shortfall (CAESar) methodology is introduced for estimating Value at Risk (VaR) and Expected Shortfall (ES), providing a more comprehensive measure of tail risk and outperforming existing regression methods in forecasting performance.","featured":"2024-07-10","label":"arXiv","topic":"Risk, Credit & Banking","cites":1,"score":4,"scale":"shares"},{"title":"The Geographic Flow of Bank Funding and Access to Credit: Branch Networks, Local Synergies, and Competition","url":"/papers/arxiv/2407.03517/","summary":"The study examines the geographic imbalance of deposits and loans, proposing a method to evaluate the impact of branch networks, market power, and scope economies on this imbalance.","featured":"2024-07-10","label":"arXiv","topic":"Risk, Credit & Banking","cites":15,"score":6,"scale":"shares"},{"title":"The Not-so-Hidden Risks of ‘Hidden-to-Maturity’ Accounting: On Depositor Runs and Bank Resilience","url":"/papers/arxiv/2407.03285/","summary":"The article uses a balance sheet-based model to analyze run risk in banking systems, using the Silicon Valley Bank meltdown as a case study to show how changes in funding and asset composition can increase vulnerability.","featured":"2024-07-10","label":"arXiv","topic":"Risk, Credit & Banking","cites":2,"score":5,"scale":"shares"},{"title":"ML Due Diligence for NPLs Profit","url":"/papers/repec/spr-rvmgts-v-18-y-2024-i-7-d-10-1007-s11846-023-00635-y/","summary":"The paper introduces a machine learning approach to predict the recovery rate of non-performing loans, aiming to minimize the lemon discount by accurately pricing the risk component of information asymmetry between banks and investors.","featured":"2024-07-10","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":14,"scale":"shares"},{"title":"Financial Disinformation Detection","url":"/papers/repec/bla-popmgt-v-31-y-2022-i-8-p-3160-3179/","summary":"A machine learning system can identify financial misinformation on social media based on the truth-default theory, impacting both theory and practice.","featured":"2024-07-10","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":32,"scale":"shares"},{"title":"Esscher Algorithm for Default Probabilities","url":"/papers/ssrn/4880705/","summary":"The article presents a new Esscher-based algorithm for determining default probabilities in structural credit risk models, providing a more accurate tail behavior than the traditional Merton model.","featured":"2024-07-03","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"Upper Comonotonicity and Risk Aggregation Under Dependence Uncertainty","url":"/papers/arxiv/2406.19242/","summary":"The research investigates the concept of dependence uncertainty and its effect on tail risk measures in relation to credit risk, showing that even minor positive dependence between losses can lead to perfectly correlated tails beyond a certain point.","featured":"2024-07-03","label":"arXiv","topic":"Risk, Credit & Banking","cites":3,"score":6,"scale":"shares"},{"title":"Credit Ratings: Heterogeneous Effect on Capital Structure","url":"/papers/arxiv/2406.18936/","summary":"The research uses double machine learning to show that credit ratings significantly influence a company's leverage ratio, with the impact varying based on the rating, and the shift from no impact to a positive impact is gradual.","featured":"2024-07-03","label":"arXiv","topic":"Risk, Credit & Banking","cites":0,"score":8,"scale":"shares"},{"title":"The Merton's Default Risk Model for Public Company","url":"/papers/arxiv/2406.18121/","summary":"The paper expands Merton's structural model for public companies, assuming observed liabilities, and provides formulas for risk-neutral equity and liability values, default probabilities, and machine learning estimators of the model's parameters.","featured":"2024-07-03","label":"arXiv","topic":"Risk, Credit & Banking","cites":0,"score":5,"scale":"shares"},{"title":"The Effect of Personal Credit Card Limits on Card Use: Micro Data Evidence from Türkiye","url":"/papers/ssrn/4861586/","summary":"A Turkish study found that raising personal credit card limits significantly changes household spending, especially among those with already high limits.","featured":"2024-06-12","label":"SSRN","topic":"Risk, Credit & Banking","cites":0,"score":20,"scale":"shares"},{"title":"Privacy-Preserving Predictive Modelling in Insurance","url":"/papers/ssrn/4861490/","summary":"Google's Federated Learning method allows insurance companies to predict claim frequency without sharing sensitive data, maintaining privacy.","featured":"2024-06-12","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":4,"scale":"shares"},{"title":"CPS Engineering for ICT Supply Chain Risk","url":"/papers/ssrn/4862263/","summary":"The MagicGrid methodology has been introduced to build a cyber-physical system and use RAAML for reliable risk management in digital supply chain transformation.","featured":"2024-06-12","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"Machine Learning in Insurance","url":"/papers/ssrn/4861283/","summary":"The article explores the use of machine learning, particularly the Kmeans method, in the insurance industry.","featured":"2024-06-12","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":3,"scale":"shares"},{"title":"Professional Training and ERM in UAE Ministry of Interior","url":"/papers/ssrn/4855950/","summary":"The study shows that professional training boosts the positive effect of Enterprise Risk Management on employee performance in the UAE Ministry of Interior.","featured":"2024-06-12","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"Credit Risk Modelling in Euro Area during COVID-19","url":"/papers/ssrn/4859610/","summary":"The study creates a logistic regression model to evaluate the impact of the COVID-19 pandemic on nonfinancial firms' default probability, emphasizing the need for robust predictive models.","featured":"2024-06-12","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"Explainable AI for Credit Spread Changes Analysis","url":"/papers/repec/eee-finana-v-94-y-2024-i-c-s1057521924002473/","summary":"The research compares linear regression and machine learning for modeling credit spread changes, with machine learning showing superior performance due to its ability to handle complex non-linearities.","featured":"2024-06-12","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":19,"scale":"shares"},{"title":"Alternative Data for Credit Scoring","url":"/papers/ssrn/4852032/","summary":"The study shows that retail transaction data can be used to generate credit scores for unbanked individuals, leading to higher credit card approval rates.","featured":"2024-06-05","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":3,"scale":"shares"},{"title":"A Robust Record Linkage Approach for Anomaly Detection in Granular Insurance Asset Reporting","url":"/papers/ssrn/4849451/","summary":"The paper suggests a supervised classification method for detecting anomalies in insurance companies' asset data reporting, emphasizing the advantages of machine learning in data quality management.","featured":"2024-06-05","label":"SSRN","topic":"Risk, Credit & Banking","cites":0,"score":2,"scale":"shares"},{"title":"Insurers' Diversification","url":"/papers/ssrn/4850963/","summary":"A study reveals that smaller insurance firms heavily invest in finance bonds for diversification, but diversify into other sectors as they expand.","featured":"2024-06-05","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"Reporting and Derivation of Data on Financial Transactions Related to Banks’ Securities Holdings","url":"/papers/ssrn/4849359/","summary":"The article assesses European financial data compilation methods, finding the direct method, though more expensive, aligns better with statistical standards.","featured":"2024-06-05","label":"SSRN","topic":"Risk, Credit & Banking","cites":0,"score":2,"scale":"shares"},{"title":"Gross Bond Issuance by Italian Banks: Key Trends in Times of Crisis and Unconventional Monetary Policy","url":"/papers/ssrn/4848819/","summary":"The paper examines Italian banks' bond issuance post the 2007-08 financial crisis, highlighting a decrease in bond issuance and a greater dependence on alternative funding and monetary policy measures.","featured":"2024-06-05","label":"SSRN","topic":"Risk, Credit & Banking","cites":0,"score":2,"scale":"shares"},{"title":"Carbon Risk in European Equity","url":"/papers/repec/eme-sefpps-sef-05-2023-0245/","summary":"The research reveals that companies with diverse gender representation on their boards have lower expected risks, positively impacting risk management and financial performance.","featured":"2024-06-05","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":6,"scale":"shares"},{"title":"Machine Learning Bank Loan Risk","url":"/papers/ssrn/4837681/","summary":"The article discusses the use of machine-learning algorithms to forecast bank loan risk premium, with SVMs showing the highest accuracy.","featured":"2024-05-28","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":15,"scale":"shares"},{"title":"Building an integrated surveillance framework for highly leveraged NBFIs – lessons from the HKMA","url":"/papers/ssrn/4842826/","summary":"The paper proposes a new method to monitor systemic risks from nonbank financial institutions by integrating multiple data sources.","featured":"2024-05-28","label":"SSRN","topic":"Risk, Credit & Banking","cites":0,"score":2,"scale":"shares"},{"title":"Credit Risk Prediction for SMEs Using ML","url":"/papers/repec/wly-mgtdec-v-45-y-2024-i-4-p-2393-2414/","summary":"The FS-RS-ML framework, using machine learning to predict credit risk in supply chain finance for small and medium-sized enterprises, has proven superior in tests using Chinese data.","featured":"2024-05-28","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":25,"scale":"shares"},{"title":"Deep Learning for Commodity Risk Management","url":"/papers/repec/wly-jfutmk-v-44-y-2024-i-6-p-879-900/","summary":"A new deep learning strategy for financial hedging has been created, offering improved risk management and an average annual economic benefit of 1.21 million CNY for a typical Chinese aluminum firm.","featured":"2024-05-28","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":16,"scale":"shares"},{"title":"Operational Loss Recoveries in U.S. Banking","url":"/papers/ssrn/4836533/","summary":"A study indicates that operational loss recovery rates in large U.S. banks decrease during economic downturns, implying that economic shocks can affect banking losses.","featured":"2024-05-22","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":126,"scale":"shares"},{"title":"Economic Risk in Disability Income Insurance","url":"/papers/ssrn/4833986/","summary":"Research suggests an asset portfolio that matches unemployment levels can effectively manage disability income insurance portfolio liabilities, as demonstrated using UK data from 2004-2016.","featured":"2024-05-22","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"Credit Land Speculation and 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banks.","featured":"2024-05-22","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"Risk, utility and sensitivity to large losses","url":"/papers/arxiv/2405.12154/","summary":"Research identifies the conditions that make a risk or utility functional sensitive to large losses, demonstrating that Value at Risk and Expected Shortfall can become sensitive to large losses if properly adjusted.","featured":"2024-05-22","label":"arXiv","topic":"Risk, Credit & Banking","cites":4,"score":2,"scale":"shares"},{"title":"When fairness metrics fail: A utility-based perspective on $\\varepsilon$-fairness","url":"/papers/arxiv/2405.09360/","summary":"The article introduces a utility-based method to measure fairness in decisions, arguing that traditional probability-based evaluations may not accurately represent real-world fairness, using college admissions and credit risk assessment as examples.","featured":"2024-05-22","label":"arXiv","topic":"Risk, Credit & Banking","cites":0,"score":2,"scale":"shares"},{"title":"Will the Isolation of Divisions in Investment Banks Mitigate Conflict of Interest","url":"/papers/ssrn/4828209/","summary":"The article explores the expansion of modern banks into proprietary trading, private equity, and hedge fund services.","featured":"2024-05-15","label":"SSRN","topic":"Risk, Credit & Banking","cites":0,"score":2,"scale":"shares"},{"title":"On joint marginal expected shortfall and associated contribution risk measures","url":"/papers/arxiv/2405.07549/","summary":"The paper introduces a new systemic risk measure, the joint marginal expected shortfall (JMES), to assess the impact of one entity's risk on another or overall risk, and compares its effectiveness with other popular measures.","featured":"2024-05-15","label":"arXiv","topic":"Risk, Credit & Banking","cites":8,"score":2,"scale":"shares"},{"title":"Financial knowledge and borrower discouragement","url":"/papers/arxiv/2405.05891/","summary":"A survey of Italian micro-enterprises reveals that entrepreneurs with less financial knowledge are more likely to avoid applying for new financing due to high costs and fear of rejection, implying that financial knowledge can improve credit market conditions.","featured":"2024-05-15","label":"arXiv","topic":"Risk, Credit & Banking","cites":1,"score":2,"scale":"shares"},{"title":"Modeling Paid-Ups in Life Insurance","url":"/papers/repec/pal-risman-v-26-y-2024-i-3-d-10-1057-s41283-024-00146-4/","summary":"Predictive models are being used to forecast the future of premium payment policies in life insurance, identifying less likely payers and the effect of surrender fees.","featured":"2024-05-15","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":12,"scale":"shares"},{"title":"Quantitative Easing, Banks’ Funding Costs, and Credit Line Prices","url":"/papers/ssrn/4816357/","summary":"The research looks into how central banks' quantitative easing can reduce debt costs for banks' equity holders, especially during the COVID-19 crisis.","featured":"2024-05-08","label":"SSRN","topic":"Risk, Credit & Banking","cites":0,"score":2,"scale":"shares"},{"title":"A Study of Machine Learning Techniques for Predictive Analysis of Health Insurance","url":"/papers/ssrn/4817382/","summary":"The article discusses the use of machine learning in health insurance for anomaly detection and predictive modeling, emphasizing the effectiveness of decision tree regression and random forest regressor.","featured":"2024-05-08","label":"SSRN","topic":"Risk, Credit & Banking","cites":1,"score":2,"scale":"shares"},{"title":"Financial Institutions Risk Management","url":"/papers/ssrn/4817239/","summary":"The paper examines the risks in the banking industry and the different risk management strategies, based on data from secondary sources.","featured":"2024-05-08","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"Risk Management 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statistical properties, surpassing traditional estimators in various loss distributions.","featured":"2024-05-08","label":"arXiv","topic":"Risk, Credit & Banking","cites":1,"score":3,"scale":"shares"},{"title":"Knowledge Graph Credit Risk Assessment","url":"/papers/repec/taf-tprsxx-v-62-y-2024-i-12-p-4273-4289/","summary":"A machine learning-based credit risk assessment model for Micro Small and Medium-sized Enterprises (MSMEs) has been launched, classifying borrowers based on credit and transaction data, achieving a balanced accuracy of 92%.","featured":"2024-05-08","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":14,"scale":"shares"},{"title":"US Financial Uncertainty and International Credit","url":"/papers/ssrn/4808060/","summary":"The article investigates the impact of US financial uncertainty on global credit conditions and economic slowdown, influenced by market expectations.","featured":"2024-05-01","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"Climate Policy and Debt","url":"/papers/ssrn/4806153/","summary":"Research shows that climate and environmental policies significantly affect the relationship between a company's environmental impact and its credit risks and debt costs, with stricter policies increasing credit risk for polluting firms and reducing it for eco-friendly ones.","featured":"2024-05-01","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"Wealth Concentration Leads to Wealth Extraction","url":"/papers/ssrn/4806290/","summary":"The article stresses the need for fair wealth distribution for the effective operation of a free-market economy, arguing that extreme inequality and a flawed banking system obstruct entrepreneurship and innovation, worsening wealth concentration and inequality.","featured":"2024-05-01","label":"SSRN","topic":"Risk, Credit & Banking","cites":0,"score":3,"scale":"shares"},{"title":"Transforming Credit Guarantee Schemes with Distributed Ledger Technology","url":"/papers/arxiv/2404.19555/","summary":"The paper suggests using blockchain in Credit Guarantee Schemes to improve their performance and efficiency.","featured":"2024-05-01","label":"arXiv","topic":"Risk, Credit & Banking","cites":1,"score":5,"scale":"shares"},{"title":"Credit Card Fraud Detection","url":"/papers/ssrn/4801244/","summary":"A new study presents a tailored logistic regression model that can accurately detect credit card fraud, addressing issues of overfitting and underfitting.","featured":"2024-04-24","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"Systematic Credit Strategies: Factor Dynamics and Cross-Market Spillovers","url":"/papers/ssrn/4805159/","summary":"The research identifies 21 bond factors that generate significant positive alpha in bond and CDS markets, with similar factor 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learning study on Chinese data from 1993-2016 reveals credit is a better output predictor than money, but its effectiveness has lessened post-2007 due to financial development.","featured":"2024-04-17","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":28,"scale":"shares"},{"title":"Measuring Bank Complexity Using Xai","url":"/papers/ssrn/4785689/","summary":"A machine learning technique shows a link between the complexity and opacity of banks, with complex firms seeing decreased trading activity.","featured":"2024-04-10","label":"SSRN","topic":"Risk, Credit & Banking","cites":1,"score":13,"scale":"shares"},{"title":"Model Risk Management for AI","url":"/papers/ssrn/4787987/","summary":"An article suggests that model risk management can be used in national systemic and cyber risk projects like Project Maven, to transition from AI automation to AI augmentation.","featured":"2024-04-10","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"The Peal Method: A Mathematical Framework to Streamline Securitization Structuring","url":"/papers/arxiv/2404.05372/","summary":"The paper introduces the PEAL Method, a mathematical framework for structuring securitizations, aimed at improving market transparency, regulatory oversight, and risk management.","featured":"2024-04-10","label":"arXiv","topic":"Risk, Credit & Banking","cites":0,"score":3,"scale":"shares"},{"title":"Auto Insurance Risk Management: Value of Vehicles","url":"/papers/repec/bla-rmgtin-v-27-y-2024-i-1-p-115-120/","summary":"Value of Vehicles: The article criticizes traditional vehicle insurance pricing methods as outdated, proposing a shift towards flexible price-to-value methods that consider the actual features and values of vehicles.","featured":"2024-04-10","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":8,"scale":"shares"},{"title":"Predicting Systemic Financial 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migration model has been developed, incorporating economic state changes and utilizing Markov theory for various rating philosophies analysis.","featured":"2024-03-27","label":"arXiv","topic":"Risk, Credit & Banking","cites":3,"score":6,"scale":"shares"},{"title":"Global Credit Shocks Transmission","url":"/papers/ssrn/4756133/","summary":"Global credit supply shocks significantly impact country-level financial outcomes, emphasizing the need for sector-specific credit market monitoring.","featured":"2024-03-13","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"Properties of the entropic risk measure EVaR in relation to selected distributions","url":"/papers/arxiv/2403.01468/","summary":"The Lambert function has been used to successfully calculate the Entropic Value-at-Risk (EVaR) measure for various distributions like Poisson, Gamma, and Laplace.","featured":"2024-03-06","label":"arXiv","topic":"Risk, Credit & Banking","cites":5,"score":3,"scale":"shares"},{"title":"Banking Stability Prediction","url":"/papers/ssrn/4747568/","summary":"The research uses the CAMELS framework and machine learning to assess the performance of major banks in top GDP countries, with the aim of predicting future performance.","featured":"2024-03-06","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"Stackelberg Reinsurance and Premium Decisions with MV Criterion and Irreversibility","url":"/papers/arxiv/2402.11580/","summary":"A study on reinsurance Stackelberg game suggests a single, one-time reinsurance contract is more beneficial than continuous or multiple discrete-time contracts.","featured":"2024-02-21","label":"arXiv","topic":"Risk, Credit & Banking","cites":8,"score":3,"scale":"shares"},{"title":"Navigating Market Turbulence: Insights from Causal Network Contagion Value at Risk","url":"/papers/arxiv/2402.06032/","summary":"The paper presents the Causal-NECOVaR, a new method for financial risk analysis that provides reliable risk predictions regardless of market shocks and systemic changes.","featured":"2024-02-14","label":"arXiv","topic":"Risk, Credit & Banking","cites":2,"score":4,"scale":"shares"},{"title":"Decomposing Downside Investment Risk: Centred Expected Shortfall","url":"/papers/repec/taf-quantf-v-24-y-2023-i-1-p-83-104/","summary":"Centred Expected Shortfall: The article recommends using Centred Expected Shortfall as a risk measure in asset management for a more accurate portfolio risk breakdown.","featured":"2024-02-14","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":22,"scale":"shares"},{"title":"Attention-based Dynamic Multilayer Graph Neural Networks for Loan Default Prediction","url":"/papers/arxiv/2402.00299/","summary":"A dynamic multilayer network model has been created for improved credit risk assessment, considering borrower connections and their evolution over time.","featured":"2024-02-07","label":"arXiv","topic":"Risk, Credit & Banking","cites":49,"score":4,"scale":"shares"},{"title":"Explainable Automated Machine Learning for Credit Decisions: Enhancing Human Artificial Intelligence Collaboration in Financial Engineering","url":"/papers/arxiv/2402.03806/","summary":"The use of Explainable Automated Machine Learning (AutoML) in financial engineering can improve the development of machine learning models for credit scoring and increase transparency in AI financial decisions.","featured":"2024-02-07","label":"arXiv","topic":"Risk, Credit & Banking","cites":19,"score":4,"scale":"shares"},{"title":"Decision-making frameworks for network resilience: managing and mitigating systemic (cyber) risk","url":"/papers/arxiv/2312.13884/","summary":"A new type of risk measures has been developed to manage systemic risk in networks, focusing on the network's topological structure to reduce the spread risk of contagious threats.","featured":"2024-02-07","label":"arXiv","topic":"Risk, Credit & Banking","cites":1,"score":14,"scale":"shares"},{"title":"True Value Investing in Credits through Machine Learning","url":"/papers/ssrn/4718484/","summary":"The research introduces a new machine learning-based value factor for credit market investing, which performs better by capitalizing more on mispricings and less on risk.","featured":"2024-02-07","label":"SSRN","topic":"Risk, Credit & Banking","cites":0,"score":3,"scale":"shares"},{"title":"Interpretable ML for Creditor Recovery","url":"/papers/ssrn/4716003/","summary":"Interpretable machine learning methods excel over traditional models in finance, specifically in modeling corporate bond recovery rates.","featured":"2024-02-07","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"An Explicit Scheme for Pathwise XVA Computations","url":"/papers/arxiv/2401.13314/","summary":"A new simulation/regression scheme for a type of anticipated BSDEs is introduced, using neural network least-squares and quantile regressions, showing better results in high-dimensional and hybrid market/default risks XVA use-case.","featured":"2024-01-30","label":"arXiv","topic":"Risk, Credit & Banking","cites":2,"score":8,"scale":"shares"},{"title":"Moderating effects of gender and family responsibilities on the relations between work–family policies and job performance","url":"/papers/doi/10-1080-09585192-2018-1505762/","summary":"Research on the Spanish banking sector shows that work-family policies indirectly improve job performance through generated well-being, with no significant influence from gender or family responsibilities.","featured":"2024-01-30","label":"arXiv","topic":"Risk, Credit & Banking","cites":28,"score":12,"scale":"shares"},{"title":"Financial Stability vs. Politics in Third-Country Central Counterparties","url":"/papers/ssrn/4704566/","summary":"The article explores the legal regulations governing the access of central counterparties to EU financial markets, including the recognition process for CCPs from non-EU countries.","featured":"2024-01-30","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"Credit Factor Investing Challenges","url":"/papers/ssrn/4700056/","summary":"The article suggests that factor investing in corporate bonds can be successful despite challenges like nontradable assets and high transaction costs, with realistic expectations and avoidance of common mistakes.","featured":"2024-01-23","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":828,"scale":"shares"},{"title":"Spurious Default Probability Projections in Credit Risk Stress Testing Models","url":"/papers/arxiv/2401.08892/","summary":"The paper highlights the complexities of credit risk stress testing, warning of potential inaccuracies in projected default rates due to inconsistent model parameterization.","featured":"2024-01-23","label":"arXiv","topic":"Risk, Credit & Banking","cites":0,"score":4,"scale":"shares"},{"title":"Shapley values in credit scoring interpretability -> Shapley values in credit interpretability","url":"/papers/ssrn/4684103/","summary":"The paper assesses the use of the Shapley value in credit scoring to enhance transparency and comprehension of machine learning algorithm decisions.","featured":"2024-01-09","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"Global Factors in Non-core Bank Funding and Exchange Rate Flexibility","url":"/papers/arxiv/2310.11552/","summary":"The proportion of non-core to core funding in advanced economies' banking systems is influenced by global factors, with exchange rate flexibility providing some protection, except during significant global financial crises.","featured":"2024-01-09","label":"arXiv","topic":"Risk, Credit & Banking","cites":0,"score":20,"scale":"shares"},{"title":"Credit Growth, Yield Curve, and Crisis Prediction with Machine Learning","url":"/papers/repec/eee-inecon-v-145-y-2023-i-c-s0022199623000594/","summary":"The research uses machine learning to create early warning models for financial crises, with credit growth and yield curve slope being key predictors.","featured":"2024-01-09","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":25,"scale":"shares"},{"title":"Comparative Evaluation of Anomaly Detection Methods for Fraud Detection in Online Credit Card Payments","url":"/papers/arxiv/2312.13896/","summary":"A study found that LightGBM was the best for fraud detection when comparing anomaly detection and standard supervised learning methods, but it was more susceptible to distribution shifts, questioning the advantage of combining these two methods.","featured":"2024-01-03","label":"arXiv","topic":"Risk, Credit & Banking","cites":16,"score":2,"scale":"shares"},{"title":"Predicting Corporate Credit Ratings with ML","url":"/papers/repec/eee-finlet-v-58-y-2023-i-pd-s1544612323010206/","summary":"The research recommends restricted CART models for predicting corporate credit ratings using machine learning techniques, emphasizing the role of company size in credit rating prediction.","featured":"2023-12-20","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":20,"scale":"shares"},{"title":"Alternative Data and Trade Credit Financing","url":"/papers/repec/eee-finlet-v-58-y-2023-i-pb-s1544612323008413/","summary":"The research reveals that the use of alternative data, specifically online sales data, boosts trade credit financing for firms in China.","featured":"2023-12-20","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":18,"scale":"shares"},{"title":"Internal and External Capital Markets of Large Banks","url":"/papers/ssrn/4660712/","summary":"Internal and External: The research shows that large U.S. bank holding companies raise more capital internally than externally due to higher frictions in external capital, resulting in partial capital segmentation.","featured":"2023-12-13","label":"SSRN","topic":"Risk, Credit & Banking","cites":0,"score":5,"scale":"shares"},{"title":"Bayesian Data Imputation for Risk Management","url":"/papers/ssrn/4661384/","summary":"The article highlights the role of Bayesian data imputation techniques in risk management, as they provide a deeper understanding of risk factors and assist in decision-making.","featured":"2023-12-13","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"Fed Info & Equity Structure","url":"/papers/ssrn/4657704/","summary":"The study suggests that investors view central bank rate decisions as indicators of the economy's health, with short-term asset returns predicting macroeconomic growth.","featured":"2023-12-13","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":283,"scale":"shares"},{"title":"Defining and comparing SICR-events for classifying impaired loans under IFRS 9","url":"/papers/arxiv/2303.03080/","summary":"The paper presents a new framework for predicting credit deterioration using three parameters, validated using South African mortgage data.","featured":"2023-12-13","label":"arXiv","topic":"Risk, Credit & Banking","cites":5,"score":28,"scale":"shares"},{"title":"ML and IRB Capital Requirements: Advantages, Risks, and Recommendations","url":"/papers/ssrn/4654659/","summary":"Advantages, Risks, and Recommendations: The article explores the potential of machine learning in improving bank capital requirements and enhancing financial inclusion through better credit risk measurement.","featured":"2023-12-06","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"Shared Causal Manifolds for Risk Management","url":"/papers/ssrn/4637990/","summary":"A finance webinar presented a machine learning-based framework for optimizing portfolio sensitivities and predicting future positions.","featured":"2023-11-29","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"FX Risk Management by Managers","url":"/papers/ssrn/4629233/","summary":"The article shares a survey of 110 corporate risk managers on hedging foreign exchange rate risk, revealing that changes in forward and future FX rates greatly influence hedge ratios, and managers are most satisfied when FX risk doesn't affect cash flows.","featured":"2023-11-15","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"Chinese Capital Market Yearbook 2022","url":"/papers/ssrn/4630341/","summary":"The yearbook provides a comprehensive analysis of the return and risk characteristics of stocks, government bonds, and credit bonds in the Chinese capital market.","featured":"2023-11-15","label":"SSRN","topic":"Risk, Credit & Banking","cites":0,"score":3,"scale":"shares"},{"title":"Simulating Spread Dynamics for VaR & CVA","url":"/papers/ssrn/4628754/","summary":"A new model using a Gaussian one factor copula is suggested for simulating spread risk in banks' risk models, ensuring consistency between simulated and actual historical spreads.","featured":"2023-11-15","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"Machine Learning for Insolvency Prediction in Insurance","url":"/papers/ssrn/4626405/","summary":"A new machine learning algorithm, SANN, is used to predict insurance company insolvency, showing better accuracy than traditional models.","featured":"2023-11-08","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":3,"scale":"shares"},{"title":"Quanto Credit Default Swaps Theory, Pricing & Practice","url":"/papers/ssrn/4624435/","summary":"The paper examines Quanto Credit Default Swaps, a financial tool that transfers credit risk with foreign exchange exposure, focusing on its theory, pricing, and use in emerging markets like Brazil.","featured":"2023-11-08","label":"SSRN","topic":"Risk, Credit & Banking","cites":0,"score":75,"scale":"shares"},{"title":"Joint model for longitudinal and spatio-temporal survival data","url":"/papers/arxiv/2311.04008/","summary":"Longitudinal and Spatio-Temporal Survival Model: The Spatio-Temporal Joint Model (STJM) is a new method for credit risk analysis that uses spatial and temporal data to predict a borrower's risk, showing better results when spatial data is included.","featured":"2023-11-08","label":"arXiv","topic":"Risk, Credit & Banking","cites":4,"score":7,"scale":"shares"},{"title":"About Interest of Credits With Public Data and Regional Disparities","url":"/papers/ssrn/4618881/","summary":"The paper discusses the use of Google Trends for analyzing credit interest in Armenia, eliminating the need for traditional surveys by gathering online search data.","featured":"2023-11-02","label":"SSRN","topic":"Risk, Credit & Banking","cites":0,"score":2,"scale":"shares"},{"title":"Estimating Systemic Risk within Financial Networks: A Two-Step Nonparametric Method","url":"/papers/arxiv/2310.18658/","summary":"The article proposes a two-step nonparametric estimation method for measuring financial systemic risk, showing that only the second step's estimation error affects the results.","featured":"2023-11-02","label":"arXiv","topic":"Risk, Credit & Banking","cites":0,"score":4,"scale":"shares"},{"title":"Law-invariant return and star-shaped risk measures","url":"/papers/arxiv/2310.19552/","summary":"The paper introduces new characterizations for law-invariant star-shaped functionals, demonstrating their wide use in finance, insurance, and probability scenarios.","featured":"2023-11-02","label":"arXiv","topic":"Risk, Credit & Banking","cites":16,"score":2,"scale":"shares"},{"title":"Model Aggregation for Risk Evaluation and Robust Optimization","url":"/papers/arxiv/2201.06370/","summary":"The model aggregation (MA) approach is a new method for risk evaluation that provides a robust value and distributional model, refining Value-at-Risk and Expected Shortfall characterizations.","featured":"2023-11-02","label":"arXiv","topic":"Risk, Credit & Banking","cites":16,"score":33,"scale":"shares"},{"title":"Machine Learning in Insurance Claims Forecasting","url":"/papers/ssrn/4610457/","summary":"A novel approach to insurance claims forecasting is introduced, using weather conditions and car sales as variables and machine learning algorithms for prediction.","featured":"2023-10-25","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"Carbon Risk Management & Credit Default Swaps","url":"/papers/ssrn/4611661/","summary":"Firms with robust carbon risk management have lower credit default swap spreads, suggesting a positive impact on their credit risk evaluation.","featured":"2023-10-25","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"Bank Failures & Optimization Errors","url":"/papers/ssrn/4609719/","summary":"The paper attributes the three largest bank failures since 2008 to improper hedging for interest rate risk during Federal Reserve rate hikes from 2022 to 2023.","featured":"2023-10-25","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"Neural Networks for Insurance Pricing with Frequency and Severity Data: A Benchmark Study from Data Preprocessing to Technical Tariff","url":"/papers/arxiv/2310.12671/","summary":"The research evaluates different models for insurance claim frequency and severity data, presenting combined actuarial neural networks (CANNs) that merge baseline predictions with a neural network correction, and recommends using global surrogate models for practical deployment.","featured":"2023-10-25","label":"arXiv","topic":"Risk, Credit & Banking","cites":16,"score":4,"scale":"shares"},{"title":"Interest Rate Risk Management Measurement by Financial Institutions","url":"/papers/ssrn/4600139/","summary":"A new method measuring financial intermediaries' residual interest rate risk found that U.S. life insurers are more sensitive to changes in long-term interest rates than property and casualty insurers.","featured":"2023-10-18","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":9,"scale":"shares"},{"title":"Unveiling Early Warning Signals of Systemic Risks in Banks: A Recurrence Network-Based Approach","url":"/papers/arxiv/2310.10283/","summary":"The research introduces a method using high-frequency data to detect early signs of potential bank crises, proving that certain indicators can predict periods of high volatility in banking.","featured":"2023-10-18","label":"arXiv","topic":"Risk, Credit & Banking","cites":3,"score":3,"scale":"shares"},{"title":"Mean-Field Libor Market Model and Valuation of Long Term Guarantees","url":"/papers/arxiv/2310.09022/","summary":"The article introduces a numerical asset-liability management model based on the multi-dimensional mean-field Libor market model, which can calculate future discretionary benefits in line with Solvency II regulation, using public life insurance data.","featured":"2023-10-18","label":"arXiv","topic":"Risk, Credit & Banking","cites":1,"score":5,"scale":"shares"},{"title":"The Predictive Power of Central Bank Communication: Evidence from Mexico","url":"/papers/ssrn/4595144/","summary":"Predictive Power: The study reveals that Natural Language Processing can predict short-term interest rate decisions based on the communication strategy of Banco de México.","featured":"2023-10-12","label":"SSRN","topic":"Risk, Credit & Banking","cites":2,"score":3,"scale":"shares"},{"title":"ESG Factors and Credit Risk of Firms","url":"/papers/ssrn/4596796/","summary":"The study finds a correlation between credit risk and Environmental Social and Governance (ESG) factors using Supervised Machine Learning techniques.","featured":"2023-10-12","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"Differential quantile-based sensitivity in discontinuous models","url":"/papers/arxiv/2310.06151/","summary":"Discontinuous Model Sensitivity Analysis: The article discusses a framework for understanding complex computational models, focusing on discontinuities and discrete input variables, and applies it to risk analysis of compound risk models and reinsurance credit risk.","featured":"2023-10-12","label":"arXiv","topic":"Risk, Credit & Banking","cites":5,"score":10,"scale":"shares"},{"title":"ML for ReTakaful Contributions","url":"/papers/repec/idn-jimfjn-v-9-y-2023-i-3g-p-511-532/","summary":"The article employs machine learning to find the best ReTakaful contributions model for Morocco's Islamic insurance sector, showcasing the algorithms' potential in calculating appropriate contributions.","featured":"2023-10-12","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":18,"scale":"shares"},{"title":"Tightening Monetary Policy and Fragile U.S. Banks","url":"/papers/ssrn/4587122/","summary":"A study warns that increasing interest rates could cause significant losses for U.S. banks, particularly those with low capital and high uninsured leverage, potentially leading to bank runs.","featured":"2023-10-04","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":132106,"scale":"shares"},{"title":"Stressing Dynamic Loss Models","url":"/papers/arxiv/2211.03221/","summary":"A proposed reverse stress testing framework using a compound Poisson process allows for the examination of hypothetical scenarios and the comparison of stress effects on process dynamics.","featured":"2023-10-04","label":"arXiv","topic":"Risk, Credit & Banking","cites":8,"score":24,"scale":"shares"},{"title":"Finding the Blind Spots Before It's Too Late: A (Reverse) Stress Testing Approach for Asset Liability Management","url":"/papers/ssrn/4582564/","summary":"The article presents a new toolkit that uses AI and yield curve modelling to detect potential risks in bank balance sheets, illustrated with two hypothetical banks.","featured":"2023-09-28","label":"SSRN","topic":"Risk, Credit & Banking","cites":0,"score":15,"scale":"shares"},{"title":"The Undrawn Credit Line Premium","url":"/papers/ssrn/4583504/","summary":"According to the research, firms with more unused credit lines have higher returns due to greater liquidity needs, but are also more vulnerable to economic shocks.","featured":"2023-09-28","label":"SSRN","topic":"Risk, Credit & Banking","cites":0,"score":2,"scale":"shares"},{"title":"Life after Default: Dealer Intermediation and Recovery in Defaulted Corporate Bonds","url":"/papers/ssrn/4579966/","summary":"The research reveals that defaulted U.S. corporate bonds are traded to dealers with prior expertise in the bond, improving recovery rates and emphasizing the importance of dealer expertise.","featured":"2023-09-28","label":"SSRN","topic":"Risk, Credit & Banking","cites":0,"score":3,"scale":"shares"},{"title":"On Risk Management of Mortality and Longevity Capital Requirement: A Predictive Simulation Approach","url":"/papers/ssrn/4580817/","summary":"A paper suggests using a simulation approach with mortality-linked securities and stochastic mortality rates to manage capital risk in the insurance industry and meet regulatory capital requirements.","featured":"2023-09-28","label":"SSRN","topic":"Risk, Credit & Banking","cites":5,"score":2,"scale":"shares"},{"title":"The Effect of Assuring the Cloud User-Related Cybersecurity Risk Management Voluntary Disclosure on the Nonprofessional Investors’ Judgments and Decisions: The Mediating Role of Perceived Management Assertions Reliability-An Experimental Study in Egypt","url":"/papers/ssrn/4580292/","summary":"Egyptian investors' decisions are significantly influenced by the reliability of cybersecurity risk management, according to research.","featured":"2023-09-28","label":"SSRN","topic":"Risk, Credit & Banking","cites":2,"score":2,"scale":"shares"},{"title":"Data Breach Impact on Bank Operations","url":"/papers/ssrn/4584825/","summary":"Data breaches at banks lead to a loss of insured and brokered deposits and negatively impact stock returns, but do not affect long-term operations; banks often increase lending after a breach, likely due to CEO compensation incentives.","featured":"2023-09-28","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":74,"scale":"shares"},{"title":"Course 2023-2024 in Financial Risk Management","url":"/papers/ssrn/4574403/","summary":"The University of Paris-Saclay offers an advanced course in financial risk management, covering topics like market risk, credit risk, operational risk, liquidity risk, model risk, and stress testing.","featured":"2023-09-21","label":"SSRN","topic":"Risk, Credit & Banking","cites":0,"score":3,"scale":"shares"},{"title":"Ensemble distributional forecasting for insurance loss reserving","url":"/papers/arxiv/2206.08541/","summary":"The paper introduces a framework for combining multiple stochastic loss reserving models, which performs better than traditional strategies and equally weighted ensembles, taking into account the full distributional properties of the ensemble.","featured":"2023-09-21","label":"arXiv","topic":"Risk, Credit & Banking","cites":6,"score":33,"scale":"shares"},{"title":"Herding Behavior in Islamic Bank Market: Gulf Region Evidence","url":"/papers/repec/eme-rbfpps-rbf-02-2021-0018/","summary":"Gulf Region Evidence: The study investigates herding behavior in Islamic bank equity markets under different conditions, revealing that herding is common in all Gulf countries regardless of market conditions, but unaffected by oil price fluctuations.","featured":"2023-09-21","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":8,"scale":"shares"},{"title":"ESG Risk Management's Impact on Shareholder Value","url":"/papers/ssrn/4565374/","summary":"The study reveals that companies with fewer supply chain ESG incidents yield higher future stock returns and accounting performance, emphasizing the importance of ESG risk management.","featured":"2023-09-14","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"Bayesian Approach for Credit Risk Parameters","url":"/papers/ssrn/4544025/","summary":"The article introduces a Bayesian model to estimate default probabilities in low-default portfolios, using credit derivatives market data and observed default data for better risk differentiation.","featured":"2023-08-24","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":98,"scale":"shares"},{"title":"Credit Cycles & Returns","url":"/papers/repec/inm-ormnsc-v-68-y-2022-i-10-p-7350-7361/","summary":"Research indicates that high leverage credit booms often lead to lower returns on risky equities, while fixed income provides slightly higher returns as a safer option.","featured":"2023-08-24","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":17,"scale":"shares"},{"title":"Scaling SMEs Credit Scoring","url":"/papers/repec/hal-wpaper-hal-04159788/","summary":"A new method using Gradient Boosting Decision Trees and SHapley Additive exPlanation values aims to enhance credit scoring for Small and Medium Size Enterprises, providing high predictability and explainability.","featured":"2023-08-24","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":15,"scale":"shares"},{"title":"Insurance pricing on price comparison websites via reinforcement learning","url":"/papers/arxiv/2308.06935/","summary":"The paper presents a new reinforcement learning framework for insurers to develop better pricing strategies on price comparison websites, proving its effectiveness over existing methods in terms of sample efficiency and cumulative reward.","featured":"2023-08-17","label":"arXiv","topic":"Risk, Credit & Banking","cites":4,"score":3,"scale":"shares"},{"title":"Contagion Effects of the Silicon Valley Bank Run","url":"/papers/arxiv/2308.06642/","summary":"The study analyzes the impact of Silicon Valley Bank's failure on other banks, highlighting the role of uninsured deposits and bank size, with mid-sized banks being most affected.","featured":"2023-08-17","label":"arXiv","topic":"Risk, Credit & Banking","cites":19,"score":2,"scale":"shares"},{"title":"A Quantitative Approach to Historical Stress Tests","url":"/papers/ssrn/4531808/","summary":"The paper introduces a new method for defining historical stress tests in finance, classifying them into four types and using volatility as a key component in their definitions.","featured":"2023-08-09","label":"SSRN","topic":"Risk, Credit & Banking","cites":0,"score":2,"scale":"shares"},{"title":"DeRisk: An Effective Deep Learning Framework for Credit Risk Prediction over Real-World Financial Data","url":"/papers/arxiv/2308.03704/","summary":"Credit Risk Deep Learning Framework: DeRisk, a deep learning framework for predicting credit risk using real-world financial data, has been shown to outperform traditional statistical learning methods.","featured":"2023-08-09","label":"arXiv","topic":"Risk, Credit & Banking","cites":8,"score":3,"scale":"shares"},{"title":"Causal Inference for Banking Finance and Insurance A Survey","url":"/papers/arxiv/2307.16427/","summary":"The paper reviews 37 studies on the use of causal inference in banking, finance, and insurance from 1992 to 2023, categorizing them and discussing the statistical methods used, while highlighting that this application is still in its infancy.","featured":"2023-08-02","label":"arXiv","topic":"Risk, Credit & Banking","cites":8,"score":3,"scale":"shares"},{"title":"Computation of Systemic Risk Measures: A Mixed-Integer Programming Approach","url":"/papers/arxiv/1903.08367/","summary":"A Mixed-Integer Programming Approach: The research proposes a mixed-integer programming problem to compute systemic risk measures in systems with complex clearing mechanisms.","featured":"2023-08-02","label":"arXiv","topic":"Risk, Credit & Banking","cites":13,"score":13,"scale":"shares"},{"title":"Trade Credit Provision and Strategic Use of Captive Finance Subsidiaries","url":"/papers/ssrn/4517691/","summary":"The research shows that larger, more active captive finance subsidiaries positively impact the parent company's trade credit provision and lower default rates.","featured":"2023-07-26","label":"SSRN","topic":"Risk, Credit & Banking","cites":0,"score":5,"scale":"shares"},{"title":"Centred Expected Shortfall (CES): A Traditional Asset Manager’s View on Decomposing Downside Investment Risk","url":"/papers/ssrn/4519406/","summary":"CES: The paper suggests using Centred Expected Shortfall (CES) instead of Expected Shortfall (ES) for a more precise evaluation of portfolio risk.","featured":"2023-07-26","label":"SSRN","topic":"Risk, Credit & Banking","cites":0,"score":2,"scale":"shares"},{"title":"Multimodal Document Analytics for Banking Process Automation","url":"/papers/arxiv/2307.11845/","summary":"The research investigates the use of advanced document analytics, such as LayoutXLM, in banking to analyze diverse documents efficiently and accurately, enhancing operational efficiency.","featured":"2023-07-26","label":"arXiv","topic":"Risk, Credit & Banking","cites":12,"score":3,"scale":"shares"},{"title":"Double free boundary problem for defaultable corporate bond with credit rating migration risks and their asymptotic behaviors","url":"/papers/arxiv/2301.10898/","summary":"The paper presents a pricing model for a corporate bond with credit rating migration risk, proving the solution's existence, uniqueness, and regularity.","featured":"2023-07-26","label":"arXiv","topic":"Risk, Credit & Banking","cites":3,"score":13,"scale":"shares"},{"title":"Reverse Causality: Credit Markets & Macroeconomic Shocks","url":"/papers/ssrn/4511662/","summary":"Credit Markets & Macroeconomic Shocks: Corporate bond credit spreads significantly react to macroeconomic shocks, with credit risk premia and leverage playing crucial roles, enhancing our understanding of credit markets and the macroeconomy.","featured":"2023-07-19","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"Explainable ML Methods for Actuarial Problems","url":"/papers/repec/gam-jmathe-v-11-y-2023-i-14-p-3088-d-1193020/","summary":"The article examines different explainable AI methods for data-based insurance issues, highlighting the need for accurate and understandable machine-learning solutions.","featured":"2023-07-19","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":24,"scale":"shares"},{"title":"Credit Market Fragility: Evidence from Asset Demand System","url":"/papers/ssrn/4501772/","summary":"Evidence from Asset Demand System: A two-layer asset demand framework is created to study the fragility of the corporate bond market, using microdata to assess the impact of unconventional monetary and liquidity policies on asset prices and institutions.","featured":"2023-07-12","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":372,"scale":"shares"},{"title":"Machine Learning-Based Variable Selection for Clustered Credit Risk Modeling","url":"/papers/ssrn/4506537/","summary":"The piece proposes a machine learning-based method for selecting variables in clustered credit risk modeling, using the most influential risk drivers as clustering variables.","featured":"2023-07-12","label":"SSRN","topic":"Risk, Credit & Banking","cites":5,"score":3,"scale":"shares"},{"title":"Artificial Neural Networks Enhance Credit Risk Prediction","url":"/papers/repec/taf-oaefxx-v-11-y-2023-i-1-p-2210916/","summary":"The study reveals that machine learning is superior to logistic regression in predicting company bankruptcy, and its predictive accuracy increases when factors like changes in operating expenditure are included in the model.","featured":"2023-07-12","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":11,"scale":"shares"},{"title":"Mixed-frequency ML for weekly claims","url":"/papers/repec/eee-intfor-v-39-y-2023-i-3-p-1122-1144/","summary":"A new method combining mixed-data sampling and machine learning, using Google Trends data, enhances the accuracy of predicting weekly unemployment insurance claims, especially during the COVID-19 crisis.","featured":"2023-07-12","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":20,"scale":"shares"},{"title":"Convolutional Neural Network for Enterprise Default Risk Prediction","url":"/papers/repec/hin-complx-5139562/","summary":"The study proposes a comprehensive metric model to address imbalanced datasets and redundant features in machine learning models for default risk prediction.","featured":"2023-07-12","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":17,"scale":"shares"},{"title":"Predictive Performance in Credit Scoring","url":"/papers/ssrn/4492913/","summary":"XPER method breaks down machine learning model performance to identify impactful features.","featured":"2023-07-05","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":371,"scale":"shares"},{"title":"Calibrating Distribution Models from PELVE","url":"/papers/arxiv/2204.08882/","summary":"PELVE converts VaR to ES and provides insights on distribution models for insurance.","featured":"2023-07-05","label":"arXiv","topic":"Risk, Credit & Banking","cites":2,"score":25,"scale":"shares"},{"title":"Optimizing Credit Limit Adjustments Under Adversarial Goals Using Reinforcement Learning","url":"/papers/arxiv/2306.15585/","summary":"Reinforcement learning techniques automate optimal credit card limit adjustments, outperforming other strategies.","featured":"2023-06-28","label":"arXiv","topic":"Risk, Credit & Banking","cites":13,"score":4,"scale":"shares"},{"title":"Unveiling Credit Risk Models","url":"/papers/repec/bde-revist-y-2022-i-11-n-4/","summary":"Explainable AI helps understand credit risk in machine learning.","featured":"2023-06-28","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"Deep Factor Model for Crop Yield Forecasting and Insurance","url":"/papers/ssrn/4476951/","summary":"A new deep factor model for crop yield forecasting and crop insurance ratemaking has been proposed, which utilizes a deep autoencoder and deep learning model to enhance the modeling of the production index and the reconstruction of crop yields.","featured":"2023-06-14","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":2,"scale":"shares"},{"title":"Interbank Decisions and Margins of Stability: an Agent-Based Stock-Flow Consistent Approach","url":"/papers/arxiv/2306.05860/","summary":"Banks' refusal to roll over short-term interbank liabilities can compromise the efficiency of the interbank market and reduce the effectiveness of conventional monetary policies.","featured":"2023-06-14","label":"arXiv","topic":"Risk, Credit & Banking","cites":5,"score":2,"scale":"shares"},{"title":"Interpretable Learning in Credit Risk","url":"/papers/repec/eee-riibaf-v-65-y-2023-i-c-s0275531923000661/","summary":"Neural network with selective interpretability introduced for credit risk assessment, shallow model leads to better accuracy for specific data portions.","featured":"2023-06-14","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":19,"scale":"shares"},{"title":"Life after (soft) default","url":"/papers/arxiv/2306.00574/","summary":"Soft credit default has substantial and long-lasting negative effects on credit score, total credit limit, home-ownership status, and income, up to ten years after the event.","featured":"2023-06-07","label":"arXiv","topic":"Risk, Credit & Banking","cites":0,"score":2,"scale":"shares"},{"title":"Large Banks and Systemic Risk: Insights from a Mean-Field Game Model","url":"/papers/arxiv/2305.17830/","summary":"Insights from a Game Model: Study investigates impact of large banks on financial system stability.","featured":"2023-06-01","label":"arXiv","topic":"Risk, Credit & Banking","cites":8,"score":3,"scale":"shares"},{"title":"A default system with overspilling contagion","url":"/papers/arxiv/1709.09255/","summary":"Model captures contagious impact of default system on global economy.","featured":"2023-06-01","label":"arXiv","topic":"Risk, Credit & Banking","cites":2,"score":13,"scale":"shares"},{"title":"Asian Emerging Markets and Central Bank Transparency","url":"/papers/repec/cbk-journl-v-12-y-2023-i-2-p-133-163/","summary":"A new model and classification for accounting for a specific jump component of volatility and the impact of monetary policy announcements is proposed.","featured":"2023-06-01","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":14,"scale":"shares"},{"title":"Modelling Systemic Risk in Morocco's Banks","url":"/papers/repec/gam-jijfss-v-11-y-2023-i-2-p-70-d-1151988/","summary":"QRNN optimized by Adam algorithm shows increased systemic risk in Moroccan banking system during COVID-19 crisis.","featured":"2023-06-01","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":13,"scale":"shares"},{"title":"Study on Intelligent Forecasting of Credit Bond Default Risk","url":"/papers/arxiv/2305.12142/","summary":"Intelligent forecasting framework for default risk in China's bond market using ConvLSTM neural network.","featured":"2023-05-24","label":"arXiv","topic":"Risk, Credit & Banking","cites":1,"score":6,"scale":"shares"},{"title":"Weighing Anchor on Credit Card Debt","url":"/papers/arxiv/2305.11375/","summary":"Consumers tend to pay credit card minimums, but an intervention can increase payments.","featured":"2023-05-24","label":"arXiv","topic":"Risk, Credit & Banking","cites":8,"score":3,"scale":"shares"},{"title":"Unimodal Maps Perturbed by Heteroscedastic Noise: An Application to a Financial Systems","url":"/papers/arxiv/2305.13475/","summary":"Investigation of mathematical properties of perturbed unimodal smooth maps, with example linked to systemic risk.","featured":"2023-05-24","label":"arXiv","topic":"Risk, Credit & Banking","cites":2,"score":2,"scale":"shares"},{"title":"A Reverse ES (CVaR) Optimization Formula","url":"/papers/arxiv/2203.02599/","summary":"An optimization formula is established for Expected Shortfall and generalized to optimized certainty equivalents.","featured":"2023-05-24","label":"arXiv","topic":"Risk, Credit & Banking","cites":10,"score":21,"scale":"shares"},{"title":"Target Rate Factors","url":"/papers/ssrn/4445293/","summary":"Study on risk associated with uncertainties in central bank monetary policy targets using short interest rate models.","featured":"2023-05-24","label":"SSRN","topic":"Risk, Credit & Banking","cites":null,"score":8,"scale":"shares"},{"title":"NonNormal Risk Measures","url":"/papers/repec/gam-jjrfmx-v-14-y-2021-i-11-p-540-d-676017/","summary":"Paper examines statistical properties of risk measures in non-normal distribution for risk management.","featured":"2023-05-24","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":23,"scale":"shares"},{"title":"Modeling Recovery Rates of US Banks","url":"/papers/repec/gam-jmathe-v-9-y-2021-i-2-p-188-d-482845/","summary":"Unified recovery rate analysis can improve modeling for US banks.","featured":"2023-05-24","label":"RePEc","topic":"Risk, Credit & Banking","cites":null,"score":19,"scale":"shares"}],"per_quarter":{"2023 Q2":17,"2023 Q3":32,"2023 Q4":31,"2024 Q1":22,"2024 Q2":51,"2024 Q3":44,"2024 Q4":34,"2025 Q1":41,"2025 Q2":43,"2025 Q3":7,"2025 Q4":18,"2026 Q1":0,"2026 Q2":3,"2026 Q3":20}}