---
title: AI in Financial Risk Management
url: https://www.ml-quant.com/papers/ssrn/5243241/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-09-26
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: SSRN 5243241
source_url: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5243241
featured: 2025-05-07
citations: unknown
topic: Risk, Credit & Banking
---


# AI in Financial Risk Management

The paper explores the use of artificial intelligence in improving financial risk management in financial institutions, focusing on its application in various risk types.

- Source: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5243241
- Identifier: SSRN 5243241
- Released: 2025-05-06
- First featured: Quant Letter No. 96 (2025-05-07): https://www.ml-quant.com/issues/2025-05-07/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Risk, Credit & Banking

## Related

- [A stochastic Gordon–Loeb model for optimal cybersecurity investment under clustered attacks](https://www.ml-quant.com/papers/arxiv/2505.01221/): A model is developed for optimal cybersecurity investment, showing that considering attack clustering improves investment policies and risk management.
- [Systemic Risk in the European Insurance Sector](https://www.ml-quant.com/papers/arxiv/2505.02635/): 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.
- [Systemic risk mitigation in supply chains through network rewiring](https://www.ml-quant.com/papers/arxiv/2504.12955/): Research shows that strategically rearranging supplier-customer connections can significantly lower supply chain risk by 16-50% without affecting production.
- [Structural robustness of the international food supply network under external shocks and its determinants](https://www.ml-quant.com/papers/arxiv/2504.08857/): 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.
- [The Bank of Italy’s Statistical Model for the Credit Assessment of Non-Financial Firms](https://www.ml-quant.com/papers/ssrn/5270521/): 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.
- [How important are ESG factors for banks' cost of debt? An empirical investigation](https://www.ml-quant.com/papers/ssrn/5270535/): 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.