---
title: ESG Factors and Credit Risk of Firms
url: https://www.ml-quant.com/papers/ssrn/4596796/
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 4596796
source_url: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4596796
featured: 2023-10-12
citations: unknown
topic: Risk, Credit & Banking
---


# ESG Factors and Credit Risk of Firms

The study finds a correlation between credit risk and Environmental Social and Governance (ESG) factors using Supervised Machine Learning techniques.

- Source: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4596796
- Identifier: SSRN 4596796
- Released: 2022-12-19
- First featured: Quant Letter No. 20 (2023-10-12): https://www.ml-quant.com/issues/2023-10-12/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Risk, Credit & Banking

## Related

- [Carbon Risk Management & Credit Default Swaps](https://www.ml-quant.com/papers/ssrn/4611661/): Firms with robust carbon risk management have lower credit default swap spreads, suggesting a positive impact on their credit risk evaluation.
- [Joint Liability Model with Adaptation to Climate Change](https://www.ml-quant.com/papers/arxiv/2404.13818/): The study introduces the Environmental, Social, Economics (ESE) score, a comprehensive sustainable credit rating system for farmers, incorporating agricultural sustainability factors into personal credit assessments.
- [Climate Policy and Debt](https://www.ml-quant.com/papers/ssrn/4806153/): 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.
- [Climate Risks in Real Estate](https://www.ml-quant.com/papers/ssrn/5120353/): The study shows how physical climate risks, specifically river floodings, can affect the credit risk parameters and internal capital calibration of banks.
- [Differential quantile-based sensitivity in discontinuous models](https://www.ml-quant.com/papers/arxiv/2310.06151/): 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.
- [Joint model for longitudinal and spatio-temporal survival data](https://www.ml-quant.com/papers/arxiv/2311.04008/): 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.