---
title: Bayesian Approach for Credit Risk Parameters
url: https://www.ml-quant.com/papers/ssrn/4544025/
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 4544025
source_url: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4544025
featured: 2023-08-24
citations: unknown
topic: Risk, Credit & Banking
---


# Bayesian Approach for Credit Risk Parameters

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.

- Source: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4544025
- Identifier: SSRN 4544025
- Released: 2023-04-19
- First featured: Quant Letter No. 13 (2023-08-24): https://www.ml-quant.com/issues/2023-08-24/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Risk, Credit & Banking

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