---
title: Re-examining Standard Changes in U.S. Corporate Credit Rating via Machine Learning
url: https://www.ml-quant.com/papers/ssrn/4771505/
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 4771505
source_url: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4771505
featured: 2024-03-27
citations: 0
topic: Risk, Credit & Banking
---


# Re-examining Standard Changes in U.S. Corporate Credit Rating via Machine Learning

Machine learning reveals an N-shaped pattern in corporate credit rating standards from 1986 to 2016, with the Gradient Boosting Machine model predicting actual credit ratings better than traditional regression models.

- Source: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4771505
- Identifier: SSRN 4771505
- Released: 2024-03-25
- First featured: Quant Letter No. 42 (2024-03-27): https://www.ml-quant.com/issues/2024-03-27/
- Citations (Semantic Scholar): 0
- Published in: not yet
- Topic: Risk, Credit & Banking

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