{"title":"财务报表指标对银行信用评级的影响:来自机器学习和SHAP技术的见解","authors":"Min-Jae Lee, Sun-Yong Choi","doi":"10.1016/j.frl.2025.107758","DOIUrl":null,"url":null,"abstract":"This study investigates the influence of financial statement indicators on bank credit ratings. We construct a dataset encompassing 53 banks and 28 key financial indicators and employ two machine learning models, GBR and LightGBM, to predict credit ratings based on these indicators. To understand the contributions of the individual indicators, we apply SHapley Additive exPlanations (SHAP) to interpret the forecasting results. The analysis reveals that indicators pertaining to a bank’s revenue structure, particularly net interest income, have a significant impact on credit assessments. This finding underscores the critical role of a bank’s debt repayment capacity and income stream diversification.","PeriodicalId":12167,"journal":{"name":"Finance Research Letters","volume":"37 1","pages":""},"PeriodicalIF":7.4000,"publicationDate":"2025-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The impact of financial statement indicators on bank credit ratings: Insights from machine learning and SHAP techniques\",\"authors\":\"Min-Jae Lee, Sun-Yong Choi\",\"doi\":\"10.1016/j.frl.2025.107758\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study investigates the influence of financial statement indicators on bank credit ratings. We construct a dataset encompassing 53 banks and 28 key financial indicators and employ two machine learning models, GBR and LightGBM, to predict credit ratings based on these indicators. To understand the contributions of the individual indicators, we apply SHapley Additive exPlanations (SHAP) to interpret the forecasting results. The analysis reveals that indicators pertaining to a bank’s revenue structure, particularly net interest income, have a significant impact on credit assessments. This finding underscores the critical role of a bank’s debt repayment capacity and income stream diversification.\",\"PeriodicalId\":12167,\"journal\":{\"name\":\"Finance Research Letters\",\"volume\":\"37 1\",\"pages\":\"\"},\"PeriodicalIF\":7.4000,\"publicationDate\":\"2025-06-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Finance Research Letters\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://doi.org/10.1016/j.frl.2025.107758\",\"RegionNum\":2,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BUSINESS, FINANCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Finance Research Letters","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.1016/j.frl.2025.107758","RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
The impact of financial statement indicators on bank credit ratings: Insights from machine learning and SHAP techniques
This study investigates the influence of financial statement indicators on bank credit ratings. We construct a dataset encompassing 53 banks and 28 key financial indicators and employ two machine learning models, GBR and LightGBM, to predict credit ratings based on these indicators. To understand the contributions of the individual indicators, we apply SHapley Additive exPlanations (SHAP) to interpret the forecasting results. The analysis reveals that indicators pertaining to a bank’s revenue structure, particularly net interest income, have a significant impact on credit assessments. This finding underscores the critical role of a bank’s debt repayment capacity and income stream diversification.
期刊介绍:
Finance Research Letters welcomes submissions across all areas of finance, aiming for rapid publication of significant new findings. The journal particularly encourages papers that provide insight into the replicability of established results, examine the cross-national applicability of previous findings, challenge existing methodologies, or demonstrate methodological contingencies.
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