Multi‑Source Data Fusion for Credit Risk and Financial Product Purchase Prediction: A Comparative Machine Learning Study in R

Machine Learning‑Based Discriminant Analysis of Corporate Credit Default

Explainable Machine Learning for Home Equity Line of Credit Risk Assessment: A Multi-Model Comparison with SHAP Interpretability

Accurate default risk prediction is essential for commercial banks' retail credit loan decisions and supervision. Traditional credit scoring models fail to provide clear decision schemes under strict regulation, while high-performance machine learning models face the black-box dilemma, making it difficult to meet finan...

Credit Risk Assessment and Explainability of Machine Learning

With the increase in online development of credit business, the customer information that financial institutions can use is also increasing, and the traditional credit scoring model has limitations in fitting high-dimensional characteristics, non-linear correlation, and multi-source heterogeneous data. This paper focus...

Machine Learning for Individual Credit Risk Assessment: A Systematic Literature Review of State-of-the-Art Methods, Challenges and Perspectives

A systematic literature review of ML applications in credit risk assessment (CRA), covering publications from January 2016 to May 2026, synthesise prevailing methodologies into a unified end-to-end credit risk modelling framework spanning data preprocessing, feature engineering, model training, evaluation, and operatio...

Construction of SME Loan Default Risk Prediction System for Commercial Banks Using XGBoost Model

Small and medium-sized enterprises play an important role in promoting employment and innovation, but their small scale, opaque financial information, and unstable operating conditions increase credit risk for commercial banks. Accurate prediction of SME loan default risk can reduce credit losses, optimize credit-resou...

Research on the Application of Big Data Technology in Bank Credit Risk Assessment

With the rapid development of FinTech, commercial banks are facing an increasingly complex credit environment. Traditional credit risk assessment models struggle to meet the processing demands of massive and multi-dimensional data. Big data technology provides new perspectives and tools for bank risk control. Based on...