The findings suggest that actual credit scores show marginally superior performance; however, estimated scores derived from restricted demographic variables can attain similar accuracy, serving as a viable substitute when conventional credit data is inaccessible.
The study validates the remarkable advantages of ensemble learning algorithms in enhancing default identification capabilities and improving the timeliness of risk control warnings, offering intelligent risk management support for financial institutions.
The findings indicate that interpretable machine learning can give lenders a defensible account of every credit decision — a capability that serves both regulatory oversight and the individuals whose applications are under review.
Kelvin Lin· Advances in Economics, Manag...· 0 citations
The credit risk model should choose between forecasting ability, interpretation requirements, misjudgment cost, and compliance conditions, and form a more stable application path through traditional model benchmarks, machine learning assistance, interpretation tools, and manual review.
Qi-Hang Yang· Advances in Economics, Manag...· 0 citations
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...
Bo-Lun Zhang, Jun Luo, Ruobing Wu et al.· Journal of Risk and Financia...· 1 citation
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...
The results show that introducing big data variables and adopting the XGBoost model can significantly improve the accuracy and AUC value of default prediction, effectively reducing the credit default risk of commercial banks.
Jia-Cheng Yan· Asia Pacific Economic and Ma...· 0 citations
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