Loan Default Prediction Based on Machine Learning Methods

Yuran Zhou

11 citations0/0 files storedInternational Conference on Big Data Economy and Information Management (BDEIM)

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Financial Distress and Bankruptcy Prediction Microfinance and Financial Inclusion Customer churn and segmentation

Abstract

Loan default prediction helps institutions predict whether a borrower will default on a loan and decide whether to lend, thereby reducing losses. We investigate the performance of different machine learning models in predicting customers' loan defaults. Four machine learning models: Logistic Regress

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1997Credit risk measurement: Developments over the last 20 years 2020Machine learning techniques for credit risk evaluation: a systematic literature review 2014Corporate governance characteristics and default prediction modeling for small enterprises. An empirical analysis of Italian firms 2019A study on predicting loan default based on the random forest algorithm 2020Corporate default forecasting with machine learning 2020An Approach for Prediction of Loan Approval using Machine Learning Algorithm 2006Artificial neural network vs linear discriminant analysis in credit ratings forecast 2020A Comparative Assessment of Credit Risk Model Based on Machine Learning ——a case study of bank loan data

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