Monotonic Optimal Binning in Consumer Credit Risk Scorecard Development

Credit scoring modeling toolbox based on R

This project commissions to examine the 100,000 credit card application data, detect abnormality and potential fraud in the dataset. All data manipulation and analysis are conducted in R. Featured analysis methods include Principal Component Analysis (PCA), Heuristic Algorithm and Autoencoder.

An R package for building state transition matrices

Credit risk analysis using the LASSO, Random Forests and the SMOTE technique for balancing

This is a course-work independent project I worked on in Fall 2021 MSc semester.

A hybrid classification and prediction model for credit risk analysis in R

Creating an India credit risk(default) Logistic Regression model

Comparison of Machine Learning Methods on a Sample of Bank Customers When Estimating Probability of Default Status

Accompanying code for the paper titled Anti Discrimination Laws AI and Gender Bias A Case Study in Nonmortgage Fintech Lending

Research Project in the area of ​​Deep Learning applied to credit risk. This model achieved better results compared to other published papers. This project is focused on the Fintech industry.

Credit risk analysis: based on the number of family dependents and the duration of the month's loan, classify the credit rating or risk rating using the decision tree method (C50 with R).

Developing a simple practical implementation of a credit risk model

The determinants of credit default - logistic regression.

Credit Loan Risk Analysis using GLM, LASSO Regression, and Chi-Square Tests.

This project is about credit risk measurement for a bank. The project entailed a comprehensive analysis of client default tendencies relative to their backgrounds using advanced classification models, providing actionable insights by model comparison and refinement.

Repository for the course 'Financial Risk' at Gothenburg University

Credit default risk data science competition.