Credit Approval and Predicting Default

Student: Cheremina Daria

Supervisor: Maria Veretennikova

Educational Programme: Economics and Statistics (Bachelor)

Year of Graduation: 2018

With the development of Basel requirements, credit scoring models became crucial for financial institutions. Credit scoring is widely used as a tool to determine the risk of the assets and, consequently, capital requirements. In this study discussed basic models for predicting default as well as more advanced as SVM and KNN. Furthermore, different approaches to credit score-modeling are studied and implemented. In this bachelor thesis the underlying approaches are implemented and the best credit scoring model for a particular dataset is determined.

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