Evaluating the effectiveness of bank credit risk assessment models.

Thesis Abstract

This research aims to evaluate the effectiveness of bank credit risk assessment models in predicting loan default and managing credit risk. Accurate credit risk assessment is crucial for banks to make informed lending decisions, maintain a healthy loan portfolio, and ensure financial stability. The study will assess the performance of different credit risk assessment models, such as the probability of default (PD), loss given default (LGD), and exposure at default (EAD) models. Additionally, the research will analyze the impact of model inputs, model validation techniques, and macroeconomic factors on the effectiveness of these models. The findings of this study will provide insights for banks in improving their credit risk assessment practices and enhancing loan portfolio management.