Application of the Bayesian approach to modeling credit risks
A computer model for analyzing, evaluating, and forecasting bank credit risks has been developed. Utilizing a Bayesian network (BN) and established parameter estimation methods, this model was implemented in the Python programming language. It predicts the probability that a borrower may fail to meet financial obligations, such as repaying a loan.