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.

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