An Evidence of Link between Default and Loss of Bank Loans from the Modeling of Competing Risks

TL;DR

This paper introduces a competing risks model to analyze the relationship between default events and loss recovery in bank loans, demonstrating a significant link through real data application.

Contribution

It develops a novel competing risks modeling approach combining Poisson and Weibull distributions to analyze credit risk and loss recovery processes.

Findings

Significant relationship between default intensity and loss recovery.

Effective modeling of competing risks in credit portfolios.

Application to real personal loans data confirms model validity.

Abstract

In this paper, we propose a method that provides a useful technique to compare relationship between risks involved that takes customer become defaulter and debt collection process that might make this defaulter recovered. Through estimation of competitive risks that lead to realization of the event of interest, we showed that there is a significant relation between the intensity of default and losses from defaulted loans in collection processes. To reach this goal, we investigate a competing risks model applied to whole credit risk cycle into a bank loans portfolio. We estimated competing causes related to occurrence of default, thereafter, comparing it with estimated competing causes that lead loans to write-off condition. In context of modeling competing risks, we used a specification of Poisson distribution for numbers from competing causes and Weibull distribution for failures times. The likelihood maximum estimation is used to parameters estimation and the model is applied to a real data of personal loans