An Integrated Decision Analysis Approach to Credit Extension and Risk Management

Wei Hailin

Abstract

This research examines credit risk management for creditors with focus on credit extension decisions using the decision analysis tool. Creditors should be able to maintain their credit exposure and ensure that they hold enough economic capital against the risk of extending credit to an array of debtors with different credit worthiness. The recent credit crunch that saw financial markets taking a giant dip and the world's economy on the brink of recession has given rise to an increasing need for effective credit risk management.

Existing literature have approached credit risk management in several ways from using statistical tools like linear credit discriminant analysis and theoretical analysis for portfolio management using the acclaimed mean-variance approach. This thesis will, in a novel attempt, integrate these theories using a decision analysis approach and on top of that, deliver more than just a combination, but an improved generic decision analysis model that can better represent risk aversion behaviours of creditors.

Three models are developed in this thesis and the results are being obtained and analyzed using commercial software DPL. The final proposed model is able to deliver the above discussed; utility functions can be changed easily to accommodate different risk aversion behaviours and an economic capital constraint based which was not discussed in this thesis.