A procedure for loss-optimising default definitions across simulated credit risk scenarios

TL;DR

This paper introduces an optimization procedure for defining default thresholds in credit risk, aiming to minimize financial losses and challenge traditional default definitions like '90 days past due' through simulation analysis.

Contribution

It presents a novel objective method for evaluating and optimizing default definitions across various credit risk scenarios, incorporating alternative delinquency measures.

Findings

Loss minima exist for specific credit risk profiles.

Default threshold optimization can improve loss outcomes.

Traditional default definitions lack objective validation.

Abstract

A new procedure is presented for the objective comparison and evaluation of default definitions. This allows the lender to find a default threshold at which the financial loss of a loan portfolio is minimised, in accordance with Basel II. Alternative delinquency measures, other than simply measuring payments in arrears, can also be evaluated using this optimisation procedure. Furthermore, a simulation study is performed in testing the procedure from `first principles' across a wide range of credit risk scenarios. Specifically, three probabilistic techniques are used to generate cash flows, while the parameters of each are varied, as part of the simulation study. The results show that loss minima can exist for a select range of credit risk profiles, which suggests that the loss optimisation of default thresholds can become a viable practice. The default decision is therefore framed anew as an optimisation problem in choosing a default threshold that is neither too early nor too late in loan life. These results also challenges current practices wherein default is pragmatically defined as `90 days past due', with little objective evidence for its overall suitability or financial impact, at least beyond flawed roll rate analyses or a regulator's decree.