When uncertainty decouples expected and unexpected losses

BIS Working Papers  |  No 995  | 
26 January 2022

Summary

Focus

Credit losses evolve through distinct phases. After seemingly benign periods, they surge abruptly and stay elevated for some time before returning to a prolonged phase of low levels. The underlying mechanism for this has remained elusive, so creditors – notably, banks – have had to set their loss-absorbing resources under much uncertainty. The fallout from the Covid-19 pandemic has brought this uncertainty to the fore.

Contribution

We extend the model behind the Basel III requirements for credit risk in order to incorporate uncertainty about the credit loss phase. This lets us distinguish between two sources of potential shortfalls in loss-absorbing resources: ignoring uncertainty, and the uncertainty itself. We study how the shortfall associated with each source depends on the level of diversification in a credit portfolio. We also propose a method to rank the level of diversification across portfolios.

Findings

Accounting for a rise in uncertainty about the credit risk phase results in a decoupling between expected losses, which underpin provisions, and unexpected losses, which drive capital. This is consistent with empirical forecasts of credit loss distributions from the standpoint of the first quarter in 2021.

We show that ignoring phase uncertainty or operating under greater such uncertainty leads to larger shortfalls of loss-absorbing resources – and hence a higher likelihood of bank failure – when the credit portfolio is more diversified. In such a portfolio, a common risk factor within a phase has a smaller scope to compensate for errors related to uncertainty about the phase.

Using data on US bank loans from 1985 to 2021, we find that in a credit loss phase a prototypical business loan portfolio is more diversified than a real estate portfolio.


Abstract

A parsimonious extension of a well-known portfolio credit-risk model allows us to study a salient stylized fact – abrupt switches between high- and low-loss phases – from a risk-management perspective. As uncertainty about phase switches increases, expected losses decouple from unexpected losses, which reflect a high percentile of the loss distribution. Banks that ignore this decoupling have shortfalls of loss-absorbing resources, which is more detrimental if the portfolio is more diversified within a phase. Likewise, the risk-management benefits of improving phase-switch forecasts increase with diversification. The analysis of these findings leads us to an empirical method for comparing the degree of within-phase default clustering across portfolios.

JEL classification: G21, G28, G32.

Keywords: expected loss provisioning, bank capital, unexpected losses, credit cycles, portfolio credit risk.