Introduction

A hypothetical exercise conducted by the Basel Committee on Banking Supervision (BCBS) for several banks, after the 2008-09 Global Financial Crisis, highlighted inconsistencies in estimates of risk-weighted assets (RWAs). The variability of RWAs under this exercise ranged from 300% for exposure to banks to over 600% for exposure to corporates.

In 2017, Basel III was updated (2017 Reforms) to reduce RWA variability and included guidelines to level the field for banks using two different approaches – standardised and internal model. The BCBS enhanced the robustness and risk sensitivity of the standardised approach, while setting an output floor with a limit on capital benefit a bank can obtain by using the internal model. This helped banks build significant resilience to financial shocks.

However, the Covid-19 pandemic has dealt a fresh blow to the financial systems across the globe. Unarguably, banks can now expect an increase in the severity of regulatory stress tests in the upcoming guidelines.

This paper intends to assist banks prepare for the impending additions in regulations and presents a streamlined process to calculate RWA under the stressful impact of the pandemic.

Increase in RWAs under stress scenarios can be used internally to analyse capital calculation and prepare for upcoming regulatory stress tests.

RWAs for wholesale and securities financing transaction portfolios

The scope for RWA estimation covers the standardised approach for wholesale (on and off balance sheet items) and counterparty credit risk (derivatives and securities financing transaction or SFT) portfolios. The methodology to generate a stress scenario for the pandemic entails a notch-down approach of obligors’ ratings, i.e. decreasing the ratings of obligors as deemed appropriate. Using a series of calculations and mapping tables across asset classes, ratings, credit quality steps and risk weights, the notch-down would increase the net exposure value and RWA amount.

The required data fields are: original gross exposure of each obligor, collateral posted by obligors, provisions calculated for each obligor, ratings (external/ internal) of each transaction, staging of each transaction, credit conversion factor as per counterparty credit risk (CRR) guidelines, exposure type (off/ on balance sheet item, derivative and SFT), country of risk/domicile, asset class and risk weights.