Two years ago we noticed a resurgence in portfolio risk modelling and some new trends in the modelling practices being implemented, with an emphasis on supporting business decision-making by reducing complexity and fully linking to business intuition. Two years and one COVID-19 crisis later, there is still steam in the sails. The principle of "as-simple-as-possible" continues to create value by complying with regulation while allowing risk departments to support the business in optimising for long-term, sustainably higher ROE. Read on below for more insights on how to use Portfolio Credit Risk Models to "make friends and influence people".
How to make friends and influence people
As the industry continues to tussle with the fallout from COVID-19, credit portfolio managers have some tricky decisions to make. With spikes in default rates expected following the end of the furlough schemes and COVID-related-forbearance, and the still uncertain impact of Brexit, it can be hard to make informed decisions such as which of your large corporate exposures to reduce first, or which sectors, products or regions should be targeted to maximise risk-adjusted returns. Firms are looking to their Portfolio Credit Risk (PCR) quantification frameworks to help them make these decisions. Those with effective tools are well positioned to take measured steps to rebalance their portfolios for the new environment and thus maximise long-run ROE.
By ‘effective’ we mean a model that captures four key portfolio risks:
- How much did you lend? (Exposure-at-Default or EAD);
- Who did you lend it to? (Probability-of-Default or PD);
- How much do you think you can recover if they default? (Loss-given-Default or LGD);
- How likely is their default to happen at the same time as other defaults? (Correlation or R).
If your PCR model combines all four to produce consistent estimates of Unexpected Loss (UL), then your approach is probably similar to the one we’re advocating here. If your model can’t yet do that, we would highly recommend an upgrade for the reasons outlined below.
When based on tried and tested methodologies, a robust PCR model helps ‘make friends’ by meeting regulatory expectations that you can accurately measure the unique risks facing your firm’s credit portfolio. It can also ‘influence people’ because its outputs are credible and help your colleagues make better risk decisions. From a regulatory perspective, models like this have been in use for many years now. As we continue to track the evolving regulatory environment (including the recent consultation paper on the UK’s approach to transition to CRRII/CRDV and the FCA’s discussion paper 20/2 on IFD/IFR for investment firms), we expect that for many years to come they will remain a principle method for internal Pillar 2 capital quantification.
We get it, you’re really busy
It takes time to build a model able to robustly estimate your credit risk and credit concentration risk capital in ways that are sensible (they pass the ‘use’ test) and defensible (in the eyes of your model validation team and to your board and the PRA). Some firms spend over a year from start to finish – and still don’t end up with something workable.
We think there are many better things your credit risk team could be doing: running COVID-19 second-wave scenarios; updating IRB and IFRS9 models; and reporting to the board on developments in the firm’s credit risk profile.
By adopting the Vasicek/Merton credit risk and VAR-CoVAR sector-region concentration risk approach (as Deloitte has long advocated across the financial services industry), firms can shave ten of the 12 months from their initial development schedule. Why? Because the methodology is established and ready to go, particularly if implemented through a vendor hosted-web-service (e.g. Capital Clarity). This frees up your Credit Risk SMEs to focus on building better assessments of the underlying risk parameters – which in any case should be their skills sweet-spot – thereby avoiding the ‘GIGO’ problem of ‘garbage in, garbage out’.
You may be missing a trick
The approach to PCR modelling that we’re recommending here doesn’t merely meet your obligations. It’s also genuinely insightful. By harnessing your firm’s best insights and channelling them through a model that has passed regulatory scrutiny dozens of times, the results are capital allocations that are easy to understand and share around the business. Better first-line and second-line buy-in means the model can pass the ‘use test’ and become the basis of business decisions.
Some firms in the UK choose to make use of the PRA’s Herfindahl Hirschman Index (HHI) approach and credit risk benchmarks to inform their Pillar 2A capital requirements. Using HHI certainly makes calculating Pillar 2A capital add-ons easier (it uses the RWA concentrations of a firm in different top counterparty, sector and region buckets to assess simplistic capital add-ons). However, it has two major weaknesses:
- The approach is intended to be right “on average” (within the UK) and is unlikely to be sufficiently accurate for any particular firm to use in its credit portfolio management.
- If the best a firm can do is fall back on the PRA’s methodology (ignoring the readily-available, industry-standard, superior alternatives) it might suggest a lack of ambition or modelling skill.
Some firms outside of the UK jurisdictions have also adopted the UK PRA’s HHI approach, though this can sometimes get them into particularly sticky waters with their regulators who want to know what their justification is for using a solution not even calibrated to their country.
All of the actions we recommended two years ago (here) remain relevant. Two years has seen some further convergence in modelling approaches as firms align on the "as-simple-as-possible" approach that provides maximum business insight for its complexity, and thus lends itself best to helping the business maximise long-run ROE. On this basis we've become somewhat more prescriptive on methodology in this article (as a reminder, it’s the “Vasicek/Merton credit risk approach for single-name and systematic credit risk and VAR-CoVAR approach to sector-region concentrations”). To demonstrate that we put our money where our mouth is, we've also built this methodology into a hosted-web-service Capital Clarity aimed at making it easier still. If you don't already use Portfolio Capital Models to make business decisions, you may be running out of excuses.
For more information on any of the contents of this article or to join our Pillar 2A/R community including webinars, insights updates and more, email firstname.lastname@example.org or visit our Capital Clarity webpage.