In commercial lending, banks rely on long-standing risk models to help inform their decisions. These models have been built up internally over decades of lending, but the events of the last year have exacerbated a number of limitations with them and are changing banks’ and regulators’ expectations with regards to effective commercial credit risk management. These enduring morels are based on historic data and given the dynamics of the pandemic and the unprecedented steps taken by governments to counter its economic impact, these historical correlations don’t hold.

Let’s take an example of a paper and board packaging business – it’s likely that it will have seen revenue from paper sales reduce significantly in the last 12 months as businesses moved to remote working and digital contracts. However, on its balance sheet, year-on-year sales for the entire business in 2020 may not look very different to 2019. This is because the decrease in demand for paper has been offset by an increase in demand for cardboard as people who are under lockdown shop online and order items to their home. While the move towards paperless working is likely a permanent change from the pandemic, the increase in online shopping is unlikely to stay at peak pandemic levels once people are able to shop in person as before. Therefore, if the business fast forwards 6-12 months, it could see a decrease in revenue that it hadn’t been expecting and therefore, hadn’t planned for.

In the context of commercial lending, forward-looking data, such as projections of revenues as per the example above, provide an additional means of understanding future risks. As these offer a glimpse of a possible outcome under certain assumptions, they can never be as accurate as historical numbers, but they do give banks and borrowers the opportunity to act with foresight. In this example, the bank, armed with this data, could take a more consultative role and if needed, advise the business to take out a loan to support working capital while it explores new revenue streams. Equally, the business’ management team can now be better prepared for changes further down the line. In a fast-changing world, a timely change of course informed by insight and foresight is much preferred to 20/20 hindsight when it’s too late to avoid a problem.

Regulators hate uncertainty and not having the ability to control an outcome. So, it’s important for banks to also consider what they can be doing to mitigate commercial risk in order to make regulators feel more comfortable. The challenge however, is that most banks’ risk models tend to lump all businesses into one of a dozen or so categories – for example, all restaurants, bars and hotels are classified as “Hospitality” – which disregards fundamental differences in how these businesses operate and makes it harder for banks to identify the most vulnerable businesses in their portfolio. The experience of a pizza delivery business throughout this pandemic will have been very different to a Michelin-star fine dining restaurant for example. Equally, the experience of an all-inclusive destination resort is likely to have been starkly different to an airport hotel or a business conferment hotel. The only way banks can effectively assess credit risk is by taking a granular, loan-by-loan approach. Banks not only need to be able to demonstrate to regulators that their data is organized, but that they’ve also got a very granular understanding of that data, and can quickly retrieve it if needed. While annual stress testing is important, regulators increasingly want the “now” view that can be dynamically managed as the subtleties of a crisis change, not just the big picture.

In the intervening years since the ‘08 recession, regulators have sought to understand how banks’ thought processes and risk management capabilities have evolved, particularly when it comes to stress-testing. The challenge however, is that traditional risk models don’t take into account how quickly the situation changes day to day during a pandemic. The steps taken by the Trump administration to manage the pandemic in the US last year were completely different to the steps being taken by the Biden administration today. Banks therefore need the ability to re-run analysis and stress test on an ongoing basis in order to determine how governmental or socio-economic changes are impacting their loan book.

The industry, regulators and businesses never stand still which is why at OakNorth, we will continue to listen, research and evolve our software, the ON Credit Intelligence Suite.