Risk analysis in retail financial services

News of the drastic increase in the proportion of residential mortgages granted for a term of over 35 years will come as no surprise to anyone with a passing familiarity with the UK property market. But with some commentators drawing attention to the connections between global financial turbulence and the UK residential property market, there is reason to look more carefully at how longer mortgage terms may change the risk profile of the borrowers and lenders concerned.

Several commentators, not to mention senior figures at the Bank of England, have pointed out that a longer mortgage term allows for less leeway should the mortgage-holder ever require an extension. Additionally, the move towards longer terms means that some mortgages could extend into retirement, meaning that the efficacy of mortgage-holders’ pension planning would have a large influence on the risk borne by mortgage lenders. With the unpredictable effect of buy-to-let reforms, the possible exodus of emerging-markets cash from London, and impending interest-rate rises, the risk profile of mortgage lenders is likely to become considerably more complex.

That is not to say that some kind of cataclysmic property crash is definitely imminent, but recent history has some vivid lessons about the perils of a highly-leveraged residential property market, so there is reason enough to reassess how risk is assessed when lending against property.

The challenge is one of accurately assessing a wide range of dynamic and complex risks, many of which interact with each other, as well as with the market itself. That calls for business leaders in the retail finance sector to look in real detail at the risks their institutions may be exposed to.

Doing so in an effective manner means moving away from traditional, static methods of risk modelling, and instead using calculations that are based on a mathematical model of the business and its market. This makes risk modelling considerably more effective, not just because calculations take account of the wider context and circumstances of the business, but because they can be run on multiple different scenarios. Rather than having simply a best, worst and average scenario, the model can assign a specific probability to each particular set of outcomes, helping the leaders of the business to plan and define their potential responses in advance.

Residential property lending in the UK has been a resounding success for the finance industry in recent years. However, as the dynamics of the market change, it is vital that lenders are able to respond effectively, in a manner which delivers value for both shareholders and customers. Banks whose leadership have an in-depth understanding of potential scenarios, as well as the risks that they face, will be those that continue to prosper in years to come.