Bankers have eagerly embraced risk analytics and modelling as powerful tools to help identify and prevent another 2008-type financial crisis. While analytics – and better overall risk management – can help banks head off the next crisis, smart banks are also investing in risk analytics to establish and maintain an advantage over their competitors.
For banks to tap into the full potential of advanced analytics, however, they should address some difficult challenges, including vast quantities of poorly organized data, inadequately skilled staff and risk management operations still stuck in silos.
According to Accenture's recent study, nearly three-quarters of bank respondents said they would increase risk analytic spending by more than 10%. That is indicative of their desire, not just to improve credit performance, but to find new areas of profitable growth. In the U.S., for example, banks are seeking to improve their ability to understand capital allocation at the pre-transaction level and to conduct more segmented analysis. We believe that risk analytics can help banks in four key areas:
Improving credit performance (and reducing credit costs). The volume of non-performing loans is still high at many banks. By identifying early warning indicators that may be emerging, such as a drop in equity on the borrower's principal residence securing the mortgage, risk analytics can help reduce the number of bad loans. Risk analytics can also help banks reduce capital by identifying high-risk customers and non-profitable accounts.
Coping with regulations. Risk analytics can help banks address some of the unintended consequences of regulation. For example, scenario analysis can help them better assess the impact of increased capital requirements, such as restricted lending and reduced levels of capital available to generate income, as well as the resulting shifts in their customer base and product portfolio.
Assisting with growth and expansion. The competitiveness and profitability squeeze in advanced economies is pushing larger banks in these regions to look outside their home countries for opportunities in emerging economies. This is especially important as these banks face net interest margin declines. Banks can use analytics to help their acquisition models and improve their chance of success in such markets. Analytics can assist them with picking more profitable customers while managing non-performing assets.
Dealing with the outside world. In addition to financial risk factors, banks are also incorporating into their risk models the effects of world events and external factors, whether environmental, political or financial. Analytics can help banks model the impact of natural and industrial disasters, as well as financial crises, in an increasingly interconnected world.
Our research indicates that bank executives are not worried about the availability of data; the problem is in applying the right tools to the right data. For example, banks have often looked at country risk on an annual basis. Recent experience in the Middle East and in Europe, however, indicates that country risk should be examined more frequently, even as often as monthly, and with a proactive view of potential changes in each specific geographic area.
Many banks are unable to leverage risk analytics because of their inability to integrate risk analyses across different businesses. Only slightly more than a quarter of those we surveyed said their organizations had a fully aggregated view of risk, and nearly half said that risk analytics is leveraged only in silos or pockets within their firms.
Identifying and developing the right skills is also essential to using risk analytics effectively. It is not just the technical and quantitative capabilities that are in short supply, it is the business knowledge needed to build meaningful models. Banks that are now leaders in credit risk appear to have been those that were ahead of the pack in setting up teams dedicated to analytics.