ABA Banking Journal
By Ashley Gunn
Risk management is a big task with lots of details—and risk managers can sometimes lose sight of the forest for the trees. What if there was a bigger-picture way to examine risk? Brian Ranson, a credit risk consultant from Toronto, suggests such an approach, advising banks to better forecast expected losses, thus leading to less volatility within the bank.Ranson—who spoke at ABA’s recent Real Estate Lending Conference—explains that managing risk within a bank is often guided by diligent accounting standards and prudent regulatory requirements. Bankers can often get weighed down by these measurements, though, causing them to lose sight of their main objectives. That’s a potentially harmful change, which is why he suggests learning how to more accurately predict expected losses. In order to do this, the bank needs to ask the right questions. Ranson provides two examples:
- How much riskier is a one-year small business loan compared to the same loan over five years?
- What is the normal life of a defaulted amortizing five-year loan?
By figuring out the answer to these questions, Ranson believes a bank will be able to better predict the likelihood of a loan’s performance, which helps better predict expected losses that can eventually affect the bank’s bottom line. Based on his research, he projects that a five-year loan is 14 times more likely to default than a one-year loan with the same rating. So why is the pricing not 14 times more expensive?
Furthermore, for a five-year loan, Ranson says, the average time of default occurred at 26 months. In fact, he claimed that 80 percent of all defaults fall between 24 and 40 months, meaning that it’s possible that the risk associated with different term loans could be underestimated. By analyzing the data for just these two questions, his research shows that the market might not be pricing the different term loans correctly. By asking additional questions like these, bankers could learn even more information that will help improve loan performance. Therefore, Ranson suggests that banks consider doing their own due diligence or creating internal risk weighting systems in addition to their accounting and regulatory requirements.
But how can bankers gather the data they need to answer Ranson’s key questions? He stresses the importance of investing in readily available data and suggests different companies, such as PayNet, as possible sources. He also emphasizes that focusing on historical data, which may often be an accountant’s preference, might not be sufficient enough to help the bank prepare for the future. Instead, he said bankers should focus on their current portfolios of performing loans. Present data could likely be the best guide to highlight a changing business environment.
Ranson says that many bank failures between 2008 and 2011 were caused by credit losses on commercial real estate. He argued that if banks had employed his credit loss analysis methodology, supported with present data instead of historical performance, they might have caught losses before they occurred. Regulatory agencies seem to agree—which might explain why they have increased their scrutiny of high-risk commercial real estate loans over the past years.
Investing in Ranson’s techniques, if properly performed, could potentially lead to better performance for the bank. Is your bank asking the right questions?
