By Walt Williams
Nearly three decades have passed since the last time interest rates spiked as fast as they have in 2022, meaning many of today’s bankers have spent their entire careers in a much calmer rate environment. That lack of experience can prove a hindrance when managing rate risk, but not a crippling one. Proper modeling and a back-to-basics approach to asset-liability management could help.
Raj Mehra was working for JPMorgan Chase in 1994, when the Federal Reserve nearly doubled interest rates to 6 percent in a year. “We’ve clearly been here before,” says Mehra, who is now EVP and CFO at Freedom Bank of Virginia. “Not everyone might remember it, and everyone’s going to have a different playbook for how to deal with it.”
Freedom Bank’s playbook has benefitted from previous decisions such as interest rate swaps made early in the pandemic when rates were low. Other institutions have also been looking ahead and developing their own sets of play calls, although those strategies are only as sound as the modeling used to produce them.
“Hopefully all [ALM] practitioners are running various scenarios to be able to tease out what risks may lie in their balance sheets for a various set of interest rate outcomes,” says Dan Schwartz, director, corporate treasury, at Discover Financial Services.
Real-world modeling
The better a bank understands the behavioral tendencies of its deposit base, the better it will be able to control its cost of funds as the Fed continues to move rates skyward, says Darnell Canada, managing director at Darling Consulting Group. And that data must reflect what is happening in the real world.
“The inputs and the assumptions that go into these models ought to be changing as the environment has been changing,” Canada says. “Typically, that doesn’t happen in the small window of time that we’ve seen. Typically, the Fed doesn’t move this quickly.
“That’s one of the key messages that we’re trying to get across to folks: it can be dangerous to make assumptions that my balance sheet is going to behave the same way it has in the last one or two or three rate cycles because the current cycle doesn’t look anything like the last two cycles.”
Robert Perry, principal at ALM and investment strategy firm ALM First, has similar advice: “It’s important to make sure that modeling and your asset pricing are live: that they’re up to date with market rates, and that you don’t kind of get behind the eight ball and misprice assets. If you’re writing auto loans right now not that far north of where Treasury rates are, and you’re capitalizing that asset and putting it on your balance sheet, you’re not getting compensated correctly for that asset.”
Focusing on the basics
Modeling is one thing, but Susan Sharbel, senior advisor at Abrigo, which ABA endorses for loan loss accounting solutions, takes a back-to-basics approach in a recent paper on five ALM best practices. She acknowledges none are earth-shattering, but they are good practices no matter the rate environment. But some do call for a different mindset, such as her first recommendation, which is starting the ALM process with an updated capital plan.
“Typically [capital planning] is viewed through a regulatory lens: the regulators demand it, so we’ve got to do it,” Sharbel says. “But really capital is also your buffer. It’s something that you can leverage to grow the institution to become more profitable. It’s very important to have a solid plan so that when you do your stress testing, you can see what the effects are on your capital.”
“Expansive” scenario analysis stress testing is her second recommendation. Again, assessing risk is something banks already must do, but many aren’t good at it, at least in Sharbel’s mind. Just as people who own a motorcycle want to buy the most expensive helmet they can afford for maximum protection, “institutions really should invest in the most robust model that they can afford,” she says.
Her third recommendation is to ensure reasonable assumptions in the ALM model: Use institution-specific data whenever feasible. Use account-level data and a customized chart of accounts as an ALM best practice. Fourth on the list is using a measurement system that captures all short-term and long-term risks. “A lot of time many institutions capture risk in what we call silos,” she says. “So here’s your credit risk. Here’s your interest rate risk. Here’s your liquidity risk. Here’s your option risk. They’re individually calculated, right? But that’s not how they happen in the bank. They happen all at once. … It’s far more productive to look at it all, you know, because they’re all affecting each other.”
Finally, Sharbel recommends an annual ALM model validation. Like capital planning and stress testing, validation is something already required of institutions, but that doesn’t mean they shouldn’t do the bare minimum, Sharbel says. High confidence in an ALM model leads to better business decisions, and “we’re in a time that decision-making is paramount.”
