Community financial institutions are familiar with utilizing their asset/liability management solutions to limit the risk of rising interest rates. But is your ALM process helping avoid the risk of underperformance when rates fall or remain low?
Obviously, protecting financial institutions against the impact to capital and earnings of rising interest rates has been the particular focus of regulators for more than a decade. Bankers since the financial crisis have become accustomed to seeing language like the following:
“The FDIC is re-emphasizing the importance of prudent interest rate risk oversight and risk management processes to ensure FDIC-supervised institutions are prepared for a period of rising interest rates.”
FDIC FIL-46-2013 October 8, 2013
ALM seen as checking the box
It’s understandable, then, that many financial institutions view the ALM model as a tool for completing a regulatory to-do. In that view, the asset/liability management solution is something to be utilized in order to soothe examiners’ and directors’ concerns about how the financial institution would fare in a worst-case scenario of rising interest rates. The worst-case scenario (as played out in most ALM models) could range from an interest rate increase of anywhere from 100 basis points to 400 basis points. Most analysis focuses on the outcomes of these types of scenarios, and discussion concentrates on how to limit risk tied to rising rates.
However, back when the FDIC sent that 2013 letter mentioned above to financial institutions, the effective federal funds rate was 0.09%. Over the last six years, that rate has risen less than 175 basis points to 1.83% (as of October 2019). It actually has fallen since April as the market anticipated three cuts to the Fed’s target fed funds rate. In other words, rates haven’t increased dramatically at all.
Extreme focus on risk of rising rates leads to underperformance
The extreme focus of asset/liability management efforts on the risk of rising rates has meant too little focus on how to use ALM to grow earnings and capital in a period when rates have remained low, leading to underperformance at some financial institutions, says Dave Koch, Managing Director of Abrigo Advisory Services.
“A majority of community financial institutions focus on how to limit the risk of rising rates instead of value creation,” he says.
Rather than viewing the ALM process as a regulatory requirement, community financial institutions can use the ALM process as an analytical tool to manage profitability and safety for stakeholders and management – regardless of the interest rate environment.
“A strong ALM process and model should provide financial institutions with answers to critical questions, like what loans, investments, deposits, and borrowings to pursue – and at what rate and terms,” Koch says “It’s about deciding how I, as a financial institution, get to my financial goals while managing potential risks.”
Using ALM to grow earnings and capital
However, 70 out of 100 CEOs and CFOs informally surveyed by Abrigo, formerly FARIN, acknowledged they don’t rely on their ALM modeling for decision-making.
One reason ALM models are underutilized is that many bankers don’t trust the results of their ALM models, according to Koch. They recognize that most ALM models lack precision due to a number of factors. Incoming data from the core system might be missing information. For example, a variable loan might be missing the repricing index and margin information because it was set up on the loan system without that data due to human error. Or non-maturity deposit data might be using incorrect assumptions about how long those accounts will remain with the institution because the assumptions are based on industry averages.
Financial institutions certainly have options to correct such issues so they can begin using their ALM process for strategic decision-making. Running a core deposit analysis provides institution-specific, updated information about decay rates for non-maturity deposit accounts, and working with ALM advisory experts can ensure the ALM model has the necessary data and power to generate decision-useful information. For example, institution-specific information on attrition rates of specific non-maturity deposit account products can feed into decisions about what rates to offer customers on those products, rather than relying solely on what rates competitors are offering.
“When it’s done right, ALM provides a community financial institution with the right guidance on maximizing profit while managing risk,” Koch says.
Financial institutions that maximize profit while managing risk will be able to not only avoid the hazards of extreme increases in interest rates, they will also be able to elude the danger of underperformance and failing to create value during more routine interest rate periods.
Mary Ellen Biery, Abrigo