It has been some time since the Advisory on Interest Rate Risk Management was issued in January 2010 and if you have not noticed, it has been taken quite seriously by bank examiners. The advisory has required some financial institutions to tweak their existing ALM systems and, in many other cases, it has required a complete overhaul. Simply stated, bankers are increasingly expected to understand how their ALM process and system actually works and homemade Excel spread sheets are increasingly less acceptable.
In the big picture, the 2010 advisory was formulated for all the right reasons. We are experiencing near-crisis credit issues and historically low Treasury yields. Every banker should clearly understand what will happen to the institution’s net interest income and market value of equity if shocked with a spike in rates of 200 to 300 basis points (which would still represent historically low rates).
Nonetheless, there are still many bankers who have been able to satisfy formal regulatory requirements without completely understanding their ALM models and therefore, are hesitant to rely on its output to manage and structure the balance sheet. Simply looking at the bank’s risk profile, given various rate scenarios, is just the beginning. Management should thoroughly understand the many moving parts of the balance sheet and the reasons why changing rates lead to changes in income and value. The ALM process is more than an abstract regulatory exercise. Understanding the assumptions that are implicit in the model and the impact of these assumptions is critical. It is also important to use the bank’s history and management expertise to establish applicable assumptions, as opposed to relying on unrelated abstractions.
A more thorough embracing of the ALM process should involve the following:
First, understand the broad methodology inherent in your model. Make sure you understand the difference between a “ramped” simulation (gradual change in rates) and “shocked” simulation (immediate and sustained). Are betas being used (changes in liability rates in relation to overall rate changes) and if so, how were they established? Do you have empirical data to support the betas and do you have faith in their reliability if rates spike up after years of lingering near zero?
Second, understand how changes in the MVE are being calculated. This calculation calls for an immediate and sustained shock of the entire balance sheet. The source of the discount rates being used to calculate value should be reviewed periodically, as rates change. Are they abstractions or do they relate directly to your history and balance sheet? How are the durations of transaction accounts being calculated and do these values truly represent your balance sheet? What impact do these calculations have on the MVE if rates change?
Understand the details related to the re-pricing of the loan portfolio. To what extent will the floors you have in place cause loan re-pricing to stutter as rates increase? Know precisely what rates you are using to re-price maturing loans and how variable-rate loans are scheduled to reset. Review your indices and how you expect them to perform as rates increase. Where do the re-pricing rates used in the model come from? Are you guessing at the re-pricing rate, or are you using a market rate that relates to your bank’s actual pricing history?
As a practical matter, a clear understanding of the above issues and many related issues, is conducive to making more intelligent manage decisions. For instance, many banks are wallowing in liquidity due to weak loan demand. It is not uncommon to see 10 percent (or more) of total earning assets in overnight funds. This position tends to result in a high liquidity ratio, which is no problem for regulators. If rates should unexpectedly increase, the bank’s interest income would increase dramatically, as overnight funds would re-price immediately; of course, the expense of some liabilities would also increase. This would be a good thing, right, or would it depend on the rationale underlying this position? If the accumulation of excess funds is a conscious decision based on a complete understanding of the consequences (reduced current income) of the position, and not merely fear or inaction, it would be justified. If, however, the decision is based on blind fear, it may feel like a safe position, but it may not be soundly based.
Take the time and make the effort to thoroughly understand your asset/liability model. If you are using a vendor or third-party provider, ensure they are willing and able to explain the basis of every assumption. Remember, you will be held accountable for any knowledge gap that might exist. Discuss the bank’s current position with the board at least quarterly and review the model assumptions with them. Explain the bank’s risk profile in detail and point out how the model assumptions are bank-specific and shaping the output. A working knowledge of your ALM model is imperative from a regulatory and management perspective.
Lonnie W. Harris is executive vice president in the asset management group at Country Club Bank, Kansas City.
Copyright (c) December 2011 by BankNews Media.