Establishing and maintaining a sound interest rate risk (IRR) program is crucial to ensure proper balance sheet structure and comply with Regulatory expectations. During my 20+ years as a senior FDIC examiner, I routinely saw organizations experiencing issues with their ALM/IRR practices, ranging from loose misunderstandings of the guidance to critical errors that put the health of the organization at risk. Unfortunately, in my current advisory role, I see the same issues all too often.
At Plansmith, we understand that interest rate risk may not be something you deal with on a daily basis, or were ever extensively trained in. We see many scenarios – none of which involve financial managers purposefully trying to be out of compliance. Perhaps you filled a role within your organization where the previous individual had poor processes in place, and you inherited the resulting task of weeding through the mess. Or, possibly you came into a situation where there was little to no process in place. Or, maybe your team has a fairly strong IRR management program in place, but you’re unsure of which tasks fall through the cracks due to lack of time, resources, or experience. Given our extensive experience examining and advising financial institutions, it’s pretty easy for us to spot issues, identify solutions, and implement programs to counteract bad processes utilized by well-meaning financial institution managers. However, for those individuals who are responsible for ALM/IRR programs within these institutions, the task at hand may not seem as straightforward.
While virtually all financial institutions conduct regular IRR modeling, there are three common pitfalls that can quickly derail any IRR management program.
- Bad Assumptions
Assumptions are the foundation of any financial model, and IRR models are no exception. As such, the model assumptions are typically subject to close scrutiny by examiners and auditors. They tend to view loan prepayments, deposit pricing (betas), and non-maturity deposit decay rates as the three assumptions that have the most influence on the model. Regulatory guidance notes that all model assumptions should be based on institution-specific data (not market, peer, or industry data), be well supported and documented, and be regularly reviewed and updated by management. Failure to do so frequently leads to exam criticisms and unreliable model results.
- Incomplete IRR Management Programs
According to Regulatory guidance, IRR management programs should include:
- IRR models that are consistent with the size and complexity of the institution
- Assumptions that are well documented and developed using institution-specific data
- ALCO and Board Reporting (at least quarterly)
- Backtesting and Sensitivity Testing
- Comprehensive policies that include limits for all IRR measurements
- Independent Review
- Not Being Prepared for Exams and Audits
Having and running a good IRR model is not enough. Not understanding what the model is telling you, not knowing what the regulatory expectations are, and not complying with prior exam recommendations can all lead to regulatory criticisms ranging from informal recommendations to formal enforcement actions. It is critical that financial institution managers understand the model results, can explain them to the Board and examiners, and can reconcile variances from prior periods.
The key takeaway is that regardless of your personal understanding of interest rate risk, the dangers of not addressing potential issues are real. Don’t feel embarrassed – simply reach out to the experts and get a second opinion as soon as possible. Though the negative effects of not fixing these pitfalls are significant, so are the benefits of fixing them.
So, if you struggle with these pitfalls, or if you are unsure if your IRR management processes measure up, we can help.
Give us a call or email us at email@example.com to discuss your organization’s individual needs.