<img height="1" width="1" style="display:none" src="https://www.facebook.com/tr?id=815305791870634&amp;ev=PageView&amp;noscript=1">

Echo Partners Community Bank Blog

    Interest Rate Risk Fuel

    Close-up of hoses in a service station-1

    Just like your car, your interest rate risk model gets you from point A to point B. With IRR models, the journey is from your core system data to your rate sensitivity measurements and reporting. That gets bank management, and your examiner, where you want to go.

    But just like your car, without enough fuel, or without the right fuel, completing your journey can be problematic. We know what fuel to put in our car, but what’s the fuel for your IRR model?

    Bank-specific assumptions are the fuel for your IRR model.

    Bank specific assumptions include the average life and rate sensitivity beta for your nonmaturity deposit accounts (NMDAs) as well as the prepay rates for your loans, and they’re critically important to an accurate IRR model result. They’re so important because they represent the biggest unknowns in your entire asset liability process.

    Interest rate risk models work by modeling the institution’s cash flow changes associated with changes in market rates. And like all models they work best when the inputs accurately reflect reality.

    Consider your balance sheet. Every asset and liability on a financial institution’s balance sheet has both a stated maturity and a rate set or formula except your NMDAs. Similarly, your loans have a stated maturity and amortization but they’re subject to prepaying early.

    Unless you accurately estimate the average life and rate sensitivity of your NMDAs and the prepayment behavior of your assets, your IRR projections will suffer. In fact, these 2 sets of assumptions by themselves are sufficient to completely change your reported interest rate sensitivity from asset sensitive to liability sensitive, or vice versa.

    Because these bank-specific assumptions are so important to a robust IRR process, the regulators specifically called them out in the landmark 2010 Advisory on Interest Rate Risk. They said…

    “The regulators remind institutions to document, monitor, and regularly update key assumptions used in IRR measurement models. At a minimum, institutions should ensure the reasonableness of asset prepayments, non-maturity deposit price sensitivity and decay rates, and key rate drivers for each interest rate shock scenario.”

    Our regulators then specifically followed up with the 2012 Interagency Advisory on Interest Rate Risk Management Frequently Asked Questions…

    “Can an institution use industry estimates for non-maturity-deposit (NMD) decay rates?

    Answer: Institutions should use assumptions that reflect the institution’s profile and activities and generally avoid reliance on industry estimates or default vendor assumptions….An institution can contract with an outside vendor to assist with this process if necessary….Similar considerations should be given to other key rate drivers and prepayment assumptions used in the IRR model.”

    Since then, examiners have been on the lookout for bank-specific assumptions along with appropriate documentation. It’s not a matter of if your examiner will question your bank-specific assumptions, but when.

    NXTsoft Data Analytics can help you meet this regulatory requirement by performing, delivering and documenting a statistically valid deposit study and loan prepay study. All at a surprisingly affordable price.

    Ask for more information on data requirements and deliverables.

    Why You Should Early Adopt CECL

    Businessman standing and making his choice between times

    I’d encourage you to ignore FASB’s recent proposal to delay CECL to 2023 and early adopt now. Here’s why:

    1) CECL will require most institutions to increase their loss reserve, often significantly. It’s just common sense that if you change from an annual reserve to a life of loan reserve that the reserve is going to increase.

    2) Bank regulators have provided a 3-year phase in of the Day One CECL adverse impact on capital. This helps offset the initial reserve build.

    3) Current credit conditions are benign leading most banks to a known and acceptable CECL starting point.

    Note: If you don’t know your CECL impact you are behind the curve. Ask me and I will quickly prepare a CECL estimate for you.

    4) We have an inverted yield curve, ongoing trade war and face the prospect of a currency war. Expect a less favorable credit environment (generating even higher CECL loss rates) as the economy slows. Why chance it?

    Early adopting CECL is definitely a case of picking the devil you know. If you wait you will likely face a less favorable implementation environment with even larger CECL reserves.

    Strategic CECL Approach

    battle of pawns

    What is your CECL goal? We need CECL for accounting and regulatory compliance. How we implement CECL drives numerous other results.

    Do you want to minimize your CECL reserve? Sounds like a dumb question doesn’t it? But obtaining a smaller reserve may not be what you want to achieve.

    A larger reserve reduces both reported earnings and taxes. But remember that your ultimate CECL loss will be the same as your incurred loss, so earnings lost in one period are made up in another. Pure timing difference.

    So what’s the downside of a larger reserve? None really if you don’t mind deferring earnings and taxes. Many bankers often lament they wish they could take some of today’s known earnings and push them into tomorrow’s uncertain earnings. Here’s your chance. Plus you get to invest the reserve so any earnings reduction is somewhat offset.

    What you decide about your reserve impacts how you implement CECL. No need to pay up for a fancy CECL methodology if it just delivers a smaller reserve. That means you are paying more for the privilege of reducing the reserve you really want to grow.

    Profit maximizing banks should select the simplest CECL methodology they can justify. As with many things simpler CECL really is better.

    CECL Migration

    close up of binary numbers background pattern

    Migration tracks loss experience compared with various credit milestones. Common migration variables might include credit score, LTV, or other credit grades.

    Migration relates reserve patterns to changes in credit quality instead of cumulative losses. As such bankers might expect migration to result in lower CECL reserves.

    Think of migration as a vintage analysis that focuses on credit quality factors instead of time. Just like vintage uses time from origination to estimate reserve patterns, migration uses changes in credit quality indicators.

    For most community banks and credit unions the challenges of migration center on data. Migration is definitely a step up in complexity. Without a systematic process to identify, track, update and audit the credit factor history on a loan by loan basis migration may not be possible.

    Community bankers must weigh the tradeoffs between promised lower reserves against the increased data requirements.

    Keep in mind that while CECL might accelerate and increase your reserve building it won’t change your overall credit loss.

    Which is more important to your institution…Minimized reserves or simplified and less expensive processes?

    CECL and the Overachiever

    Workplace with tablet pc showing charts and a cup of coffee on a wooden work table close-up

    CECL and the Overachiever

    A few recent conversations with bankers about CECL have surprised me. I’m not surprised they’re preparing for CECL but I am surprised about their approach.

    Instead of looking for a simpler solution these small institutions were focused on how they could implement a loan level analysis.

    Now don’t get me wrong. I’m a data guy and I always encourage bankers to pursue the most accurate relevant analysis. But a successful sophisticated analysis depends on having the right inputs available. The right inputs include not only the type of input but also the number of observations.

    Without sufficient loan volume a highly segmented loan level analysis is doomed to fail. A failed analysis might deliver an inaccurately large or small CECL reserve. The kicker is that you probably won’t know which until it’s too late.

    The main risk with a simple model is a marginally larger than optimal reserve. The main risk with a sophisticated model is misplaced confidence in an inaccurate result.

    Instead of trying to develop the most sophisticated CECL model, these bankers should focus on identifying a size and complexity appropriate approach.

    That’s what our regulators keep telling us. CECL is designed to be scalable for a reason.

    Probability of Default (PD)

    gambling dice with face on background

    PD is a very simple computational approach to CECL…If you have and can document the required input data.

    The probability of default expected value equation is

    PD x EAD x LGD x (1-RV)

    PD is the probability a particular loan enters default (we will define as 90 days past due). Let’s estimate a 5% risk of default.

    EAD is exposure at default. For example, a loan with an original balance of $1.2mm might be expected to have a remaining balance of just $1mm at default.

    LGD is loss given default. A loan entering default might expect to lose 80% of its value.

    RV is recovery value, or the amount we might recover after default, estimated at 10%.

    Putting these variables all together we end up with:

    5% x $1mm x .8 x (1-10%) = $36k reserved amount

    With enough time and effort most financial institutions can gather the required inputs. The minimum data needed would include loan, loss and recovery data as well as history of loans entering the selected default threshold and credit loss experience thereafter.

    PD might usually be expected to result in one of the lowest CECL reserve estimates. Keep in mind that it’s nonstationary. As economic conditions deteriorate you might find both PD and LGD variables exceeding historic estimates simultaneously.

    Quick Guide to CECL Selection

    Woman use of soft drink vending system paying by cellphone

    Here's a brief overview of how to select your CECL path in a few easy steps.

    • Is your institution smaller than $500mm assets?

    If so, an aggregate method should be a practical, safe and effective choice. Regulators have repeatedly said smaller less complex banks and credit unions may use simpler methods. Take them up on it. Plus aggregate solutions offer higher value for your investment.

    If larger or more complex consider vintage with a DCF backend.

    • Select a method that provides full peer data.

    Peer data fills in the missing gaps in your own data. What if you enter a new-to-you loan segment? Use peer data to guide your initial reserve building.

    If you’re larger and more complex with a loan level solution consider adding on an aggregate solution with full peer coverage as an inexpensive backstop and benchmark.

    • Don’t even consider an approach that can’t (or won’t) provide detailed estimates of your specific reserve needs in advance.

    If they can’t demonstrate your results using your data today what makes you think that will change tomorrow? Know what results you are buying before you sign a contract.

    There are a lot of good CECL solutions and approaches. Use these 3 steps to find the one that’s best for you.

    CECL: What Next?

    Image of businessman holding alarmclock against illustration background. Collage

    Smaller less complex banks and credit unions may have the ability to delay CECL implementation until 2023. So with time pressure off what should you do?

    FASB suggests the delay to give you more time to get ready. That means learning from public company implementation, identifying and gathering resources, evaluating system availability, and solving uncertainties about the new CECL standard.

    In other words, use the time to do your homework.

    Run estimates of your CECL exposure. Evaluate different CECL methodologies. Run parallel. Develop board-approved policies and limits. Get your procedures set. Do all the things you need to truly prepare for a sea change in credit loss approach.

    I’m going to suggest one other exercise to help prepare.

    Consider early adoption of CECL.

    There are a few reasons why early adoption makes sense. For example, you’ll avoid the implementation rush hour as everyone targets a later date.

    But the top reason to consider early adoption is that you know and can accurately model the current CECL credit environment. There are going to be no surprises if you lock in today’s CECL reserve.

    Who knows what credit and loss environment will face us 2 or 3 years in the future? Avoiding uncertainty reduces your risk.

    CECL and Procyclicality

    Data spreadsheet and pen-1

    Some CECL critics suggest that CECL is bad policy because they assert CECL is procyclical. By saying that they mean that CECL will require banks to raise reserves during a recession thereby further dampening the economy.

    As evidence critics suggest that if you model CECL against the Great Recession you would find an outsized need to increase reserves during the height of the downturn.

    There is some truth to this view, but as statisticians say, correlation does not imply causation.

    The driving force behind models showing higher CECL reserve building during the Great Recession scenario is not that the economy was in recession. It is the fact that the Great Recession was characterized by unprecedented loss rates in real estate, especially residential real estate.

    CECL relies on historic loss data to estimate future losses. If you have losses that vastly exceed those ever experienced before, CECL will require you to build reserves beyond previous experience. Of course, so would the incurred loss method or any other model.

    Using the past to predict the future only works if the future is like the past. If the future is different all models will fall short.

    CECL Impact on Lending

    Drop of water falling into the water and leaving it circles.

    As banks and credit unions implement Current Expected Credit Loss (CECL) expect to see some changes in your lending.

    All of the talk has focused on the need to reserve the lifetime credit exposure at origination. The natural conclusion then is to expect longer loans to be less attractive. But this generalization misses a subtle point.

    Bank regulators have already provided a 3-year phase in of any CECL “Day One” adverse impact on capital. So you will have an easier path to reserving your portfolio, which will dwarf the need to reserve any new loan.

    Maybe the correct way to talk about CECL’s impact on longer term lending is to say that while CECL might make growth in your long term allocation less attractive, you really won’t be incented to reduce existing long term positions?

    A bigger and more certain impact will come via pricing. Examiners will expect to see you consistently using CECL results in other bank models and decision making.

    Consider loan prices. Pricing must cover interest rate risk, credit risk, admin costs, and provide a return according to your business plan. Slotting CECL credit numbers into pricing models is a natural next step.

    Expect examiners to test if your loan pricing is consistent with your CECL results. Document any exceptions.

    Do you want to grow your bank profits with little to no risk? Click Here to  Discover How

    Written by

    Subscribe to Email Updates

    Recent Posts