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AICPA: Buzz About CECL

We had the benefit of speaking at the AICPA conference on one of our favorite topics, how to use ALM for actionable business intelligence. In this case, the focus was on how a credit union can support changes to remain relevant.

Another topic that also had a lot of buzz at the conference was CECL, which can also impact relevancy. Based on the discussions, we thought it would be a good idea to repost the blog from May 19, 2016.

CECL’s Threats To Your Business Model:  Six Questions To Consider</font size>

CECL is a new set of rules that every credit union eventually will have to play by. While it may not be in effect until 2021, many credit unions could find that they need all that time to reposition their business models to prepare for its impact. Keep in mind that the impact being discussed currently is in a good credit environment. How does the exposure to CECL change in a bad credit environment?

At the end of 2015, the nearly 500 credit unions with assets over $500 million had an average net worth ratio of 10.9% and an ALLL of 0.9%. If the impact of CECL causes ALLL to increase 50%, or even what some refer to as a worst case of 100%, the net worth will be reduced but not dramatically for most.

For those same credit unions, if you were to go back to the Great Recession, what potential impact could CECL have created?

CECL Graph

While many experienced a reduction to ALLL in the years following, what would have happened to the credit unions that would have had materially lower net worth? How could this impact business models and strategic decisions going forward?

Every credit union should be asking:

  • Because CECL will be extremely volatile in changing economic conditions, how much net worth do we need to have to prepare for that potential additional volatility?
  • How should our business model be repositioned so that we have enough net worth in volatile, bad case scenarios?
  • If our current target markets are susceptible to credit risk and could wipe out significant amounts of net worth under the new CECL rules, do we need to adjust who we target in the future?
  • After CECL is in place, loan growth, especially strong loan growth, will come at much lower initial profitability. How does this impact our business model?
  • What changes should we be making, if any, to our concentration risk policy?
  • If the battle for prime paper increases materially, will we choose to increase our presence in that battlefield, and how will we differentiate ourselves in order to remain relevant?

If you don’t think these questions are relevant, consider that in today’s good credit environment, 22% of all existing auto loans are to subprime borrowers (Wall Street Journal). How much could this increase in a recession due to credit migration?

As you wrestle with the mechanics of implementing CECL, it is even more important to think about the business model implications. In addition to the current economic environment, think through what could happen in a recessionary environment when loan losses can mount rapidly and the impact of CECL can be magnified.

The point is not to dissuade you from taking credit risk, but rather to stress that the rules have changed; everyone will need to be much more deliberate with their business models, strategic plans, and the execution of those plans to be well-positioned for CECL.

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c. notes – Evaluating Risk/Return Trade-offs When Margins Are Razor Thin

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It is no secret that decisions today are more complex and far-reaching than ever before, and margins are razor thin. Traditional and non-traditional competitors on the battlefield keep multiplying and plotting to get more of consumers’ business, all while credit unions have to throw resources toward protecting their flank from attacks such as the CFPB, CECL, NCUA’s NEV test, and RBC.

This c. notes outlines advanced approaches to evaluating risk/return trade-offs so that decision-makers can have actionable business intelligence at their fingertips.

To continue reading, please click here.

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The Importance of Isolating Variables within Stress Tests

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Stress testing is an important function of long-term interest rate risk modeling and risk management processes. As with any long-term interest rate modeling, stress testing requires both skill as well as an ability to fully understand and determine which assumptions influence the outputs and which assumptions are driving the results of the stress test.

During a recent model validation we performed, the importance of isolating variables within stress testing was punctuated once again. The objective of this particular stress test was to understand the impact widening credit spreads would have on asset valuations within the net economic value (NEV) simulation. In looking at the impact of widening the credit spreads, we observed that the overall NEV ratio was not as adversely impacted as one would have expected and as the asset devaluation would have implied.

Given that the overall results were not adding up, a deeper dive into the inputs was necessary. In analyzing the inputs, we discovered the model setting that widened the credit spreads on the assets had also increased the rates on the borrowing yield curve, which were being used to value non-maturity deposits (NMDs). The increase in the borrowing yield curve rates was thereby offsetting the asset devaluation caused by widening the credit spreads.

It is perhaps both reasonable and defendable to say that an increase in asset credit spreads could also be strongly correlated with an increase in borrowing rates. Indeed, both the science and math behind this stress test could be wholly appropriate. That said, however, increasing the rates on the borrowing yield curve unnecessarily detracted from both the spirit and objective of the stress test, which was to understand the impact widening the credit spreads would have on asset valuations.

The importance, therefore, of isolating variables when running stress tests and doing sensitivity analysis cannot be underestimated. It is both a science and an art, and interpreting whether the results of the stress test accomplish the objective and make sense should not be lost within the analysis.

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Get Them While They Are Young

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So often, credit unions focus on attracting younger members in their 20s.  The intent is to make them lifelong members so the credit union can benefit when those members are older and ready to borrow.  This idea makes sense when considering how consumers’ income and expenditures increase as they age, particularly in what is considered the prime borrowing years of 30 to 50 years old.

bls-income-vs-expenditure-for-us-by-age-group

While the idea may make sense, there are some questions on the approach.  Let us start by taking a look at some numbers.  The graph and chart below represent a composite of the demographic data we have gathered from strategic planning sessions we facilitate.

total-loan-deposit-and-non-interest-income-by-age

It is no surprise that as members move into their 30s and 40s, the balance of loans they hold increases because they buy houses and more expensive cars.  What surprises most credit unions, however, are the loan balances members still have in their 50s, and especially in their 60s.  In fact, the 60-year-olds are on par from a lending standpoint as the 30-year-olds and this is not just because of higher balance mortgage loans.  For those in their 60s, auto loans continue to be a major component of that age group’s borrowing.

Let’s circle back to the members under 30.  They account for 25% of the membership, yet only 9% of the loan dollars and 6% of the deposits.  Even taking non-interest income into account, which is usually thought to be the area in which younger members shine, they punch below their weight.  Overall, these members do not contribute very much compared the other age brackets.  While this may be expected, there are some questions to consider:

  • What types of resources are being spent to attract, retain, and service these members? At 25%, they are a sizable portion of the overall membership.
  • How long will they have to be members before they become profitable, contributing members to the co-op, making up for the resources spent to retain and service them until then?
  • Does the average length of membership of 30- and 40-year-olds support the idea of 20- year-olds becoming lifelong members?
  • Does that average length of membership also line up with the number of years it takes for those in their 20s to become profitable members?

The average length of membership for those in their 30s tends to be 5 to 7 years and 7 to 9 years in their 40s, suggesting that most 20-year-olds do not become lifelong members.  Furthermore, some credit unions that track this information regularly have seen as much as  one-third of young people leave the credit union when they turn 18.

Lining up these numbers with the competition from niche market players (think FinTechs) that are providing one-off services, getting them while they are young is harder and harder to do. Ultimately, credit unions have to ask the question of how many resources are they willing to commit on members that may not be with the credit union long enough to be profitable, especially when there may be more opportunities in other areas of the membership.