Using credit union peer data to improve the ALLL
Oct 13, 2015
Fall is the time for fantasy football leagues, and no self-respecting fantasy team manager could possibly compete without relying on performance statistics to draft and track players across the NFL.
Fantasy team managers scour player stats from previous years, comparing them to last year and to projections for this year to determine where players are in their performance trends. An important part of the selection process by managers, however, is examining stats of players in the same position in order identify the various strengths and weaknesses of potential picks relative to other players.
In the competitive world of credit unions, comparative data can also play a role in improving performance and in keeping tabs on similar financial institution players. Even with a calculation as institution-dependent as the allowance for loan and lease losses, or ALLL, credit unions can generate helpful feedback by examining data about peers’ ALLL, according to Sageworks analyst Kevin Abbas.
“An allowance should be a very institution-specific calculation in that it should be based primarily on your institution’s portfolio, policies, procedures, etc.,” Abbas said. “But it can be very useful and helpful while going through the process of calculating the ALLL to compare with institutions that are similar to your own. It can provide support for your calculation or it can point out things that maybe you need to look into further in terms of your allowance.”
Here are four metrics for which the Sageworks’ ALLL solution can provide peer comparisons:
Allowance to total loans: The metric most financial institutions want to know, this ratio describes how much an institution has set aside in ALLL reserves for its given portfolio. Some of the factors that can cause differences in this ratio among financial institutions: the composition of the loan portfolio, underwriting and collection policies and practices, and charge-off practices. Although individual factors may differ between institutions, reviewing the allowance to total loans for your institution can still provide a good gut-check in terms of how you compare to your peers. You can also be sure this is a ratio that your auditor and examiner review, so if you aren’t consistent with your peer group, you should be prepared to document why.
Allowance to net losses: By comparing over time the allowance to charge-offs, credit unions can determine if they are under- or over-reserved. Looking at how peers perform in this metric can help you benchmark your reserve levels, but caution is warranted. Charge-off rates (even within a single financial institution) can vary from year to year, and comparisons of the allowance and short-term averages of net losses could be misleading. If a credit union’s ratio is shrinking over the long term while other credit unions’ ratios are increasing, however, more investigation may be prudent.
Recoveries to total loans: This ratio provides a gauge of how successful the credit union is at recovering its charged-off loans. A ratio that is lower than that of peers could indicate, among other things, that the credit union may need to put more resources toward collecting charged-off notes. It might also mean peers have more aggressive charge-off policies and charge off a loan more quickly, making it easier to recover it. In either case, a big difference (either positively or negatively) with the peer average could mean it may be worth more research into that metric, Abbas said.
Net losses earnings coverage ratio: This ratio indicates how prepared a credit union is to withstand potential future losses, and it is calculated by combining net operating income (before taxes, securities gains or losses and extraordinary items) and the provision for possible loan and lease losses, then dividing that figure by net loan and lease losses. “You’re looking for a higher ratio, because the higher the ratio, the more earnings the institution has to withstand losses in the portfolio,” Abbas said. As with some of the other measures, comparisons with peers must be carefully considered, due to differences in loan portfolios and in practices tied to underwriting, collections and charge-offs.
As Abbas noted, credit unions can get the most out of peer data when they select institutions that are truly peers. Some characteristics to consider when selecting a peer group include product mix, size and geography. Reviewing comparative metrics for only those credit unions in your market or only those carrying the same products will not generate as much helpful, accurate analysis of your institution’s ALLL.
After all, comparing a running back with all of the wide receivers available wouldn’t make sense for your fantasy football team, would it? For meaningful analysis, managers need to know how their prospective player stacks up against others in the same position.
To learn more about selecting peer groups, see this ALLL Insiders article, “Choosing the right peer group.”
Image credit: Tom Newby via Flickr CC
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