Beyond Peer Analysis: Adopting a Benchmarking Mindset

When reviewing their UBPRs, bankers sometimes struggle to find insightful conclusions—If the bank is outperforming peers, this finding receives a mention in the board report.  However, if the bank is underperforming peers, the peer group itself is dismissed as irrelevant (“we’re a lot different than those banks anyway…”).  Neither of which add much value.

If you’re guilty of the above, it’s not entirely your fault.  Bank regulators created the UBPR “peer analysis” to help further their own mission of prudential regulation, and it may not be suitable for the bank’s own performance benchmarking.

Peer analysis vs. benchmarking?

There are three subtle but important differences between peer analysis and benchmarking. Benchmarking looks beyond peer averages to identify top performers; it redefines the nature of an assumed peer group, and it requires a deeper level of analysis from the management team.

Example:  Net Interest Margin (NIM)

For the purposes of the Q2 2021 UBPR, regulators placed a Texas-based community bank into a nationwide group of other banks with assets between $300 Million and $1 Billion (“PG5”).  Looking at NIM, in Q2 2021, the UBPR indicated a value of 3.52 for the bank and an average value of 3.40 for its PG5 peer group.  “Peer analysis” complete.

Look beyond average – With benchmarking, we should look to identify high performers to emulate, not just averages from which to compare.  To do this, we need to know the distribution of NIM values across the peer group (what does “good” NIM look like in PG5?).  In our example below, it turns out hundreds of PG5 banks had a NIM above 4.00.  We should be more interested in how these banks churn such high NIM.

Re-think “peers” – To continue with the above, it’s often helpful to redefine what it means to be a “peer.” Asset size is too broad.  For our example, we’re most interested in similarly sized banks in Texas that have 30% or more of their portfolio concentrated in Commercial & Industrial loans.  When we apply these filters, the outcome results in a much smaller, significantly more relevant cohort of nine banks.

Dig deeper – Lastly, benchmarking requires management to think critically about the attributes of top performers and how those models may be adapted to their own bank.  In the example above, the NIMs of all nine top performing banks were driven almost entirely by superior loan yields (not a funding advantage).  Further, for seven of the nine, superior NIM translated directly into leading ROA.  And it’s worth noting that most did so with below peer delinquencies and allowances.  In short, their operating models deliver stellar results and cannot be easily written off as risky or anomalous. Viewing this bank through the lens of these nine top performers is a far better use of management time than making comparisons to national peer group averages.

The UBPR provides a rich set of data that’s worth a closer look.  With a little extra effort (or software such as Qaravan), bankers can distill this peer analysis into more relevant and insightful performance benchmarks.

To learn more about Qaravan, visit https://app.qaravan.com/auth/sign-up

Article originally appeared in Independent Banker on October 1, 2021.

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Senior Vice President Market Data OTC Markets Group

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