With investment yields at historic lows (just 1.65% at 1Q2011), and credit unions flush with liquidity, it is easy to understand why credit unions are looking for ways to grow their loan portfolio. A critical step in improving performance is to know what you are doing well and where you can be doing better based on facts, not assumptions. Therefore, establishing a benchmarking report is critical to making accurate assessments about current performance, and more importantly, engaging in a productive dialogue about improving the future.
At one level, all credit unions will compare their performance today to their performance in the past. But as external factors exert a greater influence it is even more important to expand your frame of reference. One specific example: the allowance for loan losses. Up until the mortgage meltdown, this was typically calculated based on the credit union’s own historical loss ratios but we all know how that proved to be ineffective in the face of plummeting housing prices and rising unemployment.
Comparing your performance against the credit union industry as a whole can be helpful in starting the conversation about your own performance. But with total loans on the balance sheet shrinking for the second straight quarter, settling for the average may mean you miss a lot of opportunity. Average performance metrics mask important performance differentials beneath the surface.
Therefore, it is critical to compare your credit union’s success against a variety of other standards. These could be an asset-based peer group, a regional group of credit unions, individual credit unions you consider “best in class”, or – best case scenario – a combination of all of the above. Once you do this, you’ll be able to engage your senior team in a robust discussion of your credit union’s opportunities.
So, how can you create a benchmarking report that tracks key success factors across multiple dimensions and against different peer groups, and update it on a quarterly basis? It’s easier than you might think. There is a lot of data that is publically available and easily accessible from the 5300 call reports that all U.S. credit unions file.
Since there are too many data points to attempt to summarize in a single article, this example focuses on first mortgages, which today account for almost 40% of the total credit union loan portfolio. We’ve created this report comparing a credit union to its asset based peer group. Below each slide, we interpret some of the findings and suggest further questions that the management team can use to brainstorm new avenues for growth and find solutions to possible weaknesses.
- Loans are going to be a credit union's highest earning asset, so balance sheet growth is an important indicator of health. However, 52% of first mortgages last year were sold onto the secondary market by credit unions looking to mitigate interest risk. That must be considered when evaluating balance sheet growth. The credit union above is also selling significantly more loans on the secondary than their peer group average which is masking even greater potential balance sheet growth.
- While this credit union holds a lower concentration of first mortgage loans in portfolio (31.52%) than its peer group (44.76%), it is growing the balance sheet over four times faster – 11.94% versus 2.76%.
- The average first mortgage balance is about two-thirds of the peer group average. Average home prices in this credit union’s local market might be lower than average so the credit union could set up a regional peer group to check this assumption.
- The credit union also has a higher concentration of fixed rate loans. This could be due to member demand for fixed rate products, or a potential area of growth if the credit union isn’t aggressively positioning ARMs, another area for discussion.
- This credit union grew its first mortgage originations at almost 40%, while the peer group—on average—had 10% fewer originations in the first quarter of 2011. The credit union also sold a much larger percent of originations to the secondary market—75%. This could spark a discussion of why the credit unions is being so successful in this area and how they might replicate it in other areas.
- While the credit union experienced dramatic growth in their adjustable rate products, they are still a tiny part of the overall portfolio. Is there an opportunity to expand their mortgage offerings in this area to appeal to a new type of member?
- The average first mortgage originated was well below the peer group average. Again, this could be due to strategy (appealing to first time homebuyers) or circumstance (having lower local home prices), or both. Whichever the reason, it would be good to discuss and understand its impact on the credit union’s performance. Lower average balances still cost the same amount to originate as higher balance loans, so this could impact other performance metrics.
- Their peer group is originating more Balloon and ARMs which may indicate there is a market need for these products that the credit union could exploit.
- The percent of members with a first mortgage is relatively low at 1.74%. However, the previous metrics indicated that the credit union is selling a large percentage of first mortgages artificially lowering this metric. (The 5300 includes the dollar amount of loans sold but still serviced by the credit union, but not the number of loans, so it is hard to measure the actual penetration into membership based on this data.) The credit union should pull their own member data to get an accurate assessment of this metric.
- The credit union’s overall delinquency is in-line with their peers, but they have a higher ARM delinquency rate.
- The credit unions modification delinquency rate is higher than the peer group average. There are so many variables that go into this metric, a deeper dive by the management team could be in order. Some further data is available on the 5300 (such as how many of the modifications are considered troubled debt restructures (TDRs) which affects how they are accounted for.)
The metrics highlighted and questions posed above are meant to be an example of how a credit union can use benchmarking data to begin a healthy discussion about their financial performance. Credit unions can do this kind of analysis for many areas of financial performance straight from 5300 data. The sample reports above were built using Callahan’s Peer-to-Peer software, allowing a credit union to quickly update the data each quarter and also to benchmark against different peer groups. Peer-to-Peer subscribers can request the first mortgage benchmarking files by emailing firstname.lastname@example.org.