Are you someone who looks at the forest? Or do you look at the trees? Looking at a forest level, you see an entire ecosystem—how parts are interrelated and interdependent. By studying individual trees, you understand how one influence can lead to different outcomes, why some trees thrive while others struggle.
Now, apply this concept to credit unions. The forest is the industry. How did we perform in aggregate, or on average? The trees are the individual credit unions. Some thrive; others struggle. Between the full forest and the individual trees lie different biomes. Within these sub-ecosystems, the trees’ performances range. States are one such biome. Some regions have stable economies that support strong growth; others are facing natural and man-made problems that challenge traditional credit union models.
We can learn more if we evaluate both the forest and the trees than if we consider only one perspective. Filtering and synthesizing different levels of analysis creates a narrative that helps individual credit unions identify strengths and weaknesses, opportunities for growth and areas to improve.
Loan Portfolio Composition by Forest Biomes
According to Callahan’s Peer-to-Peer software, first and other real estate mortgages comprise 55% of the forest’s loan portfolio. But differences in biomes make trees’ loan portfolios look different. Texas credit unions hold approximately 33% of their loans in real estate. In the Lone Star State, vehicles – new and used – make up the largest single segment at 49%. In Michigan, 57% of the loan portfolio is in real estate. Just 28% is in autos. And in California, credit unions hold 65% of their loan portfolio in mortgages.
But in our eco-analogy, varying portfolios aren’t always the result of regional differences. Asset size is another – traditional – way to classify credit unions. Do the loan portfolios of smaller credit unions differ from the larger ones? Yes. Credit unions between $50 and $100 million in assets hold 46% of their portfolio in mortgage products; credit unions with more than $1 billion hold 60% in mortgage products.
Field of Membership (FOM) is another biome. Educational, government, and community charters are…well, interestingly, not much different in terms of portfolio composition. These three FOM-based peers groups hold similar concentrations of mortgages: 53%, 53%, and 52%, respectively.
Do these classifications, which look different, perform different? Let’s carry this analogy a little further.
Delinquency: Canopy to Roots
Different parts of the credit union forest develop different asset quality. To analyze asset quality, we must introduce another dimension—time. Time is like traveling from the canopy down to the forest floor.
As of March 31, 2010, the forest’s delinquency rate was 1.77%. Compare that to the same time last year, and the picture isn’t good. Delinquency is up 35 basis points. However, a review of the quarterly numbers shows a turnaround. Delinquency actually topped out at 1.83% at year-end 2009. This trend is consistent in all of the above-described biomes except one – California.
California’s overall delinquency rose by seven basis points over the past quarter, but drilling deeper into the delinquency data shows it’s not all gloom and doom for credit unions in the Golden State. Credit card delinquency has improved 27 basis points. And delinquencies for loans not classified as real estate or credit cards, such as auto and unsecured loans, has improved 29 basis points.
Texas’ and Michigan’s delinquency looks similar, with a decline of 10 and 11 basis points respectively. And by asset size, the $50-$100M peer group decreased total delinquency by 14 basis points in first quarter 2010, while the $1B+ peer group decreased its total delinquency by just one basis point (full disclosure: a disproportionate number of credit unions in this peer group are in California).
Delinquency at government-based credit unions declined by a dramatic 15 basis points; delinquency in educational and community peer groups declined just three basis points.
Performance differences spur the questions that help frame decision making. But with that data, how do you evaluate the trees? For example, do smaller educational credit unions in Texas perform better than large community charters in California?
Use the Forest to Evaluate the Tree
So far, our discussion has ignored the more than 7,500 trees that make up the forest. These biome comparisons are composed of individual credit unions, each with different characteristics, each turning out different performances. Where does your tree fit in the forest? Callahan has a few resources to help you answer that question.
Understanding the health of the forest is an essential starting point. Watch Callahan’s quarterly Trendwatch presentation to learn how the industry performed during 1Q 2010. Our hosts provide the broader context necessary to think beyond the trees.
Biomes Within the Forest
Last year, Callahan analyst Sam Brownell wrote about how to use Peer-to-Peer software to create relevant biome groupings to analyze individual trees’ performance and strategic direction.
Interested specifically in mortgage portfolio analysis? Watch this free Power of Data webinar to learn more about creating relevant mortgage metrics, putting them in proper context, and making fair comparisons against other financial institutions.
Trees Within the Forest
Healthy, thriving trees abound in our industry, and Callahan’s quarterly journal, Credit Union Strategy & Performance, offers first-person interviews with the leaders of these institutions. Benchmark your performance using the Percentile Ranking reports—did your 2.4% membership growth earn you an A+ or C-? The numbers don’t lie. Finally, visit CreditUnions.com as every week we highlight success stories like these: Members 1st Powers through the Great Recession and Wright-Patt Fills a New Need in Auto Lending.