4 Ways To Personalize Benchmarking Strategies

How to re-examine traditional benchmarking metrics and truly tell the credit union’s story.

 
 

Every credit union has a story to tell, and different credit unions need different tools in order to best tell their story.  A credit union that serves factory workers in Florida has a different story, and needs different tools, than one that servers farmers in Iowa. If a credit union measures its performance and success against a broad set of standards, the results are helpful only to a point. Instead, credit unions need to personalize their benchmarking strategy according to two central questions: 1) How do we know if our credit union is performing well? 2) What metrics should we use to gauge our effectiveness?

Metrics such as average member relationship, member per employee, return on assets, and the efficiency ratio help credit union leaders evaluate an institution’s performance, set goals, and benchmark success (read more about those metrics in 4 Ways To Benchmark Credit Union Performance). But to make the best decisions for the credit union, leaders also need to understand the context in which their credit union operates. After all, context is everything, and details such as size, location, membership profile, and operating model provide just that.

Size Matters

A comparison between a $200 million credit union and a $2 billion credit union isn’t likely to yield helpful results, even if the two institutions share the same market. Economies of scale and resources vary greatly depending on the size of the institution, so leaders must account for the institution’s asset size as well as number of members.

For example, Western Valley Federal Credit Union ($10.3M, Sacramento, CA) posted a return on assets of 0.33% in 2013. Compare that to the 0.85% average ROA for all credit unions in the United States and it appears Western Valley is underperforming. However, compare Western Valley to the 0.20% average ROA of credit unions with $10 million to $20 million in assets and it becomes clear that the credit union earns a decent return for its size.

RETURN ON ASSETS (PRE-ASSESSMENT)
Data as of December 31, 2013
© Callahan & Associates | www.creditunions.com

WesternValley

Source: Peer-to-Peer Analytics by Callahan & Associates

Location, Location, Location

A good credit union for a peer comparison isn’t just one that falls into a certain asset class, though. Credit unions should also benchmark their performance against credit unions in similar locations.

For example, JM Associates Federal Credit Union ($98.6M) in Jacksonville, FL, has a higher delinquent loan ratio compared to the national credit union average — 1.23% versus 1%, respectively. However, Floridians have had an especially tough time during the recession, so JM Associates’ might be better off assessing its delinquency rate alongside other institutions from the Sunshine State. With that kind of context, JM Associates’ performance is clearer. In fact, the institution’s 1.23% delinquency rate is 23 basis points lower than the 1.46% average for all Florida credit unions.

DELINQUENCY RATIO
Data as of December 31, 2013
© Callahan & Associates | www.creditunions.com

JMAssociates

Source: Peer-to-Peer Analytics by Callahan & Associates

Establish A Solid Foundation

Understanding the factors that influence your ratios and the potential drawback of using one over another is critical. Read about the pros and cons of four basic benchmarks to learn what questions to ask in different situations.

READ MORE

 


Know The Member

If credit unions are supposed to serve their members first and foremost, then they need to understand who their members are. Members are one of the most important elements to consider when benchmarking goals and comparing institutions. This is especially true for SEG-based institutions. If a sponsoring company is forced to make widespread layoffs, those layoffs will likely affect credit union performance.

Likewise, it is important for credit unions to know when other institutions that serve the same industry are thriving or struggling. That kind of context helps credit unions tell their own story.

For example, Southwest Airlines Federal Credit Union ($307.1M, Dallas, TX) is well above the industry average in annual loan growth. In fourth quarter 2013, it posted a 12.8% compared to 7.9% for all credit unions. But its success is even more profound in the context of transportation credit unions, which as a whole posted a slightly lower YOY growth, 7.6%, than credit unions nationally.

ANNUAL LOAN GROWTH
Data as of December 31, 2013
© Callahan & Associates | www.creditunions.com

Southwest

Source: Peer-to-Peer Analytics by Callahan & Associates

Different Operational Models, Different Outcomes

Credit union memberships are as distinct as the individuals that comprise them. Some groups prefer email, some prefer snail mail. Some groups want branches with convenient hours and helpful tellers, others want advanced mobile offerings. Because of this, executives should not apply a blanket comparison to operating expenses.

For example, the 4.61% operating expense ratio of Frankenmuth Credit Union ($292.1M, Frankenmuth, MI) looks high when compared to the 3.59% average operating expense ratio of credit unions in its asset-based peer group of $250 million to $500 million. But Frankenmuth isn’t like other credit unions in its asset size. It has 17 branch locations, and a deeper dig into institutions with a similar asset size and branch footprint, 15 or more, shows Frankenmuth’s operative expense are actually slightly lower than peers.

OPERATING EXPENSE RATIO
Data as of December 31, 2013
© Callahan & Associates | www.creditunions.com

Frankenmuth

Source: Peer-to-Peer Analytics by Callahan & Associates

Establish A Solid Foundation

Understanding the factors that influence your ratios and the potential drawback of using one over another is critical. Read about the pros and cons of four basic benchmarks to learn what questions to ask in different situations.

READ MORE