Why Loan Analytics are Key to Your Credit Union’s Profitability

One of the most common questions I hear thrown around is, “what is the purpose of analytics?” It’s a great question, but that’s because the answer isn’t as straightforward as it might seem.

The purpose of analytics is to solve complex problems with many variables. Analytics provide a multifaceted view of data sets. Each different view of those data sets gives a slightly different understanding of the data.

However, that answer doesn’t specify which data is being used, or for what. Here’s why that matters:

The Purpose of Analytics Changes Depending per Application
Different business units will use analytics differently. In credit unions, you may have marketers, compliance teams, loan officers, and many more all looking to get something different from an analytics solution.

In that sense, there is no exact purpose of analytics. The purpose is decided by the people who require, gather, work with, and utilize data.

And sometimes multiple business units may converge on a use for analytics. For example, loan analytics can help each group listed above: marketers, compliance teams, and loan officers.

What Are Loan Analytics?
Credit unions typically see high level data regarding their loan portfolios on their call report. You can see how many loans you have, how many are delinquent, and whether your organization is profitable.

However, what you don’t see is just as telling as what you do see. While those reports give broad overviews of loan portfolio performance, they don’t give you the best information about why your loans are performing the way they are.

Loan analytics look at the data involved in loan portfolios. They segment data as needed: by the credit tier, where the loan originated, who originated it and so on. Using this granular data, credit unions can understand which loans perform best, and why. Plus, they can see which loans underperform and why.

How to Use Loan Analytics in Your Credit Union
Let’s say that your credit union’s auto loan portfolio is your big draw. All of a sudden, you see a loss in profitability in indirect auto loans—charge off rates have spiked!

How do you respond?

  • Do you raise your rates on auto loans?
  • Do you approve fewer loans?
  • Do you ignore it, hoping that the last couple months were anomalous?

Those are all options, but none are great. If you raise your auto loan rates, then your auto loans won’t be competitive anymore. The credit union down the street will thank you as they bring in all that business.

If you approve fewer loans, the same thing may happen. Plus, you’ll probably turn away countless good loans, just to protect yourself from a few bad ones. That’s not just bad business—that’s also bad member service.

If you ignore it, then you’re figuratively sticking your head in the sand. Very few problems disappear just by ignoring them.

The trick is to use your data—after all, you already have it—to figure out why things are the way they are.

The Analytical Solution
Let’s continue that “what if” scenario above. What if you could dig deeper into the report? After all, you have the data. If you could segment the data better, you could analyze exactly which indirect auto loans are being charged off.

What would you do if you found out that your credit union’s indirect car loans were seeing high charge-off rates from one particular source? By segmenting your data better, you might find that the spike originates from

  • One or two individual dealerships
  • Members in particular credit tiers
  • Specific loan terms, e.g. those over 60 months, those without down payments

If you can identify exactly which loans are causing your spike in charge-off rates, you can quickly fix the problem. Analytics make it easy to evaluate profitability by loan segment and credit quality indicators.

It makes a lot of sense to incorporate analytics into your decision-making routine. In the above example, your credit union might stop accepting indirect auto loans from one dealer. That’s much more sensible than raising rates on all indirect auto loans.

Or, perhaps your credit union decides to raise rates for certain credit tiers instead of opting to approve fewer loans. Either way, analytics gives credit unions the opportunity to avoid implementing broad solutions for minute problems. Instead, credit unions can tailor individual portions of their loan portfolios to maximize profits while minimizing risk—all with less collateral damage.

Moving Forward with Analytics
Basically, analytics takes the guesswork out of your operations. Instead of just having the data, you’re using the data. At the end of the day, you have to ask yourself:

What kind of decisions do you want to make at your credit union?

Do you want to make uninformed decisions based on loose trends? Or would you prefer to make decisions based on hard data that offers both a bird’s-eye and granular view of things?

I always prefer decisions based on information. That’s the true purpose of analytics.

Credit union analytics—particularly loan portfolio analytics—are the key to profitability. Good, segmentable data provides credit unions with the information they need to adjust their portfolios and strategies according to historical data. Plus, with that data, they can start to predict the future.

But predictive analytics and compliance are topics for another day. Until then, just remember:

If you want to truly monitor your loans, you can’t just rely on generic reports. Credit union analytics are the key to optimizing the performance of your loan portfolio.

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