As consumers leave behind a trail of data as they digitallywander through life, credit unions are realizing they need to watchthese signs closely so they can stay a step aheadof banks in offering loans or services.

And, like any other complicated task beyond the means of mostcredit unions, CUSOs are stepping up to help credit unions linktheir private pools of data to the greater world of big data.

CUSOs from CU Direct of Ontario, Calif., to CUNA MutualAdvantEdge Analytics of Madison, Wis., are helping credit unionscreate methods to collect, interpret and act on the information inregular, timely manner.

AdvantEdge Analytics' parent, CUNA Mutual Group, has beenproviding insurance to credit unions for more than 80 years, and itnow serves about 95% of the nation's credit unions.

“Being that we're an insurance company, we have analytics in ourDNA,” said Tim Peterson, AdvantEdge Analytics' president. “We have80 years of history knowing how to assess risk and price risk, and30 years' experience with direct marketing.”

Providing the analytical models and insights from the models isat the base of their work, but the most valuable step is helpingcredit unions use the information to form and execute businessplans, Peterson said.

“There are lots of tools out there,” Peterson said. “But helpingcredit unions act upon the insights — that's where we see a prettysignificant gap, a pretty significant opportunity.”

First Service Credit Union ($671.7 million in assets, 56,669members) is in the early stages of using big data to targetindividuals for product offerings. The Houston credit union expectsthe data to provide advantages that will allow the credit union togain market share so it can remain viable in a competitive market,EVP Mike McWethy said.

“Survival in today's market requires achieving economies ofscale through growth,” McWethy said.

Achieving growth requires more effort because consumers want personalized offers timed to their needs andoffering them the means to act whether online, on the phone or inperson. Typical “shot-gun” blasting of advertising does not bringthe same return on investment as targeting messages to candidateslikely to qualify, McWethy said.

The credit union discovered this several years ago when itstarted pre-screening for auto refinance candidates and drivingthose consumers to a specific, single-product-focusedmicrosite.

“We still love being the relational, fun-loving, hand-shakingcredit union,” he said, “but we have to realize selling loan anddeposit products is what allows our survival, so we must becomemore sophisticated at it.”

Michael Cochrum, CU Direct's vice president of analytics andadvisory services, said credit unions have been developing theirabilities over the decade to handle data past, present andfuture:

Telling the story of the past. “Credit unionshave gotten good at analyzing past performance of loans,” Cochrumsaid.

Measuring the present condition. Credit unionsare increasing deploying software and hiring consulting services totrack aspects of their business, such as loan portfolio risks.

Predicting the future.Predictive analytics are especially useful for pricing loan ratesand targeting customers, but very few credit unions are using thesetools.

Measuring the present is often seen in the way credit unionsvalue their collateral in a car loan portfolio. Instead of assuminga consistent depreciation rate across the portfolio, credit unionscan tap into data on the resale value of each car by make, modeland year. The information can be updated as often as the creditunion wants.

Whether car collateral values are estimated by a formula appliedto the entire portfolio or based on actual one-to-one book valuesoften depends on the extent of risk of falling values.

“If your portfolio is weighted heavily in trucks and SUVsbecause of the demographics of your membership, it's probably notas important because they don't depreciate as fast. If they'reweighted more in sedans, you're at greater risk because thosevehicles tend to depreciate faster.”

Predicting good customer targets and matching them to the rightloan is trickier.

CU Direct has been working with credit unions to set up dynamicpricing. Instead of basing a rate on credit score and the length ofthe loan, they can help credit unions price based on the predictedprofitability of the loan, taking into account loan-to-value, andability to repay based on their current financial situation.

“Instead of offering every product to every member, they'reoffering the right product to the right member at the right cost,”Cochrum said.

Credit scores are not enough because credit score is a predictorof default at a point in time.

“It's almost exactly like a weather forecast: It's going to bemore accurate the closer you are to the storm actually occurring,”Cochrum said. “Credit unions are beginning to realize that creditscore at origination changes dramatically throughout the life ofthe loan.”

The next step is for credit unions to use big data.

Big data doesn't mean a lot of data. It means tapping sourcesoutside the credit union and linking it to members, Cochrum said.For example, it could mean studying Facebook “Likes” or othersocial media trends to see if there are ways to better identifymembers who might prefer certain products.

Is it creepy?

“I don't find it creepy at all,” Cochrum said. “My wife thoughtit was creepy that she could see on Facebook which of her friendswere close by. I told her all she had to do was turn off herlocation services.”

Cochrum, who described himself as a “fairly prolific socialmedia user,” said he would rather have someone from his creditunion call him based on social media data that indicated he hadrecently been promoted, than to have the credit union send him aflyer in the mail advertising rates on CDs that he doesn'twant.

“I'm kind of appreciative of people who use data and analyze mybehavior so they're serving up offers that are important to me, andI'm not seeing offers that don't apply to me,” he said. “If youapproach it correctly and not overdo it, there's a real benefit toyour membership when you're targeting them better.”

CUNA Mutual AdvantEdge Analytics sees itsmission as helping credit unions organize, translate and act oninformation.

Before announcing its launch of AdvantEdge Analytics in May,CUNA Mutual enlisted the help of the McKinsey & Companymanagement consulting firm “to uncover the next-generationanalytics,” Peterson said.

The CUSO met with more than 400 credit union executives andsurveyed another 400 credit unions. It hosted four-hour “deep dive”strategy workshops at credit unions about how to launch this newbusiness.

“We've been heads-down researching this with our customers,”Peterson said. “It helped us hit the ground running.”

AdvantEdge Analytics can leverage talents from within the 3,500employees of its CUNA Mutual parent. But among them, 500 people arededicated to the subsidiary as data developers, data scientists,data translators, implementation specialists and other roles.

CUNA Mutual had the foundation of resources it needed, but itwas also looking outside for innovators. In February, it spent anundisclosed amount to buy SavvyIntel, a Chicago-based dataanalytics company. Blesson Abraham, its CEO, had worked for BaxterCredit Union, based in Vernon Hills, Ill., 35 miles northwest ofChicago, for five years before co-founding SavvyIntel in 2014. Heis now AdvantEdge Analytics' director of analytics.

SavvyIntel enhanced the reporting capabilities of the AdvantEdgeAnalytics product suite that CUNA Mutual developed in 2016. Thesoftware is designed to allow credit unions to draw from a deeperpool of data from a wider array of sources than an individualcredit union's resources would normally allow.

The CUSO can manage call center and email marketing. It canprovide back-office fulfillment and build-to-order services.

“Rather than casting a lead for a loan off to a credit union, wework further in that process, proving the service to actually closethe loan on their behalf,” Peterson said.

One need AdvantEdge Analytics fills is helping credit unionsfind new members and identifying which members might be at risk ofleaving.

“Every credit union will tell you they can bring in members;their challenge is identifying and keeping high-value members,”Abraham said.

Another need is housekeeping. AdvantEdge Analytics helps set upsystems for credit unions to organize data and import data into aunified environment, where it can be compared with third-partydata.

The CUSO also helps set up systems to maintain data integrityand the quality of reports, visuals, dashboards and performancemetrics.

“Once they're ready, we help them with that predictive piece aswell,” Abraham said.

AdvantEdge Analytics buys big data from Acxiom, Experian,Epsilon and other venders to help credit unions discern demographicpatterns of members, how many members in the household, the typesof goods they purchase and where they buy them.

“External data can get pretty expensive,” Peterson said.“Collaboration is really key across credit unions. One role we canplay is to be a facilitator in that collaboration by leveraging ourscale to bring value.”