How Predictive Analytics Can Slow Member Attrition

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ROHNERT PARK, Calif.–There are several reasons why credit unions should be concerned about the rate of member attrition in the next few years, asserts one analyst.

Karan Bhalla, managing director at data analytics firm IQR Consulting, said consumer profiles are changing—with the children of aging members today not as likely to follow in the financial footsteps of their parents. Moreover, the rise of digital self-service banking tools threatens to lessen the value of the personal relationship in the minds of many consumers.

“Though member attrition is a familiar problem for credit unions, these factors are expected to intensify this issue over the coming years,” said Bhalla.

The most effective strategy to help CUs reduce member attrition, said Bhalla, can be found in the increasing availability—and resulting use—of predictive analytics.

“This can be an ideal solution for many credit unions looking to change the course of the typical member journey,” he said. “Analytics were previously only available to the largest, most sophisticated mega banks. Now these tools are within reach for smaller financial institutions. In 2017 we will see more community-based organizations, including credit unions, begin to integrate these technologies, hire the right people and build out the necessary infrastructure to power data-driven member retention capabilities.”

Bhalla said the right data strategy can predict which members are most likely to leave the credit union in the near future. He said “member churn analysis” can identify triggers in buying behaviors that pinpoint which members have the highest chances of drifting away.

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Karan Bhalla

“The resulting predictive models help marketers and other business development professionals develop hyper-personalized, relevant marketing offers to those most at risk of going elsewhere,” he said. “More importantly, the models illuminate areas where the credit union may be failing to meet the needs of a changing consumer profile.”

Bhalla asserted that the issue of loyal members looking elsewhere for their financial services can sometimes be a “touchy subject” to address with CU leaders and boards who are passionate about their credit union—which can often lead to wrong conclusions about the ability of the CU to retain, loyal and profitable members.

“Performing an in-depth analysis of factors impacting member attrition helps decision-makers get real insights into member values, needs, preferences and goals for the future,” said Bhalla. “With this information, credit unions can then formulate effective strategies to better engage members with the brand and ultimately stop them from turning to competitors.”

Section: Standard
Word Count: 537
Copyright Holder: CUToday.info
Copyright Year: 2018
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URL: http://www.cutoday.info/THE-boost/How-Predictive-Analytics-Can-Slow-Member-Attrition