Data analytics’ real-world application for credit unions

In a recent survey of 700 credit union leaders, 73% of them viewed data analytics as a game-changing opportunity. However, only 26% of the respondents had a data and analytics initiative underway, 72% had trouble accessing member data, and 9% have a comprehensive plan to share analytics data with front-line employees.

Can data analytics help credit unions grow membership, deliver best in class membership experiences, manage risk, identify new business opportunities? Absolutely! And the best part is that credit unions already have so much information about their members’ financial lives and spending habits.

My colleague, Ani Majumder, a partner in the financial services division of McKinsey & Co., explained that credit unions must focus their approach. He shared a story with me about a credit union in the Midwest that used data analytics to help reduce member churn. The credit union found that of their 15% annual member growth, nearly two-thirds ended up leaving. Of those, a high number lived more than seven miles from a branch.

Further data analysis proved that the situation was actually much worse. Prior to leaving the credit union, these members would stop using other services such as credit cards or ATM withdrawals for months prior to closing their accounts, cutting down on the members’ engagement with the credit union.


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