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How To Use Data Analytics to Beat the Mega Banks

How To Use Data Analytics to Beat the Mega Banks

Providing superior service and growing membership will continue to be a top priority for credit unions. But, to compete in today’s overcrowded, competitive market, many credit unions are investing in and utilizing advanced analytics. Why? Because many of their competitors are already using big data analytics in big ways. And if they’re not yet, they’re exploring it. Consider these big data analytics investments, which can lead to big returns.


Credit unions need a strategic plan for collecting and organizing data, and a way to measure how data analytics can create long-term value. Not all individual credit unions have the resources of corporate giants or mega banks, but advances in data storage and software tools mean that credit unions can start leveraging the value of their data right away. To get started, the first step is to ensure they have the expertise, staff, budget, tools and skills (whether in-house or from an outside partner) to effectively collect, sort and act on their data.


A big data analytics program allows credit unions to create new revenue streams and resources for members, while increasing member loyalty – which makes the credit union stronger. Effectively capturing, collecting and slicing through hidden opportunities will differentiate the true winners in today’s competitive market.


Using cluster analysis of 500,000 anonymous credit union members and 250 million transactions over a five-year time frame, researchers from Filene were able to determine the next best product a credit union member would acquire with 30% accuracy. The best predictors are the balance-to-income ratio, the expense-to-income ratio and the balance of loans to savings.


60% of financial institutions in North America believe that big data analytics offers a significant competitive advantage, and 90% think that successful big data initiatives will define the winners in the future, according to Capgemini. Advanced analytics allow a better understanding of behavior trends and purchasing influences of loyal members. When armed with data about which products members are mostly likely to acquire, it takes the guesswork out of cross-sell opportunities and enables enhanced member benefits. Member service is enhanced as cross-sell efforts are more directed; the goal is to offer less and sell more.


If your credit union opts not to invest in and hire data talent, which can be costly and time consuming, specifically seek out those partners with a customized, sophisticated, yet simple analytics solution, and/or one with embedded financial institution data scientists that can share industry best practices.


Insights from data will help credit unions better manage members’ experiences and help find ways to cross-sell and develop relationship pricing for loyal members. Advanced analytics allow them to develop a metric to identify loyalty and churn risk.


Develop more effective marketing and lead generation campaigns that are targeted to the right member, with the right message at the right time. Having a system that allows credit unions to segment, manage and track specific actions will enhance their marketing ROI. Analytics allow them to determine which marketing campaigns and segmented audiences are the most responsive and effective today and in the future.


Enhance risk and fraud management by easily and quickly spotting pattern changes that are an indicator of potential risk. Predict a member’s risk of defaulting or becoming delinquent on one or more loans.

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