Data analytics for personalized financial education
The opportunity for credit unions to give better financial guidance to members is hidden in a deep “data ocean”
by: Nate Wentzlaff
Credit unions store massive amounts of data on detailed aspects of members’ lives. Spending trends, loans, investments and savings are just some examples of data being collected by credit unions. This data is always changing as members move through their financial lifecycle. From prospective college students preparing for their first semester to retirees, credit unions have a wide range of membership. Educating members according to their current lifecycle stage is crucial to developing deeper relationships. By utilizing data analytics solutions, credit unions are now better equipped to provide education that is tailored to each member’s unique financial situation.
Member-Centric Data Model
The amount of data residing within credit unions is growing exponentially. With a massive “data ocean” stored throughout various source systems, credit unions must be purposeful when integrating these systems to discover information about their members. All data integration should be on a member-centric model. Designing a data warehouse with the member as its centerpiece is critical for the development of data analytics solutions. Every data model must be built with one object as its main focus, for credit unions, this object is the member. A data model built around the member will provide opportunities for financial education that is focused on the individual. A member’s relationship with their credit union is more delicate than ever. With an abundance of financial product alternatives, developing and maintaining relationships with members is essential for the future of the credit union industry. The member-centric data model is the foundation for credit union data analytics.
Personal Financial Management (PFM)
Once data analytics solutions have been built from a member-centric data model, financial education apps can be developed to form a PFM tool. Currently, members (especially younger ones) are reluctant to attend classes or presentations at physical locations. The new style of education is online and mobile. As members utilize this PFM tool, they will develop a habit of utilizing it when making financial decisions. By providing guidance based on members’ current data, credit unions will be able to guide them in financial decision-making. Also, marketing campaigns (webinars, training sessions, articles, etc.) can be strategically focused on members based on the current stage of their financial journey. Sending a retiree the latest student loan webinar will not be an effective use of marketing resources and results in a damaged relationship with that member. With member-centric data analytics solutions and a PFM tool, credit unions can further customize their educational guidance to each member. The ability to track financial data is desired by most members. They want to know what is going on in their financial situation on a daily basis. Allowing members to navigate, with their credit union as a co-pilot, is a powerful capability for credit unions willing to invest in data analytics solutions.
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