Credit Union Membership Increased by Data Mining

I am speaking on Friday May 18th, 2018 in Savannah, GA at the National Credit Union Conference for Directors and Senior Management.  My session topic in on how to use predictive analytics to leverage your data to increase membership and revenue.   For financial institutions, the ability to determine cross selling and targeted marketing campaigns can be achieved by leveraging the data you already have.  In this session I leverage multiple technologies to put together a complete picture of member behavior, location and impact.  The image below (for my fictional credit union) shows how many members live in each postal code along with the opportunity of households in postal code.  This type of report can help you focus on areas to increase or decrease marketing to gain membership.

Credit Union Member Penetration by Zipcode

Credit Union Member Penetration by Zipcode

Session Abstract:

Predictive Analytics can provide credit unions with a valuable tool to create actionable insights by mining their data assets.
Credit unions that embrace this technology can increase revenue, decrease cost and improve services. Derek will walk
you through examples using two common patterns: cross selling members and determining target members for email or
direct mail campaigns. By the end of the session you will have foundational knowledge of how predictive analytics can be
applied to your credit union problems.  By using data you can increase membership and revenue.

● How can data mining and predictive analytics improve my business?
● What are some common use cases for predictive analytics?
● How do you get started with predictive analytics?

 

CU Conferences Link

 

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