Predictive Analytics for Credit Union: Member Limits

In the first several posts in this series, we covered key insights that can be gathered from address changes, payroll changes, and fees as part of our “Almost 99 Small Data Hacks for Credit Unions” series. Next up, we will dive into credit union services and limits that can sometimes negatively impact your relationship with […]

How Frightened Should You Be About Amazon Banking?

By Robert McGarvey For CU 2.0 Think very – that’s the question’s answer. But maybe you already have in hand the exact weapons you need to defend your position.  Surprised?  Read on.  Triggering this discussion is a recent Snarketing post by Cornerstone Advisors’ Ron Shevlin that  offered hard data about Amazon’s potential popularity as a consumer bank.   Cornerstone had surveyed […]

Credit Union Data Analytics: What can you Learn when your Member Moves?

In our first post in this series, we covered key insights and actions you can take to turn member fees into positive, educational, and empathetic experiences for your member. This week we go even further and dive into what insights your Credit Union can learn from its data on its moving members. This is the […]

Credit Union Data Analytics: Put the Community in your Fees!

If you work for a credit union and are looking for ideas on how to leverage key data to improve your member service or overall credit union member experience, then this post is for you. This is the first post of a 9 part series. If you want the full guide “Almost 99 Credit Union […]