The Credit Union Data Analytics 2.0 Provider Guide
Want to do something with your data, but don’t know where to start? Start here and use code “CU 2.0” for a discount. Credit unions often lag competitors, technologically. Technological needs must be balanced with service, growth, and profit; often, those needs compete with fintechs, compliance, IT security, and ever-changing regulations.
Questions to Ask Data Analytics Providers (for Credit Unions)
There are many different uses for data analytics at credit unions. And, it seems, there are as many data analytics providers as there are uses. We believe this is a good thing. However, we understand that the plethora of vendors can make it hard to find the right one. Moreover, even reviewing our data analytics […]
How Data Analytics Can Improve Interchange Income
Non-interest income is an oft-neglected part of a credit union’s total income. And it makes sense, too—revenue from loan interest is generally lower, and it flies under the radar. But what if you could increase interchange income? Would non-interest income still play second fiddle? Or would you pursue a program that could increase your profits […]
Credit Union Data Analytics: Who are your best members? :)
Our “A” members are the ones who know the difference between a credit union and a bank, believe it, feel it, and espouse it. They bring us all of their financial services business and tell all their friends. If you are interested in what their data tells you about them then this post in Credit […]
Credit Union Data Analytics: Who are your best members?
Our “A” members are the ones who know the difference between a credit union and a bank, believe it, feel it, and espouse it. They bring us all of their financial services business and tell all their friends. If you are interested in what credit union data analytics tells you about them then this post […]
Credit Union Data Analytics: How do you know your member is about to leave you? :(
If you work for a credit union and are looking for ideas on how to stem attrition or member loss, then this post is for you. This blog is part eight in Credit Union 2.0’s “Almost 99 Small Data Credit Union hacks” series and is based on the book Credit Union 2.0 – A Guide for […]
Credit Union Data Analytics: Wallet Share
We only have a couple of posts left – but don’t fret – we have saved some of our best content for the end of our Almost 99 Small Data Hacks for Credit Unions – Guide series. Today, we are covering how to gain wallet share for your credit union from data analytics. Who doesn’t want […]
Credit Union Data Analytics: Common Error Avoidance
Now that we are more than halfway through our Almost 99 Small Data Hacks for Credit Unions – Guide series, it is time to switch gears a bit. This post features hacks that are entirely focused on expense savings. One credit union I worked at would survey its members regularly. The common sentiment was that the […]
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 […]