Top 8 reasons why you should know who’s earning dividends

The concept of understanding who’s earning or not earning dividends should be at the forefront of what we are doing as cooperative financial institutions to ensure that our members are getting value out of their credit union. It is great that we, as cooperative financial institutions, market that our fees and loan interest rates are lower than traditional banks, but nothing thanks a member more than providing them with cash.

We must hang our hat on the fact that we are returning profits to members and deepening our dependency on the core reason why credit unions exist, and that is to provide value to our members and participants. We must identify how we can coach members that are not earning so that they can earn, and coach members who are earning on how to continue to earn. That is the essence of credit unions as financial cooperatives.

Promoting a sense of savings within a credit union’s membership will lead to the ability for members to make larger purchases and perhaps those members will be more likely to apply for a loan with a credit union once they have a savings balance that is enough for a down payment.

Below are the top 8 reasons why credit unions should be interested in knowing who is earning dividends (and what you can accomplish through the upcoming CU*BASE Who Earned Dividends dashboard):

1. Coaching members for higher participation

By identifying members who are not earning dividends, we can coach members to participate at a higher level to ensure that they are seeing a return on their relationship with the credit union. This should be part of the train schedule for credit unions on a semi-frequent basis to ensure that members are aware of their opportunities to earn.

2. Helping members earn more

Identify members who could be earning more in dividends by suggesting an alternative product. For example, a member may be earning 1% on a savings balance when they could be earning 2% on a certificate balance. We can coach members on how to navigate their savings balance to achieve the greatest amount of return. In so doing, you promote a sense that you always have the member’s best interest at heart, and you want them to earn more.

3. Educating members on how dividends are earned

Credit unions can coach their members on how dividends are earned. I often speak with consumers (whether they be credit union members or not) and they do not understand the concept of dividends and how they are calculated. By advertising and promoting dividends and how members can earn, we can easily raise the level of advertising that we do collectively as cooperative financial institutions to prove that we are a different type of financial institution.

4. Identifying opportunities for bonus/patronage dividends

Credit unions can identify opportunities for paying bonus/patronage dividends to members. By studying which members are earning dividends and which members are not earning dividends, it allows a credit union to study which options exist for paying a bonus/patronage dividend and presents the opportunity to reward members who may not otherwise be rewarded.

5. Better informed rate change decision-making

Credit unions can closely monitor how much in dividends are being paid out to members over time. This will be helpful data for credit union management teams and board members to declare rates and perform analytics on which members would earn dividends based on a rate change.

6. Reminding members of the value they get by being a member

Credit unions can identify members who are earning dividends and remind members of what they are earning by saving money with their credit union. I do not know of any credit union that is promoting dividends any more than that the transactions are posted to members at EOM. How do we change the game so that credit unions can provide members with a greater focus of the data? We create a dashboard that easily identifies who is earning and who is not earning to bring it to the forefront of everyone’s minds.

If I were a credit union manager, I would be advertising how much I am paying to members. This data is already available on a financial statement, but as a credit union, we can get details by product, etc. that we can promote to our existing and potential members in our marketplaces. We should be telling the world what we are paying to members.

7. Deep diving the demographics of dividends

Credit unions can study/analyze what types of members are earning dividends (age, gender, zip code, etc.). This allows credit unions to isolate who is earning dividends and why. This feeds the education machine and identifies areas of the community where there may be greater opportunities for outreach and increased participation.

8. Shaping product offerings

Credit unions can identify which products they can potentially increase rates on to shift member behavior and/or retire products that do not pay dividends in favor of products that do pay dividends. If you’re a CU*BASE user, this dashboard will provide the appropriate insight to analyze these details.

How do you define “Active” and “In Good Standing”?

I was sitting in a room with nine participants from seven different credit unions across the network for our second Asterisk Intelligence week in 2018, and the audience brought up the topic of how to define an “active” member and how to define a member “in good standing”. The logical test to see if we all had a consistent approach was to go around the room and have each attendee provide us with their definitions. As you can imagine, we received multiple different answers and even some needed to refer back to their teams to discuss further.

How does your credit union define a member that is “active” and how does it vary based upon the analysis that you are performing? How do you define a member that is “in good standing” and how does that vary based upon the analysis that you are performing? Are you removing members with a deceased date from receiving your marketing material? Are you removing dormant members from your campaigns? Are members who have opted out of communications been removed from any outbound campaign/promotional materials? Is an active online banking member a member that logs in at least once a month? Twice a month? Once a week? These are the questions that we each need to answer to ensure that we are collecting and analyzing the correct data.

I suggest that credit unions define what their approach is and then create a set of rules (via the CU*BASE Report Builder tool…) that can be used for any data that is created. This helps to soothe the engine of creating data, because the credit union has already agreed upon the parameters for both what an “active” member is and what it means to be “in good standing”. This also helps to take the guesswork out of the equation when creating/analyzing data to ensure that data creation and analysis can continue on with an agreed upon routine.

P.s. Our second Asterisk Intelligence week is going great. It is a time for all types of analysts, whether they be entry-level, novice, or experts, to discuss how they are creating data today utilizing the CU*BASE Report Builder tools, CU*BASE dashboards, etc. We plan to offer 4 weeks of Asterisk Intelligence-focused training in 2019 and we hope to see you there.

Other data points to consider and why the woods may not always be filled with your trees

I have been constantly intrigued by the concept of exploring data resources that credit unions can act on. Part of this intrigue has led me to research how other industry professionals are using data and more importantly how are they analyzing the data for action. One of the documents that I recently read was “Almost 99 Credit Union Small Data Hacks Guide” ( The title in and of itself was especially intriguing because if the data hacks are small, it will be easy for all credit unions to participate with very little expense associated with the effort. The goal with the guide is to promote opportunities within your own data today and how it can be used to promote awareness and opportunity to your membership.


Some of the ideas are just no-brainers that I have never even thought of. For example, the concept of a minimum balance fee is meant to assess a fee to members who do not meet the requirements of the product. Although, it may be profitable to assess a fee to members, it may not be the wisest action. So, how about a monthly review that identifies all members that have had consecutive minimum balance fees assessed, and then reaching out to members to let them know of a product offering that better fits their lifestyle. Total no brainer. This concept utilizes data and provides an opportunity for credit unions to extend good will to their members and owners. What other fees do we assess to our members that could be reviewed for an educational opportunity? You could develop a routine for almost any fee on your fee schedule. Talking and communicating with members that have either been assessed their first fee or members that have consistently been assessed a fee is an opportunity for us all.


There was another idea that got me really excited. The idea of using data outside of your core production data to market to your members. For example, if a member request a change of address what do you do today? Do you simply just have the member fill out a change of address request or ask them to submit the request online? This could be an opportunity to use data from other places in an effort to combine that information with your member information. So, you may take the change of address information (or any new address within your database for that matter…) and then perform some research on any one of the real estate websites that exist, in order to determine what type of opportunity you could provide to the member. If the member was increasing their home size, it may mean that they are in a position to upgrade the products and services that they have with the credit union (platinum checking, platinum money market, etc.). A very simple approach that uses core production data combined with outside data sources.


Now these outside data sources may also be eventually opportunities for utilizing custom fields as well as an external data warehouse. And both of these solutions are available or soon to be available to you.


What outside data sources have you referenced or have a desire to reference for your future data analysis? Do you have a database administrator who monitors for new data opportunities?

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Yesterday’s Data? What would I do with that?

Recently, a new data warehouse was put into the hands of our Data Boot Camp participants. This new data warehouse is an exact copy of all production data as of end-of-day from the previous day. By creating a new data warehouse we are capable of not only allowing database administrators to have a new set of data to work with, but we are also increasing the amount of time that our operations team has to produce data exchanges.


What I am mostly interested in is studying how a copy of production data from yesterday can become the next greatest library for database administrators to begin dreaming up new routines to calculate insight and to promote credit union products and services. A very simple approach to study may be to look at the members balance today compared to last night and to communicate with the member. If I knew today that the members balance last night was $5,000 greater than it is today, would I have a message for this member? Or vice versa, if the members balance is $5,000 below their balance from last night, would there be a specific message for this member? This is a great new landscape for all of us to study and to understand how we can push each other to move.


In speaking with other industry experts who have created external data warehouses, one of the main goals has always been to create marketing automation routines. And in my opinion the SnapShot library is the perfect solution for this. Given that the data is produced every single day, it gives me the ability to quickly react (think punch – counter punch…). So, you may have a desire to look at all members who did something yesterday that requires an action. And that action should be a message that is conducive to the products and services you offer. Should I be communicating with members who received an ACH deposit yesterday that was greater than X dollars? And should I automate this database of members to be refreshed every single day for my marketing/outreach team to send a message?


Do you have a plan for how you will use a copy of yesterday’s data?


Should we shift our focus based on data to one that is more agile?

Recently, I returned from vacation in Florida and I spent a lot of time reflecting on the construction of our data business. I tried to soak in as many different opportunities for data that I encountered throughout my vacation, and there was no doubt that data was everywhere. One of my favorite encounters with data was at a fairly popular theme park in Orlando (the mouse’s house…). Each day my family and I went to the theme parks, and each day when we left the theme parks there was a “data gatherer” who was surveying guests as they left. After a couple of days of seeing these team members, I decided to strike up a conversation with them. As we begun chatting about the information they collect, it became apparent that one of their main goals with data collection and analysis was the ability to consistently be agile to changes in their customers.

Data agility is a concept that I became immediately fascinated with. There are millions of hits when you search for data agility on the web, so there is no doubt that this has been an important concept for data analysts, administrators, and gatherers. One of my favorite comments that I researched about data agility came from an article that I found that enlightened me to think about how we can shift and make changes in real time rather than collecting data over a period of time and then drawing conclusions or validating hypotheses. After my conversations with the “data gatherer” at the theme park, it became clear that they were shifting in one of the most simplistic manners. If park attendance was low at one of their theme parks, they would open up more opportunities (sales, campaigns, or otherwise…) to attract customers to another park. This not only helped them drive potential revenue at another park but it also helped them to balance out their crowds. This was done on the fly and in real time, simply by looking at attendance and revenue numbers throughout the day.

So how does this apply to credit unions and the data that they have at their disposal? Would a credit union be interested in a loan promotion at one branch when their loan traffic at another branch is higher than normal? Would this help them balance out their customers to the staff that were present that day? Or what if we simply realized that our daily income accrual for members at one branch was lower than expected, and we simply decided to shift our product offerings for members of that branch? The concept of a limited time sale, discount, or otherwise will shift customers in a way that was completely designed by data.

And more importantly, what services can we provide that will help our customers realize that there is an opportunity?

Does spaghetti stick to the wall?

Over the weekend, I got into my wife’s car as we were headed out to dinner, and her phone suddenly popped up a message that said we were 18 minutes from our friend’s house. But we were not going to our friend’s house, we were going out to dinner. Is it possible that the technology wrapped into my wife’s vehicle had simply made the prediction that we might be going to our friend’s house at 7 PM on a Saturday night? Whenever we do meet up with our friends, it is typically on a Saturday night and it is around 7 PM. So I was completely baffled by the fact that the technology in the car actually took a chance and had our directions pre-loaded to go to our friend’s house when in fact we were not. The technology took a chance. It was wrong, but it took a chance.

Are we taking chances with our data today? Are we taking chances with our analytics routines? As we continue on the journey of building a business about data, this is a concept we must not forget. Data will undoubtedly bring us down paths where we do not know the answer or perhaps the answer is that this group of members is the most likely to open a checking account, but there is no absolute certainty and that is ok. Taking the chance, and taking the at-bat (if you are into baseball…) is what matters most. Put yourself in the batter’s box and give yourself a chance. Put yourself in the data and send out a message. If you don’t send the message, someone else could be sending the message, or worse yet your audience may not hear your message.

What spaghetti have you recently thrown against the wall?