Getting Your Data In Order – A Recipe for Credit Union Digital Transformation

credit union digitial transformationData is fundamental to your credit union digital transformation. Customers must be able to efficiently and effectively manage transactions online. Credit Unions must be able to infer customer needs from those transactions and reach out to customers where they “live” online, whether through email, social media, or text. This blog post presents a simple recipe for getting your data in order as a foundation for digital success.

Step 1 – Unload the data you don’t need. 

Credit Unions tend to hold onto data forever, or at least long enough that it can become a problem. It is common for core systems to have database tables with hundreds of millions of transactional entries and years more data than needed for most operational needs.

Why? Fear of removing data? The effort to replace the data if you get it wrong?

Who tested that purge script anyway?

Shhhh. Is, “Don’t ask, don’t tell,” your data management policy?

OK, we all know that removing data isn’t on the list of critically important tasks, well, until it is. Removing data can make the overall management of your information system easier! Backups are smaller, and systems may run faster due to the smaller size of the database. It’s just less to manage.

The good news is that removing data, although challenging can be automated.


Step 2 – Clean the data you keep – for credit union digital transformation

Managing data in bulk is usually handled by IT teams. Managing data quality so your digital journey can be smoother is a front-line staff opportunity. The dirtier our data is the more each activity we want to embark upon causes exceptions. Having clean data reduces effort and increases performance by eliminating exception conditions.

How does data get dirty?

For example, complex core interfaces allow data entry errors to go unchecked and bulk imported data from a merger. I am sure you have other examples of where the data can and does go astray. Some kinds of data can be validated with scripts and tools, however, technology can’t fix all data problems.


Step 3 – Focus on data that supports digital engagement.

Ensuring the quality of member data like current email address and mobile telephone numbers is critically important for successful digital engagement with our members. It is important that names are correctly spelled, and that staff know how to pronounce names when they speak with a customer in person or on the phone.

Mapping member data help the selection criteria for digital campaigns, if your digital persona is a working woman who is the “CFO” of the household, you quickly realize that knowing whether your member is male or female is fundamental.

Do you have a report showing what percentage of your membership has an email in your system, a mobile phone number? This number is the upper limit of members your campaigns are able to address digitally.


Step 4 – For better member data, engage your members.

It takes time and effort to correct member data, and many Credit Unions are unwilling to ask members without some other offer or campaign. One option is to engage directly with your members to make sure their information is up to date. Train member service staff to pay attention to member data at every customer interaction. If key member information is absent or hasn’t been updated recently, have them ask members for updates.

The better the quality of your data, the easier your path will be to creating and managing the digital transformation.

 

Want to read more on digital transformation?

On the Digital Transformation Journey with Partners FCU’s CEO

Digital Transformation and the Old Fashioned Con

5 Lessons Learned from AXFI 2018

This week I had the honor of speaking at the 2018 AXFI (Analytics and Financial Innovation) Conference for Credit Unions in Minneapolis. I spoke on the Credit Union 2.0 DREAM methodology. First off, this is a great event that attracts an abundant group of Credit Union thinkers, innovators, and has truly great content. Here are the top five takeaways that I learned at this event!

  1. Artificial Intelligence is coming. We cannot hide from this. There were several great presenters including Lendified and Active.AI. We are starting to see a large number of ANI (artificial narrow intelligence) solutions hit the ground on things like small business loan underwriting, assessing credit risk, and chatbots that communicate with your members in their language.
  2. Rate Reset’s new product “Knock Knock” is winning solution competitions at tons of shows. After taking the NACUSO Next Big Idea award 6 weeks ago, Rate Reset wowed the Killer Fintech Speed Rounds at AXFI with its ability to retain existing members and products while also providing a great digital engagement experience for new member product offers.
  3. John Best of BIG demonstrated and taught how to use CU Ledger. Credit Union programmers went through two workshops and got to see firsthand how block chain technology can help credit unions secure their member identities while providing a better experience.
  4. The OnApproach Data Analytics platform is really driving innovation. There were numerous sessions where data scientists showcased great collaborative solutions for problems from CECL, member profitability, Data Lakes, to when members might be leaving. Both the collaborative environment as well as the large number of solution providers on the platform really showcased the power of CUSOs and teamwork.
  5. Analytics has a role in Cyber Security as well. Bob Miles, CISO Practice Manager, from Ongoing Operations, LLC, demonstrated key strategies and tools to find key member information on your platform, measure the risk, and help quantify and prioritize cyber tasks so that your Credit Union can minimize any potential impact from a hack or cyber event.

Overall, the AXFI conference is a terrific conference that delivers key technology strategy with hands on tactics for the industry. It attracts innovative thinkers in the industry and provides cutting edge content.

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 Union 2.0’s “Almost 99 Small Data Credit Union Hacks” series will be helpful.

This blog is the ninth and final part 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 Helping Credit Unions Compete in the Digital Age which covers in depth both big and small data for credit unions. There are six types of data that your Credit Union should be aware of:

  1. Digital Analytics – Desire
  2. Profitability – Fit
  3. Wallet Share – Depth
  4. Transaction – Triggers
  5. Design Data – Predictive
  6. Execution – IFTT (if this than that)

The key here is patterns. Once you sniff out the predictive behavior, you can be proactive with how you interact with the member.

Here are some ideas on where to look for your “A” member patterns:

Data What to do with it?
Favorite Grocery Store Special promotion with that store
Favorite Vehicle Special promotion with the local auto dealer
Favorite Coffee Shop Hang out there too – send them a cup on you!
Favorite Online Retailer Special Promotion
Favorite Local Small Merchant Hang out there too
Favorite Gym Special Credit Union deal
Who They Follow on Facebook Could this be a potential guest blogger on your site? Maybe there is an opportunity for you to update your content to be more relevant.
Where They Work Follow their leadership online
When They go to Branches Better service hours
Who Their Favorite Tellers/Call Center Reps Are Understand why
What Life Stage They are at What is next for them and how can you help?

 

Knowing your “A” members inside and out and further tailoring your services will help those members bring their friends. You want your “A” members fiercely loyal and believing in the credit union difference. Show those members the difference every day and hang out with them and their friends.

Want to learn more about how your fellow Credit Union leaders are using data? We invite you to join our Credit Union 2.0 Strategist Group where over one thousand industry leaders comment on new news and trends while sharing and learning from one another.

This is the final post in a nine part series. If you want the full “Almost 99 Credit Union Small Data Hacks Guide” click here!

In case you missed it:

Click here for part one of the data analytics series.

Click here for part two of the data analytics series.

Click here for part three of the data analytics series.

Click here for part four of the data analytics series.

Click here for part five of the data analytics series.

Click here for part six of the data analytics series. 

Click here for part seven of the data analytics series. 

Click here for part eight of the data analytics series. 

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 in Credit Union 2.0’s “Almost 99 Small Data Credit Union Hacks” series will be helpful.

This blog is the ninth and final part 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 Helping Credit Unions Compete in the Digital Age which covers in depth both big and small data for credit unions. There are six types of data that your Credit Union should be aware of:

  1. Digital Analytics – Desire
  2. Profitability – Fit
  3. Wallet Share – Depth
  4. Transaction – Triggers
  5. Design Data – Predictive
  6. Execution – IFTT (if this than that)

The key here is patterns. Once you sniff out the predictive behavior, you can be proactive with how you interact with the member.

Here are some ideas on where to look for your “A” member patterns:

Credit Union Data Analytics Patterns

Data What to do with it?
Favorite Grocery Store Special promotion with that store
Favorite Vehicle Special promotion with the local auto dealer
Favorite Coffee Shop Hang out there too – send them a cup on you!
Favorite Online Retailer Special Promotion
Favorite Local Small Merchant Hang out there too
Favorite Gym Special Credit Union deal
Who They Follow on Facebook Could this be a potential guest blogger on your site? Maybe there is an opportunity for you to update your content to be more relevant.
Where They Work Follow their leadership online
When They go to Branches Better service hours
Who Their Favorite Tellers/Call Center Reps Are Understand why
What Life Stage They are at What is next for them and how can you help?

 Credit Union Data Analytics: A Members

Knowing your “A” members inside and out and further tailoring your services will help those members bring their friends. You want your “A” members fiercely loyal and believing in the credit union difference. Show those members the difference every day and hang out with them and their friends.

Want to learn more about how your fellow Credit Union leaders are using data? We invite you to join our Credit Union 2.0 Strategist Group where over one thousand industry leaders comment on new news and trends while sharing and learning from one another.

This is the final post in a nine part series. If you can’t wait for next week and want the full “Almost 99 Credit Union Small Data Hacks Guide” click here!

In case you missed it:

Click here for part one of the data analytics series.

Click here for part two of the data analytics series.

Click here for part three of the data analytics series.

Click here for part four of the data analytics series.

Click here for part five of the data analytics series.

Click here for part six of the data analytics series. 

Click here for part seven of the data analytics series. 

Click here for part eight of the data analytics series. 

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 Helping Credit Unions Compete in the Digital Age which covers in depth both big and small data for credit unions. There are six types of data that your Credit Union should be aware of:

  1. Digital Analytics – Desire
  2. Profitability – Fit
  3. Wallet Share – Depth
  4. Transaction – Triggers
  5. Design Data – Predictive
  6. Execution – IFTT (if this than that)

Sometimes members give us very subtle clues that they are moving on. Here are a few key actions to be watching for:

What the member does? What it means?
Reduce bill pay items by more than 25% Moving over to somewhere else
Credit Card activity stops one month New Credit Card
Member stops logging into online banking No longer the PFI
Member doesn’t order new checks Moving soon and not planning on taking you along
Member doesn’t get a new car loan from you and pays off the old Found a better deal
Payroll declines or disappears entirely Switching accounts
Checking account activity declines in volume Switching accounts
Have more to add? Email info@cu-2.com and help us improve this post!

 

If you pay attention to the warning signs, you may be able to save the membership and get the member engaged again. Credit Unions spend over $200 for each new member, however most problems are way less expensive to solve for a current member and require a lot less labor.

Want to learn more about how your fellow Credit Union leaders are using data? We invite you to join our Credit Union 2.0 Strategist Group where over one thousand industry leaders comment on new news and trends while sharing and learning from one another.

This is the eigth post in a nine part series. If you can’t wait for next week and want the full “Almost 99 Credit Union Small Data Hacks Guide” click here!

In case you missed it:

Click here for part one of the data analytics series.

Click here for part two of the data analytics series.

Click here for part three of the data analytics series.

Click here for part four of the data analytics series.

Click here for part five of the data analytics series.

Click here for part six of the data analytics series. 

Click here for part seven of the data analytics series. 

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 that?

Credit Union 2.0 – A Guide for Helping Credit Unions Compete in the Digital Age covers in depth both big and small data for credit unions. There are six types of data that your Credit Union should be aware of:

  1. Digital Analytics – Desire
  2. Profitability – Fit
  3. Wallet Share – Depth
  4. Transaction – Triggers
  5. Design Data – Predictive
  6. Execution – IFTT (if this than that)

This is a fun list with lots of innovate ways to trigger marketing campaigns once you have your marketing automation and content marketing in place.

Idea Data Action
Big Deposit Grooming Watch for unusually large deposits ($25k+) Develop a content campaign on key strategies to deal with new money. The strategy should be 5 to 10 blogs long and drive for a Call To Action (CTA) to download the guide. Once you see the deposit, start emailing the member weekly with one blog each week on the topic.
Loan Renewal 24 month Auto Loan Triggers a new content campaign on educational topics such as: maintenance requirements for older cars, when to trade your car in, how to determine your cars trade in value, etc.  Have 5 to 10 blogs targeting the goal of educating the member and renewing the loan!
Address Change When a member changes address Trigger an offer to order new checks
Venmo Usage Watch for the first Venmo usage Trigger a campaign on pros and cons of Venmo. Alternatives to Venmo.  Etc.
PayPal Usage Watch for the first PayPal usage Trigger a campaign on these various topics: pros and cons of PayPal, PayPal security vs. Credit Union Security, and the difference between PayPal and a credit union.
Bitcoin Usage Watch for the first Bitcoin usage Trigger a campaign on pros and cons of Bitcoin.  Educational piece on Bitcoin and how it works.
Low Balance Savings/Checking Low Balance Offer a skip a pay option that month for a fee and donate a portion to a local charity.
Pricing Auto price loans .25 points higher On the third consecutive good payment, send an email thanking the member and auto reduce the payment .25%.  This is a great built in surprise!
Rewards Monitor reward tiers on debit/credit Auto trigger outbound emails when the member hits new rewards tiers and options.
Tax Refunds When a one-time tax refund is deposited Trigger outbound content on key strategies for tax refunds, i.e. the impact of saving your tax refunds, what would your tax refund be worth if you saved it for thirty years at a credit union, etc.
Local Merchants Top usage and dollars locally Look at your members local purchase habits.  Create unique rewards where they already shop at local businesses.

a.       Ford – free car wash

b.       Coffee Shop – free cup of coffee

c.       Flower store – coupon

d.       Dry Cleaner – coupon

e.       Theatre (movie or otherwise) – free popcorn

f.        Kids Gym or activity – coupon for a class or session

g.       Home decoration store – special offer

h.       Home improvement store – coupon

i.         Gas Station – a fill up on us

j.         Grocery store – special offer

 

ATM Set the preference ·       Language

·       No Receipt

·       Last Deposit

·       Last Withdrawal

Credit Card Offer timing Other bank credit card payment date Most members pay their credit cards within the same 3 to 5 day window each month. Time credit card switch and educational content to when payments are due for each member.
Credit Card Purchase Subscription Data Members who aren’t using the credit union’s credit card should be offered an incentive to move recurring payments over.
Joint Member Added Look up wedding registry Send a congratulations gift or item from their registry. Follow-up with credit union guide to budgeting for newlyweds etc. It might also be a time where the couple begins looking for a house.
DMV Charge Watch for a local DMV payment Trigger information on how to change your address or other life stage events.

We are getting down to the end of the “Almost 99 Small Data Credit Union hacks” guide. The next two posts will be on “how to tell a member is leaving” and “how to get more “A” members” so stay tuned!

Want to learn more about how your fellow Credit Union leaders are using data? We invite you to join our Credit Union 2.0 Strategist Group where over one thousand industry leaders comment on new news and trends while sharing and learning from one another.

This is the seventh post in a 9 part series. If you can’t wait for next week and want the full “Almost 99 Credit Union Small Data Hacks Guide” click here!

In case you missed it:

Click here for part one of the data analytics series.

Click here for part two of the data analytics series.

Click here for part three of the data analytics series.

Click here for part four of the data analytics series.

Click here for part five of the data analytics series.

Click here for part six of the data analytics series. 

 

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 posts 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 credit union is great, and despite making lots of mistakes, they always fixed them. Sometimes mistakes can actually lead to good things, but in today’s world of fintech and automation, mistakes can also be infuriating.

This is the sixth post in a nine part series. If you can’t wait for next week and want the full “Almost 99 Credit Union Small Data Hacks Guide” click here!

Credit Union 2.0 – A Guide for Helping Credit Unions Compete in the Digital Age covers in depth both big and small data for credit unions. There are six types of data that your Credit Union should be aware of:

  1. Digital Analytics – Desire
  2. Profitability – Fit
  3. Wallet Share – Depth
  4. Transaction – Triggers
  5. Design Data – Predictive
  6. Execution – IFTT (if this than that)

Data Analytics can help us see where our mistakes are occurring and how to proactively fix them before we risk repeating them over and over and infuriating our members.

Mistake Pain Action Plan
Sometimes our loan officers enter the wrong rate The member may not notice for a while, and it will take a lot of work to unwind and leave a bad taste. Run a report monthly of loans by interest rate. Sort by High and Low rates. You should quickly see if there are any incorrect rates. This then can be quickly fixed before it is painful for the member.
Sometimes our member service reps enter the wrong rate The member may not notice for a while, and it will take a lot of work to unwind and leave a bad taste. Run a report monthly of loans by interest rate. Sort by High and Low rates. You should quickly see if there are any incorrect rates. This then can be quickly fixed before it is painful for the member.
Broken Links Members click on link on your website that is dead. Once a month test the website links and make sure they are working.
Franken Forms When a member fills out an electronic form and information is sent to the abyss. Test your forms on your website and make sure you have a mapping of where the data goes and who is using it.
Monthly Subscriptions Sometimes companies like Netflix of other subscription services incorrectly bill our members. Determine the most frequent subscription services and prices, then look for members who are getting duplicate charges or are potentially being over billed and alert the member.
Phone numbers and hours There is nothing worse than having the wrong hours or addresses on your website Create an inventory of locations and hours and where the information is kept. Review this list once a year (website, facebook, behind online banking, mobile…you get the idea). Test the phone numbers and ensure everything is correct and operational.
Loan Payments Sometimes people over pay Run a report of loan payments made vs. expected.  If someone pays 10% more than normal, look into it further and let the member know.

Have an idea or something to add to this list? Submit it to the Credit Union 2.0 team today by emailing us at info@cu-2.com and help us improve this post!

Want to learn more about how your fellow Credit Union leaders are using data? We invite you to join our Credit Union 2.0 Strategist Group where over one thousand industry leaders comment on new news and trends while sharing and learning from one another.

This is the sixth post in a 9 part series. If you can’t wait for next week and want the full “Almost 99 Credit Union Small Data Hacks Guide” click here!

In case you missed it:

Click here for part one of the data analytics series.

Click here for part two of the data analytics series.

Click here for part three of the data analytics series.

Click here for part four of the data analytics series.

Click here for part five of the data analytics series.

 

Survey Ideas for Members

Creating repeatable processes that allow your credit union to continuously adjust and recreate good experiences for your employees is essential for receiving social validation. Credit unions have lots of repeated interactions – swiping a credit card, going to an ATM, calling a call center, etc. Since financial services are commoditized and fungible, it’s not fair to measure loyalty solely on a transactional level; you have to look at it much more holistically. Loyalty comes from the way you make a member feel, among other intangible identifiers. Feelings come from experiences that are unexpected or highly differentiated.

Tools like LiveSurvey are a great way to see a holistic picture. You’re able to map the person at an intricate level when giving the service, the resolution to the problem on a one-on-one basis, etc.

LiveSurvey tracks each transaction and follows up with the member to solicit feedback. Every time a member calls the call center or walks into a branch, within a minute or two of that transaction, LiveSurvey is notified of the transaction within the system. It know what, where, and who made the transaction and can immediately send a survey to ask valid experiential questions related to the transaction.

Through the use of LiveSurvey, one credit union discovered its members were creeped out by how fast they were being greeted, how much everybody was smiling, and how focused the employees were on providing a really pleasant experience.

Transactional surveys are rapidly becoming the number one most popular method for staying in touch with members. With the right questions, you will gain key insights that will help you credit union achieve massive growth and increased profitability. With transactional surveys, your credit union is gathering member feedback from all member touchpoints, at all times. Asking the right questions will aid you in attracting more of the members you want.

This article has a few credit union member survey question ideas. Here are several examples of survey questions to use with your members:

  • Ask a member why he/she joined your credit union. Were they referred by a friend? Perhaps it was a promotion you ran that worked really well or an advertisement they saw. Finding out what drew these most coveted members to your credit union means you’ll be able to model your future efforts based on what worked to bring in these members.
  • Loyalty-based questions like “How often do you use our services?” or “What is the main reason you continue to do business with our credit union?” can give valuable insight into the underlying reasons that your members remain loyal. Once you know, you can emphasize these characteristics to new and existing members in the same category, or even promote these features to prospective members.
  • The “open-ended” question is probably the most valuable of all. Simply asking the member “is there anything else you’d like to tell us?” can open the floodgates of information regarding their perception of your credit union, the products, the locations, any many other areas. Be sure to always have space for “open comments” on your transactional surveys.

 

 

Credit Union Data Analytics: Risk Awareness

As we continue the Credit Union 2.0 “Almost 99 Small Data Hacks for Credit Unions – guide” series, today we are covering risk items for internal consumption only. While many of our hacks are targeted at proactive marketing, these hacks are key insights you can gather internally from your member data.

This is the fifth post in a 9 part series. If you can’t wait for next week and want the full “Almost 99 Credit Union Small Data Hacks Guide” click here!

Credit Union 2.0 – A Guide for Helping Credit Unions Compete in the Digital Age covers in depth both big and small data for credit unions. There are six types of data that your Credit Union should be aware of:

  1. Digital Analytics – Desire
  2. Profitability – Fit
  3. Wallet Share – Depth
  4. Transaction – Triggers
  5. Design Data – Predictive
  6. Execution – IFTT (if this than that)

This list is by no means comprehensive and Credit Union 2.0 does not offer any compliance advice for any state or federal laws on the impact of using this information.

Risk Analytic Where to find it? Potential Conclusions
Minimum Payments Credit Card Data If you see members reducing their payments over time on their credit card payments, this may indicate an increased risk of default or challenging cash flow situation for your member.
Member locks themselves out Online Banking Proactively reach out if the member locks themselves out. Call their phone on record, don’t just wait for the member to call in. A frustrated member will appreciate this.
Duplicate Addresses Monthly Report of more than one member with the same address Could indicate a stolen identity
Duplicate SSNs Monthly Report of more than one member with the same SSN Could indicate a stolen identity
Duplicate Driver’s License Monthly Report of more than one member with same Driver’s License Could indicate a stolen identity
Delinquent Loans by Indirect Lender Loan System Could indicate an indirect auto dealer encouraging members to lie about income
Loans without payments Monthly report of loans with new payments Possible indication of fraudulent loans
Loans with payments made at the teller line Loan payments by teller/channel Possible indication of fraudulent activity
Loan types and dollar consistencies by MSR Loan applications by channel and person Possible indication of fraudulent activity

 

Have an idea or risk related data algorithm? Submit it to the Credit Union 2.0 team today by emailing us at info@cu-2.com and help us improve this post!

Want to learn more about how your fellow Credit Union leaders are using data? We invite you to join our Credit Union 2.0 Strategist Group where over one thousand industry leaders comment on new news and trends while sharing and learning from one another.

This is the fifth post in a 9 part series. If you can’t wait for next week and want the full “Almost 99 Credit Union Small Data Hacks Guide” click here!

In case you missed it:

Click here for part one of the data analytics series.

Click here for part two of the data analytics series.

Click here for part three of the data analytics series.

Click here for part four of the data analytics series.

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 a member.

This is the fourth post in a 9 part series. If you can’t wait for next week and want the full guide “Almost 99 Credit Union Small Data Hacks Guide” click here!

Credit Union 2.0 – A Guide for Helping Credit Unions Compete in the Digital Age covers in depth both big and small data for credit unions. There are six types of data that your Credit Union should be aware of:

  1. Digital Analytics – Desire
  2. Profitability – Fit
  3. Wallet Share – Depth
  4. Transaction – Triggers
  5. Design Data – Predictive
  6. Execution – IFTT (if this than that)

Most credit unions have several potentially confusing service limits and fees. Exposing some of these can cause undue fraud and sometimes even compliance risk. Consequently, credit unions may want to leverage this data behind the scenes and highly personalized it so as not to broadcast key risks or vulnerabilities to the world.

We explore several of these below.

Service or Limits What could happen? What should you do?
Remote Deposit Capture Setting a low limit universally will frustrate your top members. Design a multi-tiered profile based on key risk data and ensure that you give your best members higher limits.

 

When a member hits a limit, trigger an outbound email explaining how the limit was set and what they can do to change it.

ATM Limits Member is forced to make multiple trips to the ATM to get their business done…frustrating. If you see a member make the same size transaction multiple days in a row, send them a guide on how to request an increase and the pros and cons of doing so.
Change of Address You change it one account, but in a different system you forgot to update. Make a checklist of all of the locations you store addresses and make sure you clean them up everywhere at once.
Check holds Member forgets a hold came off. Ask members if they want to know when holds expire in an email. Offer them a one-click enroll in this option and then send them an email if a hold is removed.
No retirement savings Member struggles to retire Offer easy savings strategy series to members. Provide weekly tips or ideas to help your members save.
Fraudulent ACH Member is confused If a member reports fraud, trigger an outbound email that links back to an overview of how the credit union will help them troubleshoot and resolve the fraud. Update the member at agreed upon times during the investigation/resolution of the issue.
Fraudulent Check Member is confused If a member reports fraud, trigger an outbound email that links back to an overview of how the credit union will help them troubleshoot and resolve the fraud. Update the member at agreed upon times during the investigation/resolution of the issue.
Fraudulent Credit/Debit Member is confused If a member reports fraud, trigger an outbound email that links back to an overview of how the credit union will help them troubleshoot and resolve the fraud. Update the member at agreed upon times during the investigation/resolution of the issue.
Declined Transaction Member is confused and/or annoyed Have guides and information outlined on when and how transactions are declined. Include key troubleshooting strategies to resolve the issue for legitimate transactions. When the decline happens, send an outbound email to the member with a link to the guide.

As in our earlier post on turning negative fees into more positive experience, service limits are a similar opportunity. Anytime your credit union can change confusing non-transparent service items into positive transparent items, you build trust and loyalty from members.

Want to learn more about how your fellow Credit Union leaders are using data? We invite you to join our Credit Union 2.0 Strategist Group where over one thousand industry leaders comment on new news and trends while sharing and learning from one another.

This is the fourth post in a 9 part series. If you can’t wait for next week and want the full “Almost 99 Credit Union Small Data Hacks Guide” click here!

In case you missed it:

Click here for part one of the data analytics series.

Click here for part two of the data analytics series.

Click here for part three of the data analytics series.