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Credit Union Data Insights | CULytics Takeaways

Credit Union Data Insights | CULytics Takeaways
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Recently I attended the CULytics 2023 Summit in Seattle, and as someone with two decades of experience in financial services data and analytics, I found it to be a valuable experience. The CULytics Summit brings credit union leaders together to discuss real-life motivations and challenges around data and digital. This was my first time attending a credit union-specific event, and I was impressed by the knowledge and insights shared by both the speakers and attendees. Throughout the conference, I had the opportunity to connect with other professionals in the industry and learn about the latest trends and strategies in credit union analytics. In this article, I will share some of my insights from the event and key takeaways that may be useful for those working in this field. 

Insights & Key Takeaways

Credit unions must keep up with evolving technology and data to stay competitive and meet member experience expectations. This conference highlighted many data challenges for credit unions and suggested strategies for addressing them. There were four key takeaways of interest to credit union leaders: the need for a data strategy, personalized digital experiences for members, supplementing internal data with third-party data, and integrating data, technology, automation, and strategy. By taking these into account, credit unions can overcome challenges and leverage the power of data and analytics to drive success in today’s digital landscape. 

  1. Credit Unions Likely Need a Data Strategy
  2. Personalization is Expected 
  3. Credit Unions Need More than Internal Data 
  4. Data, Technology, Automation, & Strategy Need to Work Together 

Credit Unions Likely Need a Data Strategy

Many credit unions could benefit from developing a robust data and analytics strategy. Being buyers and integrators of systems, credit union data is often spread throughout the organization. The keynote speaker indicated that only 24% of Credit Unions have a written data strategy. Many credit unions I spoke with are working hard to get beyond the tyranny of Excel to improve the lives of both members and employees. Without a strategy, it will be challenging to orchestrate the many moving parts required to make data-supported decisions.

Personalization is Expected 

Members experience a fully personalized digital experience in many aspects of their lives. They are coming to expect this experience from their credit union. With competition changing from street corners to digital, credit unions will need to micro-segment their members based on behaviors to deliver services that meet these expectations. They’ll also need to offer customizable digital interfaces to execute strategies for each segment. 

Credit Unions Need More than Internal Data 

FICO inflation, personalization, the share of wallet, and FinTechs all create pressure on Credit Unions to go beyond their own data. Growing lending accounts in a time of potential inflation requires improving underwriting. That likely means new sources of data that help split the risk. Personalization may require credit unions to supplement what they know with 3rd party data to help better understand members.  

Data, Technology, Automation, & Strategy Need to Work Together 

Many attendees that are mature in their analytics capabilities reported issues with execution. They indicated it is difficult to get their analytic insights back into core systems to act. This is referred to as connecting the last mile. Challenges came from getting prioritization against other initiatives and from difficulty integrating new capabilities with legacy systems. Credit unions must integrate technology portfolio planning better to include implementing analytics projects back into core systems or finding partners that can help. 

Dig Into the Panels at CULytics 2023

The CEO Panel | A Strong Start

The CEO panel at the CULytics 2023 Conference highlighted several key themes relevant to credit unions. One of the central themes was the importance of leveraging data and analytics to make positive changes to enhance the member experience. The panelists encouraged credit unions to use data and analytics to identify member pain points and areas for improvement. They also suggested using data to personalize experiences and improve first-point-of-contact resolutions. 

Another emerging theme was the value of using capabilities like Robotic Process Automation (RPA) to streamline processes and drive efficiency. The panelists discussed how RPA could simplify the lending process by automating documentation and ensuring readiness to fund. Two of the three CEOs on the panel mentioned using RPA in their organizations, highlighting the growing interest in this technology among credit union leaders. 

Finally, the panelists emphasized the importance of staying up to date on new technologies and industry trends by attending events and staying educated. They recommended attending events like Money 2020 and Finnovate and using tools like data maturity assessments. You’ll be better positioned to create products and services that delight members by staying informed and aware of trends. 

Future of Lending | Panel Insights

Several interesting topics were discussed during the “Future of Lending” session at the Summit. One key insight was the importance of using alternative data sources beyond credit unions, as credit repair creates bias data, and the stimulus led to “FICO inflation.” The panelists discussed using alternative data sources to find ways to extend lending opportunities to members. 

The panelists also emphasized that competition in the financial industry is not limited to physical branches on the street corner anymore. Competition comes from digital entrants as well. Additionally, it was noted that credit unions are not closing branches as fast as banks, and that deposits per branch have increased four-fold over the past 20 years. This creates both new challenges and new opportunities for credit unions.  

When asked about strategic priorities, the panelist shared: 

  • Be ready for the pending recession by focusing on collections maturity 
  • Work to combat the growing cases of fraud the industry is facing 
  • Drive growth in credit cards, deposits, and members 

The CFO Panel Focused on Credit Union Data Use Cases

This was a rich session for generating ideas on how credit unions are leveraging data and analytics. Some of the use cases shared included: 

  • Second chance insufficient funds (NSF) – look for any deposits that came in by the end of day to reduce NSF rejections and fees charged to members 
  • Look at customer touch points (statements, tax forms) and see what they are not doing online and run campaigns that coach them to use the online offerings 
  • Find ghost members – members that have an account and qualify for every product but never use them and run campaigns to convert them to active members 
  • Personalize welcome and onboarding of new members to digital services 
  • Collect information on member preferences and using the information to improve how you communicate with them 
  • Segment members and run experiments to boost debit and credit card usage to build loyalty 
  • Use modeling to identify suspicious actions and take action to reduce fraud 
  • Model personalized deposit / hold limits to reduce fraud losses and increase the average member limit available 
  • Enterprise operational reporting 

Credit unions must stay abreast of advancing technology and data analytics to remain competitive and satisfy members’ expectations. Data is one of an organization’s most robust assets, but leveraging it can be a challenge. To effectively leverage your data, you need a sound data strategy. If you want to get started, we have resources to help.

 

Additional Resources

About Reid Colson

Reid, SVP of Data and Analytics at UDig, is a long-time data professional with experience at multiple Fortune 500 companies. Most recently, he was the Chief Data and Analytics Officer at Markel. Prior to that he held multiple roles at Capital One including VP of Data Engineering.

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