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  • Writer's pictureRoy Urrico

Credit Union Leaders Gather to Discuss Data Analytics Topics


More than 300 CU attendees gathered at Trellance conference. Source: Trellance.

By Roy Urrico


More than 300 attendees from the credit union industry gathered at the Trellance annual conference in Tampa, Fla. May 17-20, 2022, for insights into the ways advancing data technology can solve key challenges and unlock new opportunities.


The Trellance annual conference addressed what the company sees as central data and technology issues for the industry including credit unions’ need to advance data maturity toward predictive analytics, to forecast trends and events, and prescriptive analytics, all of which help organizations prepare for certain scenarios. The gathering also focused on the nationwide need for technology talent, the changing dynamics of member service, and the migration of technology into the cloud.


“It was wonderful to see how many credit unions want to act – and not react – in the face of changing market dynamics,” said CEO Tom Davis of Tampa-based Trellance, which helps credit unions with data management, quality, and governance. He added, “Members’ expectations for service are evolving rapidly as Big Tech shapes their preferences, and tech-first competitors are looking for opportunities to go after credit unions’ mainstay business. Credit unions know they occupy a valuable space in financial services, and they are determined to adapt and innovate to stay relevant.”

CEO Tom Davis of Tampa-based Trellance.

Many leaders in the credit union movement indicated a commitment to innovating faster, strategizing better, and defying expectations with their ability to manage change.


A Recap of Key Conference Topics


The following subjects were among the most popular at the Trellance conference.


Predictive Analytics: Opportunities and Trends. To compete in the emerging fintech environment, credit unions must produce meaningful analytics and react to market movements validated by their own member behaviors.


Credit unions must leverage the power of cloud-distributed artificial intelligence (AI) and machine learning (ML) technologies, and apply data science models to improve members’ experience and reveal opportunities to provide products and services that members want and need. Additionally, predictive models can help credit unions accurately determine a member’s lifetime value.


The Holy Grail for Optimal Member Experience. The cloud, AI, and ML can create optimized member experiences. Credit unions continue to shift the concept of member service to one powered by technology, integrating data from a myriad of sources and mining deeper for previously unknown insights.


Craig Meyer, data manager at the $1.66 billion Melrose, Minn.-based MagniFi Financial shared how his credit union invested in cloud data analytics to empower employees with faster and deeper insights.


Leading Data Quality Practices. When it comes to data, more is not better if the data is not high quality. In fact, bad data actually hurts the bottom line and ultimately leads to poor decision-making. So, how are the credit unions with better data achieving and maintaining it with less effort?


Machine learning and automation together help meet the challenge of managing trusted, high-quality data at scale. Trellance and its partner, Pasadena, Calif-based DQLabs, shared leading best practices that improve data quality and insight accuracy for data governance, management, architecture, and lifecycle; and the use of metadata and analytics.


The Tech Talent Crunch. Credit unions are struggling to fill open positions while at the same time defending their turf against tech-savvy disruptors. The talent shortage figures to get more acute as organizations in all industries draw from the same talent pool.


Credit unions must think differently about how to build a high-performing technology department today. Trellance shared use cases of how credit unions are employing more flexible and dynamic staffing models to address specific challenges.


Non-Interest Income Transaction Analysis. With profit margins squeezed ever tighter, doing more with less is the new name of the game. For portfolio profitability, credit unions must understand network interchange and meticulously track results.


Trellance and its partner, Australian-based Leverage Technologies, looked at the best networks to maximize interchange revenue, how to avoid paying for unutilized networks, and the best tools to track results monthly and annually.

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