Executive Summary
Credit unions looking to accelerate their analytics capabilities can leverage the wealth of knowledge and talent of academic researchers and their university students by forming long-term, close partnerships with their universities. Credit union personnel can work jointly on a defined project with a specified faculty member (usually called the “faculty mentor”) and his or her students, who can then apply their state-of-the-art analytics knowledge and ideas to address the credit union’s analytical problem.
Such credit union–academic institution partnerships not only support credit unions’ data science and quantitative projects but also provide credit unions with a talent pipeline for their analytics capability. In fact, credit union–academic institution partnerships can provide the following:
- An ability to assess the unique value of quantitative techniques or skills before the credit union must invest in the human capital that has that analytics technique or skill.
- In-depth exposure to all students, allowing the credit union to accurately assess a student’s fit as he or she decides whether to join the partner firm as an intern or employee.
- Ongoing relationships with the faculty mentor, in which the corporate partner continues to engage with the mentor after the conclusion of the project to leverage his or her expertise, either informally through conversations or more formally through consulting engagements.
- A deep, meaningful, and continued partnership will support a breadth of the credit union’s needs, including internships, training, workshops, customized executive education, and programming.
Credit Union Implications:
Academic Institution Partnership with the Credit Union Data Exchange
The Credit Union Data Exchange (CUDX) is an endeavor conceptualized and launched during the summer of 2023 and sponsored by Filene Research Institute and Trellance, a credit union technology company. Headquartered in Tampa, Florida, Trellance has partnered with hundreds of credit unions since its 1989 inception, and over the last few years, it has become the leading provider of analytics solutions to the credit union industry.
Thus, CUDX leverages Trellance’s technological platform and analytics provisioning with Filene’s quest to address innovative ideas that continue to enhance credit union capabilities. Additionally, credit unions participating directly with CUDX provide primary governance for CUDX itself, defining its processes, including use case priorities, data management guidance, and the development of a common data model.
As CUDX evolves from a conceptual framework to a robust data exchange leveraging the collaborative nature of the credit union system, it is important to have quantitatively skilled data scientists who can support the evaluation of use cases. While some participating credit unions will be able to leverage the analytical talent they currently have within their organization, having a sufficient number of employees with the requisite quantitative skills will remain a significant challenge for every participating credit union. Facilitating relationships with experienced academic institutions can supply some of this talent and jump-start the CUDX use case value creation.