Report
525
Number
Nov 09 2020

Data Analytics and the Future of Financial Services Overview

Led by Filene Fellow Cheri Speier-Pero of Michigan State University, the Center of Excellence for Data Analytics and the Future of Financial Services will explore the practice of data analytics and prepare credit unions for the future financial services landscape. The research will offer an actionable framework for effective approaches to data management and analytics for the larger financial services industry concomitant with ethical practices in the use of consumer data.

Cheri Speier-Pero
Cheri Speier-Pero
Associate Dean, Broad College of Business, E&Y Professor of Accounting and Information Systems
Michigan State University
Report Number 525

WHAT WORK WILL BE DONE BY THE CENTER OF EXCELLENCE FOR DATA ANALYTICS AND THE FUTURE OF FINANCIAL SERVICES? 

The exploration of data analytics is not new to Filene’s members, and credit union leaders have wrestled with issues related to data analysis across the spectrum from early IT outsourcing to core processors and data integration, and fairness around AI technology. This Center is designed to facilitate our knowledge of effective credit union industry data analytics use. Thus, establishing a baseline of how and on what types of activities credit unions are implementing analytics solutions provides an initial benchmark. More importantly, this Center strives to accelerate the development, implementation, and creation of value associated with a responsible data analytics strategy.

To accomplish this, the Center will focus on an ecosystem framework to address the following questions: 

  1. What capabilities do credit unions need to deliver valued-added analytics?
  2. What partnerships will most benefit credit unions as they seek to develop successful analytics programs (e.g., core providers, technology partners, academic institutions, etc.) and what do these partnerships look like? 
  3. What operational issues do credit unions face regarding data, business processes and human capital, and how should they resolve these issues to accelerate successful data analytics outcomes? 
  4. How might credit union leadership develop a data-driven culture within the organization?