Advanced Analytics and Machine Learning are no longer just buzzwords or far-away future developments. They have become a reality and are the basis of any future business undertaking. Corresponding strategies and decision-making processes are either in the process of being implemented or already part of daily business.
But how are Credit Unions performing in this game compared to their competitors such as large or regional banks or Fintech players?
It was with this question in mind that my colleagues and I headed to the NAFCU Lending Conference in St. Pete, FL, in November and also to the Credit Union CFO Summit in Fort Lauderdale, FL, in December. Our team had developed a short assessment that gave Credit Unions the option to evaluate their data & analytics maturity on the spot by answering a few questions. One lucky Credit Union even won a free Analytics Discovery Project.
The assessment results and the feedback we received provide interesting insights into the status of digital transformation in the Credit Union industry that I would like to share with you today.
1. Status quo: Credit Unions are just starting their data & analytics journey
Most Credit Unions want to become more data-driven to foster future growth, attract new members and optimize decision-making. However, approximately half of the Credit Unions we interviewed did not have a clear data and analytics strategy yet. Some Credit Unions viewed implementing such strategy as a purely departmental project instead of taking a holistic approach.
2. Obstacles: Leveraging data & analytics in finance is not easy
In our conversations with Credit Union representatives on both the NAFCU Lending Conference and the Credit Union CFO Summit, it became clear that several hurdles are preventing Credit Unions from becoming truly data-driven. First of all, budget is almost always an issue. Implementing data-focused culture is an investment, and the corresponding ROI often takes time to materialize. However, these investments should not be an optional choice. On the contrary, they are essential to ensure that Credit Unions don’t fall even further behind in the data & analytics journey. Secondly, a lack of relevant talent such as data scientists or data analysts is a major problem – even for Credit Unions that have committed to setting aside the relevant budget and that are looking to recruit. Last but not least, the lack of a holistic digital growth plan slows some Credit Unions down. Thus, it is essential to develop and implement a cross-departmental data & analytics strategy – joint forces are crucial to achieve sustainable progress.
3. Next steps: What to achieve with data & analytics in 2019
Member and loan growth are top priorities for almost all Credit Unions we talked to, along with fraud prevention, a better loan quality and an optimized collections process. The good news is: All these challenges can be tackled by establishing and implementing a data & analytics strategy along the member lifecycle. Collecting data and building data warehouses are the first steps towards gaining a better understanding of members. In the end, this helps optimize not only particular areas such as lending and reporting, but the complete member lifecycle.
Do you want to embark on the data & analytics journey? Please click here to find out how you can optimize your member lifecycle.
If you’d like to assess your organization’s data & analytics maturity and to receive detailed guide on how to foster progress on this journey, please click here.
Questions? I am happy to receive your email.
Business Development | North America