Data continues to prove itself as a necessity for decision-making in financial institutions. For years, major banks and innovative companies such as Google and Amazon have taken advantage of “Big Data” to gain better insights into their customer base and make business decisions to position themselves for the future. The credit union industry is finally beginning to take advantage of their data and utilize new technologies. However, credit unions are much smaller than major banks and simply don’t have the same quantity of data that banks are able to collect from their customers. Fortunately, data pooling serves as a great solution to this problem. Here are 5 reasons your credit union should participate in data pooling:
As credit unions begin their journey into the future, they must rely on an industry standard analytics platform to guide them to their destinations.
Google Maps has revolutionized how we navigate our lives. It saves us from headaches caused by unnecessary traffic and other challenges in traveling. My journey from work to home has many different routes depending on traffic patterns. During days with slower traffic (i.e. - winter snowstorms), the Google Maps recommended route will change every 5 – 10 minutes. Using an analytics engine that informs me of the best route allows me to spend extra time on more important things in life. Credit unions have a similar opportunity when navigating their institutions into the uncertain future of financial services. Establishing an industry standard analytics platform will enable credit unions to cooperate on analytics and guide them to their desired destinations.
In the third Data Analytics Series BIGcast, The CECL Effect, John Best speaks with Joe Breeden of Deep Future Analytics about CECL, data pooling, and predictive analytics.
The Impact of CECL
As Joe Breeden explains in the podcast, CECL stands for Current Expected Credit Loss, and is the new accounting standard for how financial institutions will set loss reserves. Typically, organizations under $10 Billion assets have utilized moving averages to calculate loss reserves, but this model is backward-looking and will not be acceptable for the new regulations. A moving average model will always set your loss reserves too low moving into a recession and too high moving out of the recession.
When discussing how to meet CECL requirements and create a forward-looking model, Breeden states, “There is a lot of flexibility on how you implement it, but there are two things that are pretty much unavoidable”:
In the second episode of the BIGcast Data Analytics Series, John Best speaks with Blesson Abraham of SavvyIntel about credit union analytics insights, data pooling and optimization. The financial services industry is facing immense pressures, and credit unions cannot rely on the intuition or “how it has always been done” any longer. As John and Blesson discuss, utilizing big data and advanced analytics is no longer an option, but a necessity for credit unions.
You Have to Clean Up your Room
Analytics is a major point of discussion these days for credit unions. However, less frequently discussed, is the organization of the data required to perform analytics. Companies such as SavvyIntel have created incredible models which can be utilized at all credit unions. However, no model is ever going to work properly and provide truly actionable insights if the data isn’t clean and validated.
In a Star Tribune article this week, “Medtronic agrees to share data in patient-safety effort”, we learned that “when it comes to patient safety, the leaders of the two companies are now sitting at the same table to discuss how they can share de-identified patient data with each other, as well as outside researchers and entrepreneurs, to predict health problems.”
The need to share data about patients and customers is hitting the mainstream as companies figure out that the pooling of this data is critical to the discovery of new insights that can help them develop better products that improve the lives of their customers. Competitors in many industries are realizing that they need to “get over themselves” and start figuring out ways to share this data for the greater good.
The trend of data-driven decision making is exploding within the credit union space. Pressures to increase revenue, reduce risky assets, and efficiently identify qualified sales leads have all contributed to the growing trend. But as the push for data-driven decision making has gained popularity, the need for a wider breadth of data has become apparent.
The credit union industry is on the cusp of significant challenges with the potential to disrupt the financial services landscape as we know it. Big Data and Analytics is driving a new breed of competitor into what has been a very traditional marketplace. The industry will need to envision and build out the “Next Big Idea” for credit unions to stay competitive and successfully navigate the next 10 years.
OnApproach's Founder and CEO Paul Ablack discusses today's evolution of Big Data and how credit unions can benefit from this increasingly refined information to provide more specific products and services for enhanced value.
Topics: Reporting and Analytics, Analytics, Mobile Banking, Business Intelligence, Big Data, Credit Unions, Mobile Payments, Data warehouse, Data Integration, Marketing, Data Pool, Video, Mobile, Shared Applications, Big data/analytics, predictive analytics, Lending Clubs, Cooperation, Podcast
“Unity is strength... when there is teamwork and collaboration, wonderful things can be achieved.” –Mattie Stepanek
The credit union industry (or credit union movement as it’s often referred to) is probably one of the most collaborative industries in the United States, if not the entire world. Unlike other organizations, credit unions share ideas and even their “secrets.” They truly care about the welfare of the industry and its millions of members. It’s great! Collaboration benefits credit unions in several ways but one way, in my opinion, presents the biggest opportunity. Big Data and Analytics.