If you are a credit union still waiting on the data analytics sidelines, you’re already too late. Data analytics is not a fad – it is a major opportunity for credit unions to gain deeper insights and improve decision making to create a strong and competitive future. However, it is not always clear where credit unions should begin. To help answer these questions, John Best recently spoke with Clay Yearsley, SVP of Data Analytics at Texas Trust Credit Union about getting started on the analytics journey, the skills needed, and the value of data in the podcast, “Catching a Unicorn – Discussing Data Analytics with Clay Yearsley”.
In the sixth and final Data Analytics Series BIGcast, That’s a Wrap, John Best speaks with Paul Ablack, OnApproach CEO, about key themes and trends we are experiencing in the credit union industry, and how credit unions can get started with data and analytics.
In the fifth Data Analytics Series BIGcast, Sorting Socks: A Data Automation Conversation with Graham Goble, John Best speaks with Graham Goble of BankBI about financial performance management, reporting, and business intelligence.
The Excel Curse
One primary point of discussion during the podcast is about the use of spreadsheets in comparison to data automation. “The Excel Curse” is certainly not unique to credit unions, but it is absolutely a problem across the industry that requires action. Excel is a powerful tool and serves a number of purposes very well, but advanced analytics for financial institutions is not one of them. Even for a spreadsheet guru, there a several fatal flaws in using such a software as a primary reporting tool in credit unions:
In the fourth Data Analytics Series BIGcast, From Questions to Answers: Becoming a Data-Driven Organization, John Best speaks with Brewster Knowlton of The Knowlton Group about data-driven decisions, data warehousing and successful data integrations.
The Six Characteristics of a Data-Driven Organization
According to Brewster, there are six characteristics to determine whether your organization is really data-driven:
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 the first episode of the BIGcast Data Analytics Series, John Best speaks with Anne Legg of THRIVE about credit union growth and member engagement. The financial services industry is changing rapidly, and credit unions need to keep on top of innovative technologies and competitive threats. As John and Anne discuss, big data has become a necessity for credit unions to continue to thrive.