The Decision Maker

Credit Union Industry Disruption: NACUSO 2015 – Part 2

Posted by Paul Ablack on Apr 27, 2015 12:43:00 PM

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Last week in my blog, Credit Union Industry Disruption: NACUSO 2015 – Part 1, I talked about the pending threat of Big Bang Disruption in the financial services industry and the growing prominence of predictive analytics. In this second and final blog on the learnings from the NACUSO 2015 conference, I will cover what we learned about how credit unions can respond to Big Bang Disruption and the strategic importance of Predictive Analytics.

In my Part 1 blog, I summarized the portion of the presentation by John Lass, Lass Advisory Services (www.cunamutual.com) that outlined the threats facing the credit union industry. The latter part of his presentation provided four recommendations on how credit unions should respond to industry disruption:

  1. Be Alert – pay attention to your competition
  2. Pay Attention to the clock – things change very quickly as the taxi industry is realizing with UBER.
  3. Use defense to buy time – John referenced using a legislative approach; this will buy time but it is not a fix
  4. Develop an offensive strategy – this is the only way to long term prosperity

In his closing comments Mr. Lass referred to the book “Only the Paranoid Survive”, by Intel CEO Andy Grove, as a template for how CEOs should constantly challenge their business model. Many businesses get trapped by their own strategy and process to the point where they are unable to respond to competitive challenges.

There was a lot of discussion about the volumes of data that credit unions possess and the importance of harnessing that value through predictive analytics.  Dr. Joe Breeden of Deep Future Analytics, a CUSO focused on predictive analytics for credit unions, demonstrated how predictive analytics is strategically important. Dr. Breeden has over 20 years of experience in large bank retail lending analytics and was an advisor to major corporations in the last global financial crisis. He possesses a deep knowledge of nonlinear modeling, optimization and validation, and is the author of the book, “Reinventing Retail Lending Analytics”. Below is a summary of six key points from Dr. Breeden’s presentation at NACUSO 2015:

  1. Big banks and big competitors for the CU industry are investing millions of dollars right now on regulatory compliance, focused on avoiding another financial crisis. Dr. Breeden stressed several times that the 2008 financial crisis could have been averted if the lending institutions has priced adequately for risk which requires an ability to forecast probability of default.
  2. Regulators are currently focused on driving stress testing models and methodologies and the big banks are spending huge on developing true predictive scenario-based loan-level models which is a huge improvement over the current models which are based on historical performance.
  3. Given the huge investment being made in predictive risk models, those institutions making the financial commitment are looking for a return on their investment in four areas that would create competition for CUs:
    • Pricing
    • Risk appetite
    • Account management
    • Loss reserve forecasting
  4. Credit risk is now more than just FICO, Term and LTV
    • The new methods are big data driven and incorporate many additional factors for a true forecast
  5. The good news is that credit unions are also at a point where we can meet this competition through collaboration. Collaboration:
    • allows credit unions to be faster, more nimble, and more responsive
    • enables pooled repositories of historical behavioral data
    • allows predictive anaytics to be developed at a fraction of the cost.
  6. The first institution to use a loan-level forward-looking model was a credit union and that model is being used today successfully to predict loan level risk, set loan pricing, and much more.

In summary, we know that changes are coming to the financial services industry and that the level of competition from these Big Bang competitors will be formidable. This is too big a challenge for 95% of the credit unions in the US to face on their own. However, the credit union industry has a number of competitive advantages: (1) they have built up a brand identity with their members, (2) they sit on huge volumes of data that can be used to help them better serve their members, and (3) they know how to collaborate to find solutions to tough industry problems.

If credit unions take an aggressive tack towards becoming Analytic Competitors (from the book Competing On Analytics, by Thomas Davenport), they stand a very good chance not only surviving the next three to five years but thriving during that time. Today, credit unions hold about 7% of the US retail financial services market. What if the industry set a collective goal to be 14% of the US retail financial services by the year 2020 by making use of innovative practices like predictive analytics? What should credit unions be doing now to prepare?

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Topics: Analytics, Big Data, Big data/analytics, predictive analytics, Credit Union Service Organization

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