The Trellance Data Blog

Predictive Analytics Empowers Credit Unions to “Think Globally, Act Locally”

Posted by Nate Wentzlaff on Dec 4, 2014 1:01:00 PM

Predictive Analytics Empowers Credit Unions to "Think Globally, Act Locally"

In order to continue thriving, the credit union industry must launch predictive analytics solutions to impact local initiatives

In his 2007 book, Competing on Analytics, Thomas Davenport explains how analytics solutions have been implemented to give competitive advantage to companies throughout various industries.  The astronomical amount of data being collected and analyzed by large companies (financial and non-financial) threatens individual credit unions who currently rely on rearview reporting of historical data.  Therefore, a holistic approach to data that leverages predictive analytics is the key to the success of credit unions.  With predictive analytics, credit unions will be able to effectively cultivate the abundance of data available (from a variety of sources) to create innovate solutions that capture opportunities within their local community.  By utilizing public data (e.g. IMF statistics) along with their private data (e.g. core systems), credit unions will truly be able to “think globally, act locally”.

Think Globally: Interconnected Financial Systems

Credit Unions are being impacted by global events now, more than ever before.  With the world’s widespread adoption of the internet, trade is traveling in seconds rather than days.  The world’s finances are more interconnected than ever.  A college student with a $1,000 online brokerage account in the United States can invest in a palm oil factory in Malaysia with the click of a mouse.  Political unrest in Hong Kong can cause the capital markets in London to destabilize with one governmental decision.  Like it or not, we are truly becoming the global village once envisioned in sci-fi novels.  With the amount of data being produced daily by world events, how does a credit union capture new opportunities out of this chaos? 

Credit unions, like people, will follow the crowd when they do not feel confident in their ability to predict the future.  An ability to build predictive analytics on pooled global data will give credit unions the ability to rise above the crowds to capture opportunities that others simply do not see.

Act Locally: Opportunities In The Chaos

After gathering data on a global scale, credit unions must make decisions on a local level.  The future of interest rates, for example, has a serious impact on all credit union decisions.  Gains (and losses) are the result of interest rate mismatches between assets and liabilities.  Utilizing predictive analytics will allow credit unions to mitigate their interest rate risk and, more importantly, capture opportunities.  Managing the loan portfolio is currently a speculative process and optimizing it with predictive analytics gives credit unions the ability to take action locally.

Deciding on the concentration level of first mortgages in comparison to auto loans is a prime use case for predictive analytics.  Without the ability to understand the purchasing power of people that will need specific loans, many managers make decisions based on pure conjecture and past experiences.  However, with a well-built predictive analytics program, managers will be able to gather insights and make data-driven decisions for optimal performance.  Passionate employees, with predictive analytics tools, will become the future champions of the credit union industry.

Artificial Intelligence: Systematic Learning

As credit unions begin using predictive analytics, they will be able to continuously improve their predictions.  Predictive analytics are constantly changing as the world becomes filled with more data.  Past performance of analytics solutions and new data being produced (inside and outside of the credit union) will allow predictive analytics solutions to begin learning from their performance.  As our brains change when we learn a new skill, predictive analytics models will continuously change based on the “learning” they attain over time.  The artificial intelligence of analytics solutions may sound like another sci-fi novel, but companies all around the world are realizing its benefits and investing billions of dollars into its development.

Cooperating On Analytics

Instead of competing with their predictive analytics solutions, the credit union industry must continue to be true to its roots.  By cooperating on insights from predictive analytics, credit unions will be able to build applications for the toughest problems (and best opportunities) within the industry.  Fostering an analytics ecosystem among groups of credit unions will be the next step in predictive analytics.  Combining the cooperative philosophy with predictive analytics technology will bring a new wave of collaboration to spur innovation throughout the credit union industry. 

Credit Union Data Analytics: Beginning The Journey Whitepaper


Topics: Big Data, Credit Unions