The Decision Maker

Nate Wentzlaff

Recent Posts

Prescriptive Analytics for Credit Unions: Healthcare Style

Posted by Nate Wentzlaff on Mar 2, 2017 12:03:00 PM

Just as healthcare is developing robust analytics for patients, credit unions have a great opportunity to empower members to track their financial health and take actions to improve it.

Being raised in a small town, I never thought about the healthcare I received. I had the same doctor from birth until I moved to college. As long as nothing seemed wrong to him, I felt confident that I was healthy. However, when I moved to a bigger city, everything changed. I was no longer able to rely on my hometown doctor, and I needed a way to monitor and maintain my health. At the same time, the healthcare industry was going through a data revolution. The traditional relationships between doctors and patients were changed forever. In shopping for my new healthcare provider, I felt the most comfortable with the one that had the best analytics and enabled me to make data-driven decisions to improve my health.

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Topics: Data Integration, Data Analytics, Prescriptive Analytics

Credit Union Cooperation: Google Maps Style

Posted by Nate Wentzlaff on Feb 7, 2017 12:02:00 PM

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.

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Topics: Analytics, Data Integration, Data Pool, Cooperation, Data Visualization, Insight Platform

The Comfort of Data-Driven Decisions

Posted by Nate Wentzlaff on Dec 13, 2016 11:02:00 AM

 

As the next generation begins making financial decisions, credit unions will be able to comfort them with data-driven product recommendations.

Recently, my wife and I were shopping for a mattress. We began the process by “trying out” mattresses by how they felt. My wife thought she preferred firm mattresses, while I thought I preferred soft ones. As we tried mattress after mattress, my wife would ask me, “what do you think about this one”, in which I would usually reply, “It feels pretty good to me”. We became frustrated by a complicated search for a large budget item until we found a mattress store that comforted us with data. The mattress store (Becker Furniture World) is locally owned with only 8 locations (does this sound familiar to your credit union?). They approached mattress shopping from a data-driven way. By using an analytic data model (developed by Sleep to Live Institute), they are using analytics to aid customers in their mattress investments through data sensors and user input. The data comforted us enough that we decided to purchase one of the mattresses it recommended.

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Topics: Analytics, Data-Driven

The Purpose of Analytics

Posted by Nate Wentzlaff on Nov 1, 2016 12:04:37 PM

As credit unions continue to invest in analytics solutions, they should focus on the purpose of analytics; Making data-driven decisions to better serve members.

Big data and analytics are a couple of the most used buzzwords throughout the credit union movement.  You can’t avoid these terms no matter where you try to hide. Many vendors promise analytics that will be a panacea to the movement. They continue to make bold claims that are sure to perk an executive’s ears (and drive sales for the vendor). Although there are many powerful products available to credit unions, they must understand the purpose of analytics before they begin their journey.

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Topics: Analytics, Machine Learning, Data-Driven

The Power of Truth in Credit Union Analytics

Posted by Nate Wentzlaff on Sep 28, 2016 10:07:00 AM

Data generation continues to grow at an exponential rate throughout the credit union industry. In order to hear the signals through the noise, credit unions must establish a single version of the truth.

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Topics: Analytics, Semantic Layer

The Power of Semantics in Credit Union Analytics

Posted by Nate Wentzlaff on Aug 23, 2016 11:06:00 AM

A common language forms a bond between humans and strengthens their ability to cooperate. Credit unions must agree on common semantics to establish powerful business analytics throughout the industry.

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Topics: Data Integration, Data Standards, Semantic Layer, data model

Sharpen Collateral Valuation through Data Integration

Posted by Nate Wentzlaff on Jul 13, 2016 11:30:00 AM

Collateral Valuations are essential while serving members and maintaining a healthy credit union. However, credit unions are relying on inaccurate valuations of their members’ collateral values because of disintegrated data.

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Topics: Big Data, Credit Unions, Data Integration, predictive analytics

The Fed is Data-Driven; What Drives Your Credit Union?

Posted by Nate Wentzlaff on Apr 14, 2016 11:30:00 AM

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In the last few FOMC meetings, the Federal Reserve has emphasized it will only act according with economic data. The same data that the Federal Reserve utilizes to make data-driven decisions are available to every credit union. 

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Topics: Analytics, Big Data

Saving Small Credit Unions with Big Data

Posted by Nate Wentzlaff on Mar 30, 2016 1:00:00 PM

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Topics: Credit Unions, Big Data & Analytics

A Storm's Brewing: Build Your Data Reserves!

Posted by Nate Wentzlaff on Jan 13, 2016 11:30:00 AM

As economic changes and regulatory winds continue to blow faster every year, credit unions should prepare for the future by effectively collecting and storing their data.

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Topics: Credit Unions, Data Storage

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