The Decision Maker

The Next Big Idea for the Credit Union Industry

Posted by Paul Ablack on Feb 23, 2015 11:11:57 AM

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.

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Topics: Business Intelligence, Big Data, Credit Unions, Data warehouse, Data Integration, Data Pool, Big data/analytics, predictive analytics, CUSO, Cooperation

How Credit Unions Can Leverage Big Data [Video]

Posted by Austin Wentzlaff on Feb 5, 2015 11:30:00 AM

 


 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.

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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

Why Attracting Millennials Requires Big Data/Analytics

Posted by Austin Wentzlaff on Jan 27, 2015 12:26:00 PM

Millennials are living in a vastly different world than their Baby Boomer parents. They live in a time in which a phone isn’t just a piece of plastic used for making calls, it’s now “smart” and acts as an extension of oneself. A time in which “going shopping” or “depositing a check” no longer requires you to leave home. We are living in a world dominated by the rise of online/mobile and the demise of brick-and-mortar. This changing consumer landscape is being primarily driven by Millennials as they demand more personalized experiences.

Defining Millennials – Millennials (also known as the Millennial Generation or Generation Y) are the demographic cohort following Generation X. There are no precise dates when the generation starts and ends. Researchers and commentators use birth years ranging from the early 1980s to the early 2000s.

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Topics: Credit Unions, Big data/analytics, predictive analytics, Millennials

Understanding Analytics at Your Credit Union

Posted by Austin Wentzlaff on Dec 29, 2014 11:30:00 AM

On December 9th, 2014 I attended an afternoon presentation at the Credit Union Big Data/Analytics Conference hosted by OnApproach. This particular session, “The Denali Story: What Management Needs to Know About Analytics” was presented by Greg Nolder, VP of Applied Analytics at Deep Future Analytics (a CUSO formed by Denali Alaskan FCU) and discussed common reporting and analytics practices at credit unions. More specifically, he discussed his vision for the future of credit unions, and how they can remain competitive in an ever-changing industry by adopting predictive analytics strategies.

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Topics: Analytics, Big data/analytics, predictive analytics

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

Posted by Nate Wentzlaff on Dec 4, 2014 12:01:00 PM

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”.

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Topics: Big Data, Credit Unions, Big data/analytics, predictive analytics

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You now have more information at hand about your credit union than ever before. But are you using it to "out-think" your rivals? If not, you may be missing out on a potent competitive tool.

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