The Decision Maker

Comparing Credit Unions to Craft Beer: What Can Your Organization Learn from a Brewery?

Posted by Mark Portz on Mar 20, 2018 12:14:00 PM

As collaborative community-based institutions, credit unions are very unique organizations. For many that have not been exposed to credit unions, it is difficult to see what makes this community so special, or even how a credit union differs from a bank, for that matter.

Since my time as an undergraduate at the University of Minnesota, I have been highly involved in another industry, or “community” – that of local craft beer. In fact, discovering the parallels between these two unique industries sparked my initial interest in the credit union movement, and is ultimately what has led me to my current role at a collaborative credit union service organization (CUSO).

In very recent years, the nation has witnessed the craft brewing community explode. In fact, according to the Brewers Association, the craft beer industry has been experiencing years of steady 10-15 percent growth, and now boasts over 6,000 U.S. craft breweries, for the first time in history. Despite the parallels between these communities outlined below, we are all aware of the declining number of U.S. credit unions, shrinking from over 7,200 in 2011, to less than 6,000 today. For community-based institutions focused on quality service, why do these trends differ?

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Topics: Data Pool, Shared Applications, predictive analytics, collaboration, CU Analytics Platform

Coming up for Credit Unions... Blockchain, Chatbots, AXFI and more with Paul Ablack on CUbroadcast [Video]

Posted by Mark Portz on Nov 2, 2017 11:10:00 AM

At the 2017 NWCUA MAXX event, Paul Ablack joined Mike Lawson of CUbroadcast to discuss Digital Transformation, predictive analytics, chatbots, the upcoming Analytics and Financial Innovation (AXFI) Conference, the increasing popularity of blockchain, and more. 

As a part of the conversation, Paul and Mike discuss member expectations and the interactions between credit unions and members. Members who shop at stores such as Zappos experience seamless and easy-to-use online shopping. These types of experiences alter the expectation for members when interacting with other organizations, such as their credit unions. In addition, credit unions have to learn how to connect with members throughout the entire decision making process. As Paul points out, credit unions need to position themselves to not just be in the business of loans or mortgages, but as an organization that is helping to make dreams come true. Rather than just being the last step in a process of getting a loan, credit unions could help with the decision making process, and truly be there for members before they've even decided whether they need a loan. 

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Topics: Video, predictive analytics, AXFI Conference, Blockchain, CUBroadcast, Digital Transformation

5 Reasons to Pool your Data

Posted by Mark Portz on Mar 7, 2017 1:04:00 PM

Data continues to prove itself as a necessity for decision-making in financial institutions. For years, major banks and innovative companies such as Google and Amazon have taken advantage of “Big Data” to gain better insights into their customer base and make business decisions to position themselves for the future. The credit union industry is finally beginning to take advantage of their data and utilize new technologies. However, credit unions are much smaller than major banks and simply don’t have the same quantity of data that banks are able to collect from their customers. Fortunately, data pooling serves as a great solution to this problem. Here are 5 reasons your credit union should participate in data pooling:

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Topics: Data Pool, predictive analytics, Data Analytics

Descriptive, Prescriptive and Predictive Analytics, Oh My: The CECL Journey

Posted by Mark Portz on Jan 23, 2017 11:06:49 AM

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”:

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Topics: Data Pool, predictive analytics, Data Analytics, CECL, BIGcast

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

Why Attracting Millennials Requires Data Analytics

Posted by Austin Wentzlaff on Feb 11, 2016 2:05:59 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.

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Topics: Big Data, predictive analytics, Millennials

Analytics for CECL: Challenge Creates Opportunity

Posted by Austin Wentzlaff on Jan 28, 2016 11:30:00 AM

“Everything negative - pressure, challenges - is all an opportunity … to rise.” – Kobe Bryant

Getting ahead of the new CECL requirements is a strategic initiative for all credit union executives in 2016. Being compliant will be no easy task, however. The new CECL requirements require life-of-loan loss forecasting capabilities. In most cases, this means the credit union will need to collect data, A LOT OF DATA. Unfortunately for most credit unions, collecting, storing, and analyzing data has not been a priority and most do not have the proper infrastructure in place to do so.

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Topics: Big Data, predictive analytics, CECL

Mobile Payments and Big Data

Posted by Austin Wentzlaff on Jul 15, 2015 1:31:14 PM

“…wallets may generate substantial data that will lead to better member insights and possibly also profits.” – Kirk Drake, founder and CEO of Ongoing Operations, LLC

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Topics: Analytics, Big Data, Mobile Payments, Payments, predictive analytics

Credit Union Industry Disruption: NACUSO 2015 – Part 2

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

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.

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

The Future of Analytics: Predictive Analytics

Posted by Austin Wentzlaff on Apr 22, 2015 12:24:00 PM

The promise of business intelligence and Big Data/Analytics has been around for years.  Companies have been making claims that data-driven decision-making will revolutionize organizations but have failed to fully deliver.  It is true that descriptive analytics (reporting) is necessary and valuable but in order to create real value (Return on Investment) for data analytics, organizations must think about the future.  In order to achieve real value from Big Data/Analytics, organizations must execute predictive analytics.

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Topics: Analytics, Business Intelligence, Big Data, predictive analytics

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