The Decision Maker

Making a Difference with Data at Our Community Credit Union

Posted by Mark Portz on Oct 19, 2017 12:23:10 PM

In the recent BIGcast, Analytics as The Fuel for Innovation – Implementing Analytics at OCCU, Andrew Bertrand, Data Analyst at Our Community Credit Union (OCCU) in Shelton Washington, discusses his role as a data analyst, getting started with data analytics, and data pooling for predictive analytics.

Getting Started with Analytics at OCCU

In the podcast, Andrew explains that prior to installing OnApproach M360 Enterprise, OCCU, a credit union with $360 Million in Assets, had an ODBC connection to their core system. It was a hassle to obtain data, and it didn’t meet the growing needs of a data-driven organization. Andrew realized that he could not possibly perform any predictive analytics without obtaining the history of member transactions.

After briefly (and in Andrew’s words, “foolishly”) considering to build their own data warehouse, Andrew decided it would be an inefficient use of time and resources. As John Best describes, for a financial institution to build their own data warehouse from scratch, is like building a “house of cards” as it has to be rebuilt repeatedly as elements are added and improvements are made.

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Topics: Analytics, Case Study, Podcast, BIGcast

Quick Wins and Data Warehousing Advice for Credit Unions with Keith Malbrue

Posted by Mark Portz on Sep 21, 2017 11:07:00 AM

In the recent BIGcast, To Fish with a Net or a Spear? Implementing Analytics at CUTX, John Best discusses data warehousing, core conversions, and winning at analytics with Keith Malbrue, CIO at Credit Union of Texas. 

Core is NOT King

Years ago, in his previous role at another credit union, Keith Malbrue was the first OnApproach M360 client. He had come to OnApproach (a data consulting company at the time) with a problem. Keith realized member history was very important, and he didn’t want to lose all the member history when converting cores. According to Keith, it often feels like “Core is King” in this industry, but that doesn’t have to be the case. Credit unions should not have to lose member information because of a core conversion. To solve this problem, he engaged with OnApproach to discover a solution to this issue. The solution has come to be known as OnApproach M360 Enterprise.

By equipping his credit union with M360 Enterprise, Keith explains he gained 3 major advantages:

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Topics: Data warehouse, Podcast, BIGcast, Core Conversion

A Day in the Life of a Data Analytics SVP: Making Use of Your Credit Union’s Data

Posted by Mark Portz on Aug 24, 2017 11:17:42 AM

If you are a credit union still waiting on the data analytics sidelines, you’re already too late. Data analytics is not a fad – it is a major opportunity for credit unions to gain deeper insights and improve decision making to create a strong and competitive future. However, it is not always clear where credit unions should begin. To help answer these questions, John Best recently spoke with Clay Yearsley, SVP of Data Analytics at Texas Trust Credit Union about getting started on the analytics journey, the skills needed, and the value of data in the podcast, “Catching a Unicorn – Discussing Data Analytics with Clay Yearsley”.

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Topics: Data warehouse, Data Analytics, Podcast, BIGcast

Credit Union Service Organizations and Platform Analytics with Paul Ablack

Posted by Mark Portz on Mar 27, 2017 12:02:00 PM

In the sixth and final Data Analytics Series BIGcast, That’s a Wrap, John Best speaks with Paul Ablack, OnApproach CEO, about key themes and trends we are experiencing in the credit union industry, and how credit unions can get started with data and analytics.

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Topics: CU Analytics Platform, BIGcast

The Excel Curse and Automation Cure: 3 Reasons to Automate your Data

Posted by Mark Portz on Feb 21, 2017 12:05:00 PM

In the fifth Data Analytics Series BIGcast, Sorting Socks: A Data Automation Conversation with Graham Goble, John Best speaks with Graham Goble of BankBI about financial performance management, reporting, and business intelligence.

The Excel Curse

One primary point of discussion during the podcast is about the use of spreadsheets in comparison to data automation. “The Excel Curse” is certainly not unique to credit unions, but it is absolutely a problem across the industry that requires action. Excel is a powerful tool and serves a number of purposes very well, but advanced analytics for financial institutions is not one of them. Even for a spreadsheet guru, there a several fatal flaws in using such a software as a primary reporting tool in credit unions:

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Topics: Shared Applications, Data Analytics, BIGcast, Data Automation

Looking to the Future of Data Warehousing

Posted by Mark Portz on Jan 30, 2017 11:01:00 AM

In the fourth Data Analytics Series BIGcast, From Questions to Answers: Becoming a Data-Driven Organization, John Best speaks with Brewster Knowlton of The Knowlton Group about data-driven decisions, data warehousing and successful data integrations.

The Six Characteristics of a Data-Driven Organization

According to Brewster, there are six characteristics to determine whether your organization is really data-driven:

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Topics: Data warehouse, Data-Driven, BIGcast

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

A Clean Room, a Pool, and Actionable Information from Credit Union Data

Posted by Mark Portz on Jan 10, 2017 11:01:00 AM

In the second episode of the BIGcast Data Analytics Series, John Best speaks with Blesson Abraham of SavvyIntel about credit union analytics insights, data pooling and optimization. The financial services industry is facing immense pressures, and credit unions cannot rely on the intuition or “how it has always been done” any longer. As John and Blesson discuss, utilizing big data and advanced analytics is no longer an option, but a necessity for credit unions.

You Have to Clean Up your Room

Analytics is a major point of discussion these days for credit unions. However, less frequently discussed, is the organization of the data required to perform analytics. Companies such as SavvyIntel have created incredible models which can be utilized at all credit unions. However, no model is ever going to work properly and provide truly actionable insights if the data isn’t clean and validated.

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Topics: Data Pool, Podcast, BIGcast

Moonshots, Taco Bell, and Member Engagement at Credit Unions

Posted by Mark Portz on Dec 19, 2016 11:17:35 AM

In the first episode of the BIGcast Data Analytics Series, John Best speaks with Anne Legg of THRIVE about credit union growth and member engagement. The financial services industry is changing rapidly, and credit unions need to keep on top of innovative technologies and competitive threats. As John and Anne discuss, big data has become a necessity for credit unions to continue to thrive.

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Topics: Member Engagement, Podcast, BIGcast

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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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