The Decision Maker

Credit Unions and Data Lakes – The Next Wave

Posted by Peter Keers, PMP on Oct 5, 2017 12:03:00 PM

In two previous OnApproach blogs, the concept of a data lake was defined and differentiated from a traditional data warehouse. Yet, a key point was a data lake and a data warehouse are not mutually exclusive. In fact, a structured data warehouse could be a subset of an overall data lake architecture.

Simply stated, a data lake is an effective way to store and access very large quantities of data.

What does this mean for credit union decision makers?

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Topics: Data warehouse, Data Pool, Data Lake

What is a Data Lake? - Part 2: Sink or Swim

Posted by Mark Portz on Jul 26, 2017 11:07:00 AM

In my previous blog, “What is a Data Lake? Part 1”, I discussed how to define a data lake, and how it differs from a data warehouse. To briefly recap, a data lake is a massive data repository for raw data in its native format. To better understand the idea, let’s dive a bit deeper and get to know the advantages and disadvantages surrounding data lakes.

To start, there are a number of advantages data lakes serve for financial institutions:

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Topics: Data warehouse, Data Pool, Data Lake

What is a Data Lake? - Part 1: Testing the Waters

Posted by Mark Portz on Jul 18, 2017 11:03:00 AM

Financial institutions all over are working to build effective data strategies and improve decision-making. With so many new technologies and innovations out there, it can get very difficult to keep up with the industry and even keep straight the buzzwords we hear throughout the day. In this piece, let’s dive in to better understand what makes a data lake.

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Topics: Data warehouse, Data Pool, Data Lake

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

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

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

Medtronic and Masimo agree to share de-identified patient data to improve patient safety; A lesson for the credit union industry

Posted by Paul Ablack on Nov 15, 2016 10:01:00 AM

In a Star Tribune article this week, “Medtronic agrees to share data in patient-safety effort”, we learned that “when it comes to patient safety, the leaders of the two companies are now sitting at the same table to discuss how they can share de-identified patient data with each other, as well as outside researchers and entrepreneurs, to predict health problems.”

The need to share data about patients and customers is hitting the mainstream as companies figure out that the pooling of this data is critical to the discovery of new insights that can help them develop better products that improve the lives of their customers. Competitors in many industries are realizing that they need to “get over themselves” and start figuring out ways to share this data for the greater good.

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Topics: Data Pool, collaboration

Data Pooling: Leveraging Your Neighbor’s Data

Posted by Mitch Nelson on Oct 8, 2015 12:27:48 PM

The trend of data-driven decision making is exploding within the credit union space.  Pressures to increase revenue, reduce risky assets, and efficiently identify qualified sales leads have all contributed to the growing trend.  But as the push for data-driven decision making has gained popularity, the need for a wider breadth of data has become apparent. 

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Topics: Data Pool, Data Storage

Credit Unions and Big Data/Analytics [VIDEO]

Posted by Austin Wentzlaff on Mar 16, 2015 12:13:00 PM



 

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Topics: Analytics, Business Intelligence, Big Data, Credit Unions, Data warehouse, Data Integration, Data Pool, Big data/analytics, Analytic Data Model

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