The Decision Maker

Data Use Cases for Credit Unions: Chapter 2

Posted by Lou Grilli on Jun 6, 2019 10:09:00 AM

Getting Out from Behind The Curve

Chapter 1 of this series considered the importance in establishing a specific goal to solve using data analytics and proving the ROI in order to justify automation and decisioning using business intelligence in a credit union. Chapter 1 also highlighted two real use cases of success credit unions have had using data analytics to solve real-world problems. According to a recent study conducted by Best Innovation Group (BIG) and OnApproach (now Trellance), 45 percent of credit unions don’t currently have a strategy in place, and those that do have a strategy still say it will take three to five years to implement. Credit unions that aren’t making the most of data analytics today could be in even bigger trouble if an economic downturn occurs, as some economists are forecasting. “As we go forward there will be a significant performance difference between those that have invested and those that have not,” says Kirk Kordeleski, senior managing partner at BIG. “We think any downturn in the economy will highlight the advantage that data-oriented FIs will have over their competitors.”

How Much Will It Cost

The survey revealed that more than half of the 85 credit unions surveyed have budgets in place for data analytics. Of those, one-third plan to spend more than $200,000, the other two-thirds plan to spend between $50k to $200k. In addition, credit unions need to consider on-going costs. A rough rule of thumb is that a CU with $500 million in assets should budget between $150,000 and $300,000 per year for three years to cover software/hardware, analytic applications, and strategy. Smaller credit unions can find some savings by relying on a CUSO to provide the analytics and associated services.

The following paragraphs are real use cases that credit unions have shown to prove out their investments.

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Topics: Business Intelligence, Credit Unions, Data

Unlock the Data in your Reports

Posted by Lou Grilli on May 16, 2019 11:07:36 AM

Simple Steps To Make More Informed Decisions And Enhance Member Experience

There is a lot of buzz about big data and data analytics, but all the data in the world does no good unless it is utilized. Credit unions are behind retail and online companies in using data to make informed decisions. For example, if your forms, such as a HELOC application, do not have the fields for name, address, etc. already filled in for your members, that indicates that you are probably not using your data. You should already know this information about your members. Save them the hassle and give them the option of updating if necessary.

There’s so much more data than was available in the past that can be collected and used for purposes that can benefit the member. There are also better tools than previously available to aggregate the data to help decision makers. These two factors are bringing a wave of data analytics to credit unions. More importantly, it’s a matter of survival. Credit unions must take advantage of these opportunities to guide their sales initiatives. For example, the data can help you to decide who to target, like a new member who joined the credit union to access an auto loan, should be offered your credit union-branded credit card to maintain a sticky relationship. Or, who not to target for a specific product, like a member who already has your credit card but accessed a new loan, should not be sent another offer for the same credit card. Rich data helps you to determine who your target is for specific products and services, which helps to enhance your member experience.

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Topics: Reporting and Analytics, Business Intelligence, Data Visualization

Data Use Cases for Credit Unions: Chapter 1

Posted by Lou Grilli on Apr 29, 2019 11:53:00 AM

Data Use Cases is an ongoing series showcasing real use cases of success that credit unions have had using data analytics to solve real world problems. Data analytics was once the sole domain of giant tech companies – Amazon’s suggestions “If you bought that you might like this”; Facebook’s algorithms that determine which of your friend’s posts you most want to see on your timeline; Google’s ability to propagate data about you so that when you search for something like “hotels in San Francisco” you start seeing ads for restaurants in San Francisco on other sites. With the proliferation of data across multiple systems, the increase in computing power at a decreasing price, and tools to extract and harness data, the science of data analytics to create solutions to business problems, also known as business intelligence, is being increasingly used by credit unions to make better decisions. And it’s not just the biggest credit unions introducing business intelligence through data analytics to their staff. Credit unions with under $500 million in assets are realizing that use cases for data analytics drive ROI, better member experiences, and increased product penetration across their member base. Almost ironically, it is the smaller credit unions that absolutely need to embrace the use of data analytics – they are the ones that need to remain competitive or be merged out of existence.

Data Just For Data’s Sake – NOT!

It’s important to keep in mind that no company, regardless of what industry, invests in data analytics just for the technology. The cost of the tools, the hardware (or more commonly, the cost of cloud storage), investment in staff such as business analysts and possibly a data scientist, consulting services to help get started, can represent not just a significant up-front investment, but an on-going cost that must be justified. The justification comes in the form of use cases – individual examples of data-driven decision-making that makes a difference in how members are rewarded, or sold-to, or what products are offered, or just making a member feel more connected to their credit union through targeted, meaningful campaigns. In fact, for a credit union that’s just embarking on the data analytics journey, the best way to start is with the end in mind. Pick a single use case, a single vexing problem to solve, ideally one that has a fairly high payback if solved correctly. There are many articles that talk about the intangible benefits of business intelligence. But credit unions, especially their CFOs, want to see a return on their investment. The following paragraphs are a few real use cases that credit unions have shown to prove out their investments.

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Topics: Business Intelligence, Data Analytics, Data-Driven

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: Business Intelligence, Big Data, Data Analytics

Credit Unions and Big Data/Analytics [VIDEO]

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



 

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Topics: Business Intelligence, Big Data, Credit Unions, Data Integration, Data Pool, Analytic Data Model, Data Analytics

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 Integration, Data Pool, CUSO, Analytic Data Model, Collaboration

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, Business Intelligence, Big Data, Credit Unions, Data Integration, Marketing, Data Pool, Video, Analytic Data Model, Data Analytics, Collaboration, Podcast, Digital, Lending

Is Your Credit Union Ready for Big Data & Analytics?

Posted by Paul Ablack on Oct 27, 2014 12:58:00 PM

I recently attended a seminar at which John Best, CEO of Best Innovation Group, presented on the topic of mobile technology and payments. A key takeaway from the presentation was his explanation of why many technology implementations fail.

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Topics: Business Intelligence, Big Data, Credit Unions, Data Analytics

“I Know It When I See It” - 3 Essentials for Effective Business Intelligence Requirements

Posted by Peter Keers, PMP on Oct 15, 2014 11:30:00 AM

Supreme Court Justice Potter Stewart famously said about obscenity, "I know it when I see it". This often seems to be the case with many credit union decision makers when asked to define Business Intelligence (BI) requirements.

Consider this common scenario: an innovative credit union executive champions the BI concept. The executive points out all the flaws in organization’s current reporting and analytics. Then, showing examples of how BI is revolutionizing performance in other industries, secures budget dollars for a BI initiative.

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Topics: Reporting and Analytics, Business Intelligence, Credit Unions, Data Integration, Budgeting, Analytic Data Model

4 Reasons for a Scalable Data Warehouse

Posted by Nate Wentzlaff on Oct 13, 2014 10:48:00 AM

Meeting the rapidly changing data requirements necessary for today’s economy and allowing credit unions to adapt.

Scalable data warehouse architecture is vital for the Credit Union Movement.  It gives credit unions the ability to flexibly change and add data to their data warehouse (DW).  With a constant flood of technological innovations and regulatory changes, credit unions are continually being bombarded by new data requirements.  Regulators, business executives, IT and other stakeholders are constantly requiring deeper analyses of the data residing within the credit union.  As software companies are able to process increasing amounts of data, credit unions have access to enormous amounts of data.  However, this influx of data can be disastrous if the DW within the credit union is not built to accommodate future changes and growth. 
 
In order to fulfill the limited number of reporting goals that were detailed in the initial requirements, many organizations build a DW with only the present in mind.  It is human nature to fix a present situation without considering future needs.  However, with insight from data warehousing and BI professionals, envisioning the DW scalability necessary for the future advancements is possible.  If credit unions want to remain competitive and continue to propel their mission, they will need to take their  DW architecture seriously. 
 
Four major reasons that a credit union will need scalable DW architecture are:
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Topics: Business Intelligence, Big Data, Credit Unions, Data Integration, Analytic Data Model