The Decision Maker

Data: The Key to a Successful Card Portfolio

Posted by Ann Farrell on Jun 25, 2019 1:17:41 PM

Understanding your members’ behavior gives you the opportunity to serve them effectively, and in turn, increases your bottom line. Unfortunately, it is not uncommon for credit unions to overlook existing cardholders as a significant opportunity to help stimulate portfolio growth and increase profitability. With the use of data, you can identify trends that will help you to ensure that you are offering the right incentives, rewards, and services that will not only retain your existing cardholders, but also attract new prospects.

What can data do for you?

Data can open the door to product and service opportunities that your credit union did not offer in the past. Also, by utilizing data from your card portfolios, as well as home and auto loan applications, you will have a vivid picture of each member that will help you to create unique member experiences. In the end, you can feel confident that you are offering a competitive card product and doing what is required to stay “top of wallet.” With rich data you can:  

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Topics: Marketing, Membership, Data-Driven, Lending

Using Big Data to Move Beyond FICO and LTV for Loan Analytics

Posted by Paul Ablack on Dec 4, 2018 12:02:00 PM

The FICO score has a long and well-established history as a key metric in the determination of credit-worthiness. The FICO score has the power to influence whether a person can experience significant life events, like the purchase of their first car or home. Currently, it’s a major factor in credit union loan analytics.

However, as we rapidly enter the age of Big Data and loan analytics, does the FICO score utilize enough information to make an accurate determination of a borrower’s ability to pay? The wealth of data available to credit unions should augment their loan analytics.

A New Age of Loan Analytics

As I consider the future of credit unions, I believe the industry’s position on the significance of the FICO score in their underwriting process is an important issue. Is FICO a major determining factor, or is it merely one of many data points that can be used to predict probability of default for a given loan?

The mission of the credit union movement is to improve the lives of their members. While this is a very altruistic and admirable goal, it is only possible if credit unions can effectively assess and manage their loan portfolio risk. Current loan analytics strategies privilege the credit union over the member. At the end of the day, credit unions have a fiduciary responsibility to protect the assets entrusted to them by their members.

Credit unions are faced with delicately balancing two diametrically-opposed objectives when serving their members:

  1. Being more compassionate than the big banks when it comes to lending.
  2. Being “prudent,” as defined by NCUA guidelines, in their lending practices. For any loan application that is being processed by a credit union, the decision comes down to the FICO score and the Loan to Value (LTV), which is no different than the big banks.

Is there a better way to balance for loan analytics? The answer is a resounding, “yes.” Big Data and analytics is the new frontier for the retail lending industry.

If Others are Doing It…

Credit unions have access to volumes of internal data and the means to access external data. However, they lack the infrastructure and the culture to perform the loan analytics needed to improve their underwriting processes.

Expanded loan analytics platforms may have eluded credit unions, but others are leveraging more complete information. Lending Clubs are entering the retail lending market with lots of data (which credit unions also have) and loan analytics (an area where credit unions are behind the curve).

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Topics: Big Data, Insight Platform, Lending

Making the World a More Predictable Place: Which CECL Model is Best for your Credit Union?

Posted by Alex Beversdorf on Nov 27, 2018 12:05:00 PM

 

Which CECL Model Should You Choose_

Trouble playing the video above? Click here. from CUbroadcast on Vimeo.

Current Expected Credit Loss, or CECL, is an important upcoming accounting requirement that requires financial institutions to attempt to predict the expected losses on loans and other debt securities over the entire life of the loan. Large retailing banks and credit unions of all sizes can benefit from an accurate CECL model as both entities provide much of the same services to their customers and members, respectively.

The two main metrics you have to consider when choosing the right CECL model should be accuracy and procyclicality. If a loss model lacks accuracy and consistency, what’s the point of spending all that time, money, and effort in a meaningless implementation? A good CECL model will be adequately equipped to better track credit losses. There is a strong correlation between the credit cycle and the economic cycle. Models that account for implied volatility better estimate the timings and severity of economic recessions and manage to do so in a timely manner.

In the webinar, “Which CECL Model Should You Use”, Dr. Joseph Breeden, Chief Scientist and COO, at Deep Future Analytics and Prescient Models LLC, talks about the various types of CECL models. He clarifies the key differences between simple “spreadsheet” models and more advanced statistical models and how they can directly benefit credit unions with improved predictability.

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Topics: Video, CECL, Lending

FASB’s New CECL Comments Could be a Worst-of-Both-Worlds Approach

Posted by Joe Breeden (Deep Future Analytics) on Apr 19, 2016 11:30:00 AM

Last week’s comments by the Financial Accounting Standards Board (FASB) about how they will allow the different levels of complexity in credit loss calculations for lenders of different sizes would seem to be a victory for smaller credit unions and community banks.

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Topics: Credit Unions, CECL, Lending

Credit Union Industry Disruption: NACUSO 2015 – Part 1

Posted by Paul Ablack on Apr 20, 2015 12:51:56 PM

I had the opportunity to attend NACUSO 2015 in Orlando last week. NACUSO is a great conference to interact with other thought leaders in the credit union industry to make valuable business connections. It is the essence of the “credit union movement”, a group of talented industry leaders looking for ways to collaborate to make the industry stronger.

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Topics: Big Data, CUSO, Data Analytics, Digital, Lending

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

Lending Clubs: A Threat to Credit Unions

Posted by Austin Wentzlaff on Nov 26, 2014 10:32:00 AM

This article was originally posted on CUinsight.com on November 19th, 2014 by Austin Wentzlaff 

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Topics: Big Data, Data Analytics, Lending

4 Ways “High Tech” meets “High Touch” in Credit Union Big Data/Analytics

Posted by Nate Wentzlaff on Nov 18, 2014 11:26:00 AM

Member-focused initiatives must be blended with high tech solutions in the credit union industry

In his #1 New York Times Bestseller book, Megatrends, John Naisbitt predicted that with the rise of “high tech” solutions, people would increasingly feel a need for “high touch” connections to balance technology overload.  The need for personal touch in financial services has been continuously met by the credit union industry.  Many banking customers have become disillusioned after being treated as just another number in a bank’s system.  The mission of credit unions is to deepen relationships with their members to provide them with exceptional products and services.  However, they realize that technology on its own will not bring about superior service for their members.  By keeping the High Tech/High Touch balance in utilizing Big Data/Analytics (BD/A) solutions, credit unions will bring efficiency to their processes and excellent service for their members.

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Topics: Big Data, Membership, Branch, Lending