Credit score competition: be a force for change

Any Star Wars fans out there? The iconic trilogy ended with “The Return of the Jedi,” which was released in 1984.  Perhaps other than its creator, George Lucas, we all thought the masterpiece had come to a thrilling and suitable end.

Au contraire! Fast forward to today and Hollywood is rolling out new sequels, prequels and spin-offs every year!

Not to make light of a very serious matter, sometimes I feel as if our efforts to introduce competition into the mortgage market have taken on a similar, saga-like feel.

The latest installment was the Federal Housing Finance Agency’s (FHFA) publishing in the Federal Register an 18-page Notice of Proposed Rulemaking. As my note mentioned last month, the proposed rule was supposed to interpret and set into motion the credit score competition provision of the ‘‘Economic Growth, Regulatory Relief, and Consumer Protection Act’’ (Public Law 115-174), which was passed into law last spring.

The law requires FHFA to establish standards and “criteria for any process used by an enterprise to validate and approve credit scoring models …” and Fannie Mae and Freddie Mac to “establish validation and approval process[es] for the use of credit score models.” 

In other words, the law was aimed at introducing a competitive market in which mortgage lenders and borrowers are able to continue to assess the latest breakthroughs and potentially leverage the features and benefits of various different, preapproved models.

Instead, as it is currently proposed, the rule would perpetuate and strengthen FICO’s current monopoly by making nearly all of FICO’s current competitors “ineligible” as a result of various newly proposed requirements that were not originally included in the Credit Score Competition Act.

Here’s why this matters and how you can help:

In order to keep pace with shifting population demographics and changing borrower behaviors (detailed last month in this newsletter), it is critical that lenders have the ability to leverage recent scoring innovations. Such innovations will only continue if credit score model developers compete on an even playing field.

We have paved the way for positive changes in the credit scoring market. Among many first-to-market innovations that are now widely accepted, VantageScore was the first model to eliminate paid collection accounts to prevent them from penalizing a consumer’s score. We also extensively increased the population of consumers who can be reliably scored using the latest model development methods and provided increased transparency to help consumers understand their credit health.

In order for the marketplace to leverage these benefits, and embrace what competition will create for the future, the proposed rule must be dramatically revised.

The good news is that THE RULE IS NOT FINAL. Industry participants are urged to provide their feedback through a comment period that will end on March 21, 2019.

Competition is good for consumers and good for the industry. We’ve posted information and addressed industry concerns on our website.

Your comments will shape how the rule is implemented.

Further information and the portal for comment solicitations is on the FHFA’s website here. We strongly encourage your input and would be happy to provide additional information upon request. Send inquiries to

Oh … and may the Force be with you!


Barrett Burns

Student loan risk down, bankcard risk up Shows Risk in Student Lending Hitting All-time Low as Bankcard Lending Risk Category Continues to Rise

VantageScore Solutions, LLC, developer of the VantageScore® credit scoring models, announced an update to its Default Risk Index™ (DRI), an online tool that identifies lender risk appetite in major loan categories, using new loan origination data from the third quarter of 2018. After five years of data collection, the most recent update reveals a risk in student lending trending downward, this quarter marking its lowest DRI since the inception of the DRI in 2013. Relative to other loan categories, the overall risk in student lending remains high though the trend downward signals improvement.

The DRI compares the volume and weighted-average risk profile of quarterly originations within each major loan category. The following table measures changes in index values for these loan categories between the third quarter of 2018, the second quarter of 2018, and the third quarter of 2017.

















































Default Risk Index Insights

Originations: Mortgage originations slowed 7% relative to last year, while auto and credit card originations showed little change. Student loan originations more than doubled in the third quarter, consistent with seasonal expectations.

DRI: Despite the surge in volumes, student loan originations looked less risky both relative to the previous quarter (-18%) and to the third quarter in the prior year (-7%). This is the lowest student loan DRI observed since the beginning of the series.

Snapshot: The DRI began five years ago with a starting value of 100 in each lending category. In the third quarter of 2018, the student category reached its lowest value ever (“lower” indicating less risk) while the credit card category showed its second highest yet (the highest was in the second quarter, same year). The auto category is closest to where it started, at a DRI of 94, while the mortgage DRI of 88 reflects relative tightening (the latest value is in the bottom, or lowest risk, quartile of DRI values observed so far).   

About the Default Risk Index™

The VantageScore DRI and its website,, permit users to monitor the shifting quarterly risk profiles of loan originations in the mortgage, credit card, auto, and student loan categories. The DRI is derived using credit file data from TransUnion and VantageScore odds charts — tables provided to VantageScore users that match values on the 300-850 VantageScore scale range with their corresponding probability of default (PD) values.

The DRI is a measure of relative changes in risk level, benchmarked against the third quarter of 2013, the first period for which data were compiled. Interactive tools at allow users to view trends for each loan category and freely download the data behind the charts.

Each risk profile for the DRI is indexed to the beginning of the series, where the third quarter of 2013 equals 100. DRI profiles that are close to 100 show an equivalent risk activity to the 2013 benchmark, whereas DRI profiles that fall further from 100 distinguish risk activity that is either higher or lower than the benchmark (depending on the results).

The VantageScore DRI is provided as a free resource to institutional and individual investors, professionals in the securitization field, academics, and all others interested in systemic lending risk. It is updated quarterly, with data reflecting loans issued in the preceding quarter.

VantageScore Solutions and TransUnion® developed the DRI to highlight limitations in the traditional ways credit scores are used to evaluate risk for categories or securitized pools of consumer loans. Today’s common practices — using “weighted average” or “distribution by score band” to summarize risk—are mathematically flawed. Reliance on those metrics can result in a miscalculation regarding the true credit quality of a loan pool as well as obscuring meaningful trends and leading a well-intentioned analyst to the wrong conclusions.

Why old models are just bad for business

By John Ulzheimer, credit expert and author

Every few years the companies that design and develop credit scoring models will go through the lengthy process of redevelopment. For comparison purposes, think of how Apple or Microsoft will periodically release a new operating system for your Mac, PC or smartphone. The newer version is very similar to the previous version, with some notable improvements.

As with smartphones, banks and other users of credit scores have the option to convert to the newest scoring model once it becomes commercially available. The process can be time-consuming, given the amount of analysis that must be done to properly adjust underwriting standards for the newer version, as well as the operational changes and governance steps involved. But the benefits far outweigh the challenges.

More Predictive

Newer credit scoring models are more effective than older scoring models and that’s really their primary function: predicting a future default. Changes in consumer behaviors, lending practices and the macro environment are better represented in newer models that are built on more recent observations. Further, the availability of new forms of data and more advanced modeling methodologies provide additional firepower to a newly developed model.

There are a variety of empirical methods used to compare the performance of credit scoring models. The Gini coefficient (“Gini”) and the Kolmogorov-Smirnov (KS) statistic are two common metrics used to compare the effectiveness of credit scoring models and their ability to delineate between future “good” and “bad” credit risk populations. Lenders perform such “champion-challenger” comparisons in evaluating new models. Other analyses performed to assess the performance of new credit scoring models relative to an older model compare profiles of approved and rejected borrowers, resulting in default rates as well as approval rates have given a loss tolerance.

Failing to adopt the newer versions means lenders are making decisions based on less effective tools, leading to suboptimal risk and pricing decisions. And, choosing to continue to use much older scoring systems, like what is happening in mortgage lending because of FHFA policy, is counter to sound underwriting and risk assessment practices.

Captures More Recent Trends in Risk Assessment

A valuable product of newer scoring systems is the ability for the model developers to react to more recent data and research and development findings, and then apply these learning into their scoring models. This is commonly referred to by credit score experts as “following the data.” The underlying premise of a credit scoring model, like any model, is that what is observed in data historically will be indicative of the future. Hence, models that take into account more recent observations are more representative of the “through the door” populations and will perform better. Newer models also benefit from insights gained from data elements that were previously unavailable for modeling.

There are many examples of features included in newer scoring models that are not captured in older scoring models, like the ones used by mortgage lenders. Some of these features in newer models relate to:

  • Changes in borrower behavior post-Great Recession
  • Treatment of smaller dollar collections or collections with zero balance
  • Treatment of medical collections
  • Accounting for the reduced presence of derogatory public record information due to changing reporting requirements, and
  • Use of new data measuring changes in credit behavior over time versus a static snapshot

Benefits Consumers and Lenders Alike

As previously addressed, newer scoring systems do a better job of more clearly separating lower risk consumers from higher risk consumers. What this means, in practical terms, is low-risk consumers are going to have higher credit scores under the newer scoring models. Think about that: Higher credit scores simply because a lender is using a newer and better scoring model. This translates to higher approval odds for a loan and better product terms, such as lower interest rates and higher credit limits for creditworthy borrowers.

The opposite, of course, is true as well. In older scoring systems, low-risk consumers are going to score lower than they deserve. This means consumers who do business with lenders that use older scoring models may have lower chances of being approved for a loan or face less favorable product terms, compared to what they would receive from lenders that use newer, more effective scoring models.

For lenders, the choice is between growing their business safely and soundly with the help of a newer and more effective scoring model supporting their underwriting decisions, or using an older model that may lead to loss of good business to competition, or worse, originating loans with higher risk of default than desired.

At the end of the day, lenders and consumers both win from using newer credit scores. Matching creditworthy consumers with the right loan products is good business for lenders and helps consumers meet their needs while guarding them against getting in over their heads with debt.

No Reason Not to Use Newer Models

There really is no good reason not to convert to the newer scoring systems if this helps business.

Sure, there’s work involved in converting to a new credit score. This may include an analysis that needs to be performed to determine the adjustments necessary to underwriting policies and product features, going through required governance processes, such as credit committee approvals and model validation, operations and technology changes, training and communication for staff, among others.

These activities are not uncommon as part of the normal course of business and should not deter from implementing a newer and better model. Lenders go through similar steps when introducing a new product, adjusting policies, entering new markets or adopting new processes or technology. While there is an initial investment, longer-term benefits offered by a newer model far outgrow the cost.

Disclaimer: The views and opinions expressed in this article are those of the author, John Ulzheimer, and do not necessarily reflect the official policy or position of VantageScore Solutions, LLC.

5 Questions with Jim Deitch

Jim Deitch is co-founder and chief executive officer of Teraverde®. Previously, he was a co-founder, chief executive officer, and director of“Feb2018” the American Home Bank division of First National Bank of Chester County. Under his leadership, American Home Bank was named one of the fastest growing private companies in the United States by Inc. Magazine and a top 50 national residential lender by American Banker and National Mortgage News. Mr. Deitch has served on the board of publicly traded and privately held banks and non-bank companies. He is a frequent industry speaker and best-selling author.

In 2018, he wrote the best-selling book “Digitally Transforming the Mortgage Banking Industry: The Maverick’s Quest for Outstanding Profit and Customer Satisfaction.” Its success was followed up by his most recent book, “Strategically Transforming the Mortgage Banking Industry: Thought Leadership on Disruption from Maverick CEOs,” which is now available for sale online.

Not only is VantageScore proud to be listed in his latest book, we are honored to be speaking with Mr. Deitch for our newsletter this month.

1. In your mind, what constitutes being a maverick?

 A maverick is a groundbreaker, a pioneer. The original Sam Maverick was a Yale graduate, from New England, who moved to Texas when it was dangerous territory, worked hard and accepted the risk to create a new state. Like Sam, today’s maverick takes calculated risks to grow, to invoke change. Like Sam, a maverick is an initiator, someone willing to explore unfamiliar territory and try on innovative ideas when and where others are not. Just as Sam maverick helped to create a Texas constitution, that was fair to all, mavericks today look for joint wins for the consumer, the company and the industry in an innovative, responsible and creative manner.

2. When you think back about how the mortgage industry has changed over the years, who stands out as the biggest mavericks?

I’ll quickly mention three names of many important mavericks: Dave Stevens, former CEO of the MBA, united the industry to address regulatory, political and legal threats arising from the subprime meltdown. Bill Emerson of Quicken achieved outstanding customer satisfaction numbers eight years in a row and created RocketMortgage. Deb Still of Pulte Mortgage played key roles in Pulte, MBA leadership and MBA Opens Doors. There are more, and I’ve profiled many of the mavericks in my books.

3. How does your book address situations like the Countrywide scandal where a maverick or “maverick-like behaviors” caused consumers significant harm? Are there lessons to be learned there? 

Being a freewheeling buccaneer who takes excessive risks with other people’s money and lives is the farthest thing from a maverick. A maverick’s carefully calculated risks are the outcomes of thought innovation and idea exploration leading to a win/win. Let me be clear: During the 2005-2009 mortgage meltdown, a small percentage of mortgage executives allegedly engaged in irresponsible behaviors or, worse, allegedly knowingly engaged in illegal or deceptive practices. Those buccaneers sought their own benefit, not the maverick’s mutual benefit for the consumer, the company and the industry. 

4. Your book is a must-read for mortgage industry participants, but what are the broader lessons for those outside the industry?

The importance of transparency and fair dealing apply far beyond residential lending. While a few voices may decry our industry, 99.9% of mortgage participants strive to provide a competitive and appropriate product to serve consumers. Contrast that to a recent Wall Street Journal article on air travel that, in essence, concluded, “Many airlines view their customers as adversaries, with exorbitant ‘change’ fees that have no relation to value provided, to dynamic pricing mechanisms that extort business travelers.” I suggest that many airline executives could benefit by spending some time with executives from Quicken, Guild, SWBC and other mortgage company executives learning about customer experience and satisfaction.

5. There’s a technology revolution occurring in the mortgage industry that some might say is way past due. What are some of the innovations that you are most excited and hopeful about?

Much of mortgage banking is still stuck in the world of forms and procedures. Mortgage banking needs to be about data and loan performance. Eight-hundred pages of stuff doesn’t lead to good loan performance. Data-driven analysis of loan performance is exciting. For example, work that VantageScore is doing to score more consumers is an example of true innovation. 

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