Hang On Sloopy For A Pot Of Gold

Mike Darne, vice president of marketing at CreditXpert, says almost anyone who applies for financing can raise their scores by 20 points, and do so within 30 days. That’s because scores are not static. Yet, when loan officers and agents pull someone’s score, they are accepted as such.

Yes, under today’s systems, scoring is a snapshot in time — no, a single moment in time — that is designed to tell us how well a potential borrower handles credit. Does he pay on time? Does he use the maximum amount of credit to which he’s entitled? Does he have any black marks against him?

But Darne says people are anything but static. They are living, breathing organisms who do things every day that change their scores. Perhaps they finance the purchase of a new car. Maybe they pay a loan early. Or perhaps they close out an old department store account.

Moving Numbers

As a result, scores are dynamic, moving numbers. And when considered in that light, Darne maintains, lenders should look at every applicant’s score, “not for what it is but what it could be … Taking the consumer’s credit score at face value is a mistake and can rob lenders of potential business.”

Darne, who has spent his entire career in one aspect of the financial services sector or another, calls it “credit optimization.” CreditXpert’s research, which included an analysis of nearly half of all mortgage credit inquiries, found that 74% — three out of every four — could have raised their scores from below 780 by as many as 20 points within a 30-day period.

Credit, as you know, is one of the three Cs of mortgage lending, the other two being capacity and collateral. But it is the only one over which the borrower has any control. Some aspects of a borrower’s credit take years to affect a score: payment history, for example, or the age of his credit accounts. Yet others can have an impact quickly, i.e., usage and the total number of accounts.

With that in mind, the Hampton, Md.’s credit optimization tool uses both data science and predictive analytics to identify a borrower’s credit potential AND offers a detailed plan that will help him reach his scoring potential. The program, which also identifies aspects of the credit file that could be problematic to underwriters, is available to lenders as a white label add-on, and a consumer-centric version is on the way.

The program searches for “opportunities” a borrower could take to raise this all-important score. But many applicants never get the chance to do so. CreditXpert found that 65% of a representative sample of people who bought homes in the last six months and who intended to buy in the next six were never given the chance to improve their scores.

Steps To Improvement

On the flip side, seven out of 10 of those who were told how they might raise their scores took steps to do so. Their main reason, of course, was to save money. How much cabbage varies with each person. But in one example offered by the company, an actual borrower seeking a $400,000 mortgage raised her score 40 points, saving a boatload of moolah in the process.

By taking three steps — which CreditXpert did not innumerate — she was able to raise her score 33 points, from an original 640 to 673. By taking an additional fourth step, again not revealed, she bumped up the number seven additional points, to 680. In so doing, she was able to trim her interest rate from 7.65% to a flat 7%.

The savings in principal and interest were formidable — $158 a month — as were the savings in mortgage insurance premiums — $131 — for a grand total of $289 a month. In addition, she was able to knock half a year off the time she had to keep MI coverage in force. And in the long run — queue the music, please — she will have saved nearly $74,000 over the life of her 30-year loan.

To quote Mötley Crüe, though, “Something for nothing … it’s never free.” And so it is with credit optimization. That is to say, the steps a borrower might be asked to take may require some out-of-pocket spending. In the above example, the borrower would have to spend $2,810 to ratchet her score up to 680. In this case, she mostly had to pay down a credit card or two. (In other instances, other accounts might have to be paid down as well.) And in just 10 months, she would all but recoup her out-of-pocket costs. The rest, as they say, is gravy.

Meanwhile, back at the GSE jungle, the Federal Housing Finance Agency has given Fannie and Freddie until next January to begin accepting scores produced by VantageScore 4.0 and the new FICO 10-T model as part of their approval processes. At the same time, though, the FHFA is asking all originators to place the 4.0 and10-T programs alongside the traditional FICO model. That way, lenders will have time to “get their internal plumbing systems in order,” said Tony Hutchinson, Freddie Mac’s senior vice president of industry and government relations, who called the current FICO program “outdated.”

Trends, Not Predictions

Both new scoring models are “trended” systems, whereas the FICO score now used by most lenders is based on a predictive snapshot of a borrower’s credit record on any given day and often excludes otherwise creditworthy people.

Even though new and innovative scoring models have found little traction in the mortgage arena, VantageScore has consistently monitored the performance of its model in housing finance. In its most recent assessment, according to a company white paper, 4.0’s predictive performance registered roughly midway between strong accuracy and perfect predictive value.

Most of the 2.7 million or so consumers who would qualify for a home loan under 4.0 are either “dormant” or “newly scorable,” according to the report. Both groups are pretty much ignored by traditional scoring systems.

Dormant consumers, which account for 91% of the unscored population with scores above 620, are infrequent users of credit but have activity beyond the normal six-month threshold. For example, that guy who paid cash for his wheels would be scored by 4.0 but not by the current FICO program.

The other 9% are new to credit or have “young” credit files. This group has established credit, but their files are less than six months old. They receive a score of 4.0 on the day a tradeline is reported. About three-quarters of them also have a score of 620 or higher because they, too, pay on time.

To score these consumers, 4.0 uses non-traditional statistical methods. The company’s data scientists apply machine learning techniques that it says are “at the forefront” of artificial intelligence to identify the criteria that best predict future default.

To test the model, VantageScore compared 4.0 to conventional scoring models and found that predicted default rates were similar. “Therefore,” the paper says, “lending decisions can be consistent for newly and conventionally scorable consumers.”

One major lender has already incorporated 10-T into its system, and VantageScore expects some of its customers to do the same with 4.0 “soon,” Hutchinson said. Those who do so sooner than the legislated deadline will have a leg up on those who wait until the last minute, he warned.

Implementing the new systems “will benefit millions of consumers who are currently underserved or excluded from home ownership,” he said. Not to mention lenders’ bottom lines.