What’s in a Credit Score? More than You Might Think, and It’s Constantly Changing


Editor’s note:  DataQuick®, a provider of
advanced real estate information solutions recently announced that Gordon
Crawford, Ph.D. had joined their firm as vice president of Analytics.  MND doesn’t normally note such appointments,
but it caught our eye that Crawford who until recently was
president of Mortgage Research a
t Fannie Mae, is
an expert on credit scoring performance models and spoke about that
topic at a recent Mortgage Bankers Association Risk Conference.  He was kind enough speak with us on the topic
while preparing for that meeting.

While a lot of us can now actually sing
the words, the original screwball television commercials about credit scores marked
the first time many people ever heard the words.  Dr. Crawford told us that until recently credit
scoring was sort of a “black box” for consumers.   Compared
to credit reports, scoring is a relatively young credit tool, and even after consumers
learned they had a score, many had no real idea of what that meant.

In the last few years FICO, the main
purveyor of credit scoring technology, and other providers have worked to
educate borrowers, providing information about what goes into credit scores and
consumer guides on how to improve them.  Another
recent consumer innovation is the ability to do credit score
simulations online. 

Using one of these simulators a consumer
can, for example, test the effect of paying off one debt entirely in contrast
to paying a portion of another or whether opening a new line of credit will
have a positive or negative effect. 
This, Crawford said, is a double edged sword.  Credit scoring companies now know that these
simulators have given consumers the ability to game the system and must take
this into account whenever they make changes to their models.  “People should know what is in their score and
how to improve it,” he said, “but being able to manipulate it can invalidate
the scorer’s model.”  

In two respects credit scoring is not a
static science.  From the consumer
standpoint, Crawford said that what were considered acceptable credit scores before
then started to decline in 2002.  A score
of 700
used to be considered good, then 660; then suddenly it was 580.  That trend flipped in 2008 and since then
scores have ramped up to what is now a 760 to 780 average for what is
considered a prime score.  “We now have a
strange situation,” he said, “with very low interest rates but very tight
access to credit.  What used to be
considered a good score, 720, is now one where lenders have to propose
alternative programs.  We have swung from
a standard that was way much low to one that is probably too high.”

From a lender standpoint credit scoring
doesn’t stand still either.  Crawford
said that vendors frequently update scoring models and the industry is
challenged by this because it is not easy to adapt.  All credit scoring is predicated on a FICO
model and changing one necessitates changing or at least tweaking others.  Existing pricing and underwriting models are
also already calibrated to old scoring, making it costly to put new ones in
place.  Consequently lenders want to see substantive
changes or ones that provide measurable benefits before they undertake the trouble
and expense of training their people and changing their systems in order to accommodate

A case in point is a new model recently
introduced by FICO
which introduces data from a new CoreLogic credit report
into the scoring and thus gives weight to such information, according to FICO “as
property transaction data, landlord/tenant data, borrower-specific public data,
and other alternative credit data.  FICO
maintains that the new model raises the scores of many borrowers – about 3
percent more individuals would score above the current 715 median – and has a
predictive value of risk performance 7-1/2 times greater than current models.

Crawford said “Newer measures to beef up
thinner files need to be proven out.  If
one lender adopts a new model and others don’t follow then it is hard for him
transfer a loan or its servicing, sell the loan on the secondary market, or
communicate about that loans and its risk. 
He risks losing common measures with other lenders.”

Besides, Crawford said, lenders are
right now with the tighter underwriting standards.  Behind their concerns about any loosening of them
is an uncertainty both about the capital levels that will be required for
holding mortgages and about the future of Fannie Mae and Freddie Mac.  “Until they have a higher comfort level they
won’t be willing to accept more exposure to risk.” 

He said that lenders, of course, use
credit scoring as one in a whole arsenal of tools when they evaluate risk;
appraisals, owner occupancy status, and other factors all enter into the
equation.  In addition, Crawford said,
credit scores are intended to predict success with a loan, not necessarily to
predict success with a mortgage loan.  For
this reason many lenders beef up scores by taking specific fields from them –
for example the utilization rate of revolving debt – and wrapping them into
their underwriting, thus multiplying the weight they carry.

Crawford’s role at DataQuick will involve
developing all models and analytics, including home price indices, automated
property valuation models and loan performance models.  While at Fannie Mae he worked on performance
models used to determine loss allowance measures and pricing.  Crawford earned
a Bachelor of Arts in Economics from Brigham Young University and both a Master
of Arts and a doctorate in Economics from the University of Rochester.  

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