the changing types and levels of fraud risk. A
difference of 16 months dramatically changed the
breakdown of fraud types. As the vintage continues
to age, liabilities will likely continue to shrink.
Early feedback from QC reviews may bias risk
managers and operations managers to target just
the specific issues that were the focus of review.
For example, the large share of liabilities-as-a-fraud
type provides the most immediate feedback, so
lenders may focus on this risk to the exclusion of the
broader fraud picture. The issues that emerge later
may not garner the same level of attention or root
cause analysis and prevention focus. But these later
discoveries are those that come from the defaulted
loans – the issues that are more likely tied to loss.
THE ROLE OF PREDICTIVE ANALYTICS
As we have seen, mortgage origination fraud
may have a long discovery delay, and different types
of fraud are more likely to emerge at different times.
For these reasons by the time a problem has been
identified, it may have become very large. To prevent
this, we need to know which loans are more likely to
have fraud, either to target prevention efforts, or to
measure risk levels and trend changes.
At CoreLogic, we have the benefit of a
consortium-based population of millions of loan
applications, and thousands of examples of loans
with fraud. We use these populations for predictive
modeling. The current model incorporates the most
predictive features based on analysis of over 2000
data points regarding loan, borrower, and property
elements. The output is a risk ranking score from
1-999. As a point of reference, the score identifies 60
percent of fraud in the top 10 percent of scores. Our
clients use the score trends to monitor their fraud risk
levels over time and benchmark against the entire
We also compile the consortium scores into a
National Mortgage Application Fraud Index. This
is available publicly and is updated quarterly. The
index is a tool that lenders can reference to gauge
the increasing or decreasing risk levels over time.
Because it was modeled from loans that had time to
season, and includes both pre-fund and post-fund
findings, it provides a complete picture of current
mortgage origination fraud risk. (You can learn more
about the index, find our quarterly updates, and
annual mortgage fraud reports at corelogic.com.)
As of the second quarter of 2017, we are seeing
the highest risk level since we began our index in
2010, so this is a good time to evaluate whether
your institution is focused on a short-term view of
mortgage fraud, or a long-term view.