40 December 2017
discoveries is that by the time a financial institution
gets the feedback, it is too late to mitigate the
situation. Another issue is that the lack of rapid
feedback gives management a false sense of security
about their fraud risk. Insufficient fraud detection
practices or an undetected scheme could continue
for years. Finally, the types of fraud most likely to be
discovered early are not representative of overall
fraud risk. This can create a skewed picture and could
lead to poorly-informed risk management decisions.
WHEN AND HOW IS MORTGAGE
ORIGINATION FRAUD DISCOVERED?
There are several times over the life of a loan that
fraud can be discovered:
Prior to the loan closing – Of course, this is the
best time to discover and prevent it. Verification
processes, up-front fraud tools, underwriting, and
pre-fund quality control account for most of these
discoveries. Unfortunately, few institutions have
strong tracking mechanisms to determine how
much fraud is being averted, which loans, and what
method accounted for the detection. This is a missed
Standard post-fund QC reviews by originating
lender – Depending on the size of the institution,
QC sampling usually looks at about 10% or less of
the loan population. This may be supplemented
with an adverse or targeted sample. QC reviews are
completed the first two to three months after closing.
They usually include new verifications including credit
reports, income, and asset verifications. Fraud can
easily go undetected in a QC review because it is not
a fraud-specific review. Credit reports will consistently
show most new debts, but asset reverifications may
not be returned and may just show the current asset
picture versus what it was at the time of the original
asset document. Income verifications may not be
returned, or if part of a collusive scheme, be returned
with false information again. Fraud found in these
reviews are most likely to be undisclosed liabilities or
job loss that happened prior to closing. Organized
schemes usually are sophisticated enough to pass
through this type of review.
Investor QC – Investors typically perform some level
of QC in the first few months after origination. Again,
fraud is not the primary focus of these reviews and
they are also most likely to find undisclosed liabilities
and job loss prior to closing. Indemnifications or
repurchase requests are possible outcomes.
Early Payment Default (EPD) reviews – Loans
that become 60 to 90 days delinquent in their first
six to 12 months are often subjected to a special
QC review. Fraud found in these reviews will be
like the earlier post-fund QC reviews, however,
a higher percentage of the reviewed population
will have issues. Unsophisticated fraud schemes
(such as a one-off straw buyer flip) that defaulted
immediately are often detected in this type of review.
Indemnification or repurchase requests are likely if
loan was sold with reps and warrants in the contract.
Severe loss reviews – Many investors will perform
QC or root cause analysis on loans with large losses,
even those aged more than a year. Egregious frauds
and schemes may be detected here, and recourse
will be sought from the originator.
Fraud investigations – These take place over the life
of the loan, and are usually triggered by a tip about
a particular loan, loan officer, appraiser or a fraud
scheme. As the investigation continues, the sample
will broaden as related loans are identified. This is
where most fraud schemes are fully identified. Again,
recourse from the originator will be an outcome if it
was purchased with reps and warrants in the contract.
EARLY FEEDBACK BIAS
As time progresses, different types of fraud are
likely to emerge. Because standard post-fund QC
reviews do not provide a good picture of the level of
fraud or the type of fraud in loans originated, relying
on QC results as the only indicator of fraud risk levels
can be misleading.
As we have seen, these reviews tend to skew
towards undisclosed liabilities and miss other types
of fraud. A good example of how risks shift over
time can be seen in Fannie Mae’s monthly reporting.
The figure below, for example, looks at a 2015
vintage portfolio at two different points and shows