policies. In order to limit scrutiny around exceptions,
lenders may want to consider tighter controls around
exceptions and general underwriting procedures
before the data is reported.
HMDA data fields, such as the combined loan-to-value
(CLTV) ratio, credit-score and debt-to-income (DTI)
ratio, are important variables that may be used in
credit decisions and loan pricing — and thereby are
typically involved in focal-point reviews and regression analysis.
If the denial rate for a group of borrowers fails a
benchmark test, or is tested to be statistically significant, that could become a focal point during the next
regulator exam, and may implicate redlining or perhaps reverse-redlining concerns. Therefore, it is critical
for these fields to be accurate.
Demographic information may be the most challenging and complicated area for data collection,
data integrity and data analysis — and could impact
marketing, redlining, pricing, underwriting and servicing fair-lending analytics. Lenders need to be confident that they understand the many nuances and
complexities of the rules relating to the aggregate,
disaggregate and free-form text categories.
Lenders should monitor the volume of applications
received from applicants that designate their race or
ethnicity within these new subcategories in order to
begin the analysis on these populations as soon as
possible. Similar to many of these other newly reported
fields, lenders should know whether there are issues
within the more granular data that may be masked in
the aggregate-data reporting.
Pulling a rabbit out of a hat may seem like a much
easier feat to accomplish than analyzing the new
HMDA data. For all lenders, however, it is time to start
analyzing this new data to better understand how this
information will be viewed — and originators also
should be clued into these processes and results. The
time to act is now to devise a strategy to ensure that
fair-lending analytics will be something to celebrate. n
Also, core business, compliance and marketing strategies that have been put into place based on data collected prior to the new HMDA rule being implemented
may need to be revisited and updated based on the
data profile that will be created from this new data.
Following are some of the biggest changes that
should be considered when re-examining your
Previously optional to HMDA reporting, the now-required reporting of dwelling-secured, open-ended
lines of credit (commonly known as a home equity line
of credit, or HELOC) may be the single most impactful
change of all of the new reporting requirements. This
is for two reasons: the portfolio nature of the product,
and the overall volume of reporting for these transactions.
For products such as HELOCs that are likely to be
retained in portfolio, credit exceptions are believed to
be more likely to occur, as an institution would not
have to answer to an investor on these determinations. Additionally, underwriting and pricing criteria
may not have been developed in as rigorous a process
as traditional first-mortgage loans.
This added level of discretion without an appropriate level of controls could result in a higher degree of
risk for potential discrimination on a prohibited basis
now that this data is readily available for examination.
Therefore, lenders should examine the credit and
pricing policies and controls to ensure that the HELOC
criteria are empirically derived. This would be in addition to performing fair-lending analysis, monitoring
and testing to ensure that the policies are equally
applied to all applicants.
Additionally, the sheer number of HELOCs could
potentially shift ratios and statistics for an institution
in dramatic fashion. The introduction of a large population of HELOCs within the HMDA data, for example,
will undoubtedly impact redlining analysis, which has
been a hot topic for regulatory scrutiny for the past
several years. It may take a lot of time for institutions
to adjust to these new volume measures, so it’s critical
to start doing analytics as soon as possible to determine the impact of this new data on the lending
New York state of mind
Specific to the state of New York only, transactions involving a loan consolidation, extension and modification agreement (CEMA) are now reportable under the
new HMDA rules. For New York lenders, this could be a
significant portion of the loan-application population.
Institutions should begin to perform analysis on this
new HMDA-reportable population. They will need to
determine if the addition of CEMA reporting results in
On another front and affecting all lenders, unsecured home-improvement loans deemed consumer
transactions (nonbusiness-purpose transactions) will
no longer be reportable under HMDA. If previous
analysis is included on this population of borrowers,
that analysis should be updated in order to understand the impact and changes year over year.
In addition, previously optional to report, pre-
Expanded data fields
approval requests are now required reporting under
the new HMDA rules. The addition of pre-approval data
will add more records to the reporting for those institu-
tions that participate in a pre-approval program.
Certainly, the expanded data fields are the area of
significant focus, as the data can now be evaluated
in many ways, singularly and combined, and can thus
yield much more information about each application.
It is critical to be proactive, and consider the fields that
have the highest potential impact. Following are of
some of the fields that should be considered in that
Application channels. The application-channel
reporting added into the mix of the HMDA data
introduces an interesting wrinkle in the fair-lending
analytics. If a lender participates in both direct and
indirect lending, separate analysis by channel may
yield disparities that were previously hidden within
the analysis of the aggregate data.
Because only a small number of loans could mask
problems, lenders who engage in both direct and indirect lending should begin to understand how their
data may be viewed separately — before the regulators have access to the data. If lenders are currently
performing regression or other robust analysis,
these institutions should also begin to bifurcate the
approach in order to determine if a single channel may
surface hidden issues.
Fees and interest rates. The expanded HMDA
reporting includes several pricing fields, including
the fees associated with a loan (origination charges,
discount points and total loan costs); lender credits;
and the interest rate. Because of the impact of these
fields on the APR [annual percentage rate] calculation and pricing decisions, data-integrity controls and
robust analysis needs to be put in place to ensure that
these criteria are assessed individually, as well as in the
aggregate APR-calculated field.
Lenders should know which of their borrowers are
charged discount points, for example, and the degree
to which these points benefit the borrower. There
also might be some trends or customs by regions that
may need to be accounted for to ensure that a lender
can accurately tell their story when interpreting the
data and discussing any apparent differences with
Prepayment penalties and non-amortizing
features. These loan features have had a negative
perception associated with them over the past few
years. Institutions need to understand the distribution
of these elements to ensure that there is no disproportionate distribution of these components across
Automated underwriting-system results. The
automated-underwriting results will provide the regulators a clearer view into exceptions to underwriting
<< HMDA continued from Page 86 “Pulling a rabbit out of a hat may
seem like a much easier feat to
accomplish than analyzing the
new HMDA data.”