Small Business Administration
Actions Needed to Improve the Usefulness of the Agency's Lender Risk Rating System Gao ID: GAO-10-53 November 6, 2009The Small Business Administration (SBA) guarantees individual loans that lenders originate. The agency uses its Loan and Lender Monitoring System (L/LMS) to assess the individual risk of each loan, and SBA's contractor developed a lender risk rating system based on L/LMS data. However, questions have been raised about the extent to which SBA has used its lender risk rating system to improve its oversight of lenders. The Government Accountability Office (GAO) was asked to examine (1) how SBA's risk rating system compares with those used by federal financial regulators and lenders and the system's usefulness for predicting lender performance and (2) how SBA uses the lender risk rating system in its lender oversight activities. To meet these objectives, GAO reviewed SBA documents; interviewed officials from three federal financial regulators and 10 large SBA lenders; analyzed SBA loan data; and interviewed SBA officials.
SBA's lender risk rating system uses some of the same types of information that federal financial regulators and selected large lenders use to conduct off-site monitoring, but its usefulness has been limited because SBA has not followed common industry standards when validating the system--that is, assessing the system's ability to accurately predict outcomes. Like the federal financial regulators and 10 large lenders GAO interviewed, SBA's contractor developed lender risk ratings based on loan performance data and prospective, or forward-looking, measures (such as credit scores). Using SBA data, GAO undertook a number of evaluative steps to test the lender risk rating system's predictive ability. GAO found that the system was generally successful in distinguishing between higher- and lower-risk lenders, but it better predicted the performance of larger lenders. However, the system's usefulness was limited because the contractor did not follow validation practices, such as independent and ongoing assessments of the system's processes and results, consistent with those recommended by federal financial regulators and GAO's internal control standards. For example, the agency did not require a party other than the one who developed the system to perform the validation, and SBA's contractor did not routinely reassess the factors used in the system as part of its validations. Further, SBA does not use its own data to develop alternate measures of lender performance that could be used to independently assess or supplement the risk ratings, citing resource constraints. Because SBA does not follow sound validation practices or use its own data to independently assess the risk ratings, the effectiveness of its lender risk rating system--the primary system SBA relies on to monitor and predict lender performance--may deteriorate as economic conditions and industry trends change over time. Although SBA's lender risk rating system has enabled the agency to conduct some off-site monitoring of lenders, the agency does not use the system to target lenders for on-site reviews or to inform the scope of the reviews. Unlike the Federal Deposit Insurance Corporation and the Federal Reserve, which use their off-site monitoring tools to target lenders for on-site reviews, SBA targets for review those lenders with the largest SBA-guaranteed loan portfolios. As a result of this approach, 97 percent of the lenders that SBA's risk rating system identified as high risk in 2008 were not reviewed. Further, GAO found that the scope of the on-site reviews that SBA performs is not informed by the lenders' risk ratings, and the reviews do not include an assessment of lenders' credit decisions. The federal financial regulators use the results of off-site monitoring to identify which areas of a bank's operations they should review more closely. Moreover, their reviews include an assessment of the quality of the lenders' credit decisions. Federal financial regulators are able to use review results to update their off-site monitoring systems with data on emerging lending trends. Regardless of the lender's risk rating, SBA relies on a standard on-site review form that includes an assessment of lenders' compliance with SBA policies and procedures but not an assessment of lenders' credit decisions. According to SBA officials, it is not the agency's role to assess lenders' credit decisions. Without targeting the most risky lenders for on-site reviews or gathering information related to lenders' credit decisions, SBA cannot effectively assess the risk posed by lenders or ensure that its lender risk rating system incorporates updated information on emerging lending trends.
RecommendationsOur recommendations from this work are listed below with a Contact for more information. Status will change from "In process" to "Open," "Closed - implemented," or "Closed - not implemented" based on our follow up work.
Director: Team: Phone:GAO-10-53, Small Business Administration: Actions Needed to Improve the Usefulness of the Agency's Lender Risk Rating System
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Report to Congressional Requesters:
United States Government Accountability Office:
GAO:
November 2009:
Small Business Administration:
Actions Needed to Improve the Usefulness of the Agency's Lender Risk
Rating System:
GAO-10-53:
GAO Highlights:
Highlights of GAO-10-53, a report to congressional requesters.
Why GAO Did This Study:
The Small Business Administration (SBA) guarantees individual loans
that lenders originate. The agency uses its Loan and Lender Monitoring
System (L/LMS) to assess the individual risk of each loan, and SBA‘s
contractor developed a lender risk rating system based on L/LMS data.
However, questions have been raised about the extent to which SBA has
used its lender risk rating system to improve its oversight of lenders.
GAO was asked to examine (1) how SBA's risk rating system compares with
those used by federal financial regulators and lenders and the system‘s
usefulness for predicting lender performance and (2) how SBA uses the
lender risk rating system in its lender oversight activities. To meet
these objectives, GAO reviewed SBA documents; interviewed officials
from three federal financial regulators and 10 large SBA lenders;
analyzed SBA loan data; and interviewed SBA officials.
What GAO Found:
SBA‘s lender risk rating system uses some of the same types of
information that federal financial regulators and selected large
lenders use to conduct off-site monitoring, but its usefulness has been
limited because SBA has not followed common industry standards when
validating the system”that is, assessing the system‘s ability to
accurately predict outcomes. Like the federal financial regulators and
10 large lenders GAO interviewed, SBA‘s contractor developed lender
risk ratings based on loan performance data and prospective, or forward-
looking, measures (such as credit scores). Using SBA data, GAO
undertook a number of evaluative steps to test the lender risk rating
system‘s predictive ability. GAO found that the system was generally
successful in distinguishing between higher- and lower-risk lenders,
but it better predicted the performance of larger lenders. However, the
system‘s usefulness was limited because the contractor did not follow
validation practices, such as independent and ongoing assessments of
the system‘s processes and results, consistent with those recommended
by federal financial regulators and GAO‘s internal control standards.
For example, the agency did not require a party other than the one who
developed the system to perform the validation, and SBA‘s contractor
did not routinely reassess the factors used in the system as part of
its validations. Further, SBA does not use its own data to develop
alternate measures of lender performance that could be used to
independently assess or supplement the risk ratings, citing resource
constraints. Because SBA does not follow sound validation practices or
use its own data to independently assess the risk ratings, the
effectiveness of its lender risk rating system”the primary system SBA
relies on to monitor and predict lender performance”may deteriorate as
economic conditions and industry trends change over time.
Although SBA‘s lender risk rating system has enabled the agency to
conduct some off-site monitoring of lenders, the agency does not use
the system to target lenders for on-site reviews or to inform the scope
of the reviews. Unlike the Federal Deposit Insurance Corporation and
the Federal Reserve, which use their off-site monitoring tools to
target lenders for on-site reviews, SBA targets for review those
lenders with the largest SBA-guaranteed loan portfolios. As a result of
this approach, 97 percent of the lenders that SBA‘s risk rating system
identified as high risk in 2008 were not reviewed. Further, GAO found
that the scope of the on-site reviews that SBA performs is not informed
by the lenders‘ risk ratings, and the reviews do not include an
assessment of lenders‘ credit decisions. The federal financial
regulators use the results of off-site monitoring to identify which
areas of a bank‘s operations they should review more closely. Moreover,
their reviews include an assessment of the quality of the lenders‘
credit decisions. Federal financial regulators are able to use review
results to update their off-site monitoring systems with data on
emerging lending trends. Regardless of the lender‘s risk rating, SBA
relies on a standard on-site review form that includes an assessment of
lenders‘ compliance with SBA policies and procedures but not an
assessment of lenders‘ credit decisions. According to SBA officials, it
is not the agency‘s role to assess lenders‘ credit decisions. Without
targeting the most risky lenders for on-site reviews or gathering
information related to lenders‘ credit decisions, SBA cannot
effectively assess the risk posed by lenders or ensure that its lender
risk rating system incorporates updated information on emerging lending
trends.
What GAO Recommends:
GAO recommends that SBA ensure that its contractor, consistent with
industry standards, follows sound model validation practices, use its
own data to assess the lender risk rating system, develop a strategy
for targeting lenders for on-site reviews that relies more on its
lender risk ratings, and consider revising its on-site review policies
and procedures. In responding to a draft of this report, SBA generally
agreed with these recommendations and outlined some steps that it plans
to take to address them.
View [hyperlink, http://www.gao.gov/products/GAO-10-53] or key
components. For more information, contact William B. Shear at (202) 512-
8678 or shearw@gao.gov.
[End of section]
Contents:
Letter:
Results in Brief:
Background:
SBA's Lender Risk Rating System Is Similar to Those Used by Federal
Financial Regulators but Is Limited by Insufficient Validation:
SBA Does Not Use Lender Risk Ratings to Target Lenders for On-Site
Review or Tailor the Scope of the Reviews:
Conclusions:
Recommendations for Executive Action:
Agency Comments and Our Evaluation:
Appendix I: Objectives, Scope, and Methodology:
Appendix II: Comments from the Small Business Administration:
Appendix III: Predictive Performance of the March 2007 and March 2008
Lender Risk Ratings:
Appendix IV: Small Business Predictive Score:
Appendix V: GAO Contact and Staff Acknowledgments:
Tables:
Table 1: Sources of Data Used to Calculate Lender Risk Ratings for 7(a)
Lenders:
Table 2: Comparison of Alternative Rankings and Rankings Based on 2007
Lender Risk Rating Raw Scores, 2007 Currency Rates, and 2008 Lender
Risk Rating Raw Scores for 7(a) Lenders:
Table 3: Comparison of Alternative Rankings and Rankings Based on 2007
Lender Risk Rating Raw Scores, 2007 Currency Rates, and 2008 Lender
Risk Rating Raw Scores for 504 Lenders:
Table 4: Results of Correlation Analysis:
Table 5: Predictive Ability of SBPS for Loans below and above $150,000:
Figures:
Figure 1: SBA's Lender Risk Rating Process for 7(a) Lenders:
Figure 2: Data Used for Off-Site Monitoring:
Figure 3: Commonly Accepted Validation Practices and SBA's Practices:
Figure 4: SBA On-Site Reviews, 2005 to 2008:
Abbreviations:
Basel Committee: Basel Committee on Banking Supervision:
FDIC: Federal Deposit Insurance Corporation:
Federal Reserve: Board of Governors of the Federal Reserve System:
L/LMS: Loan and Lender Monitoring System:
NAICS: North American Industry Classification System:
OCC: Office of the Comptroller of the Currency:
SBA: Small Business Administration:
SBPS: Small Business Predictive Score:
[End of section]
United States Government Accountability Office:
Washington, DC 20548:
November 6, 2009:
The Honorable Mary L. Landrieu:
Chair:
The Honorable Olympia J. Snowe:
Ranking Member:
Committee on Small Business and Entrepreneurship:
United States Senate:
The Honorable Richard J. Durbin:
Chairman:
The Honorable Susan M. Collins:
Ranking Member:
Subcommittee on Financial Services and General Government:
Committee on Appropriations:
United States Senate:
In April 2003, the Small Business Administration (SBA) obtained a loan
monitoring service from Dun & Bradstreet to help manage and oversee the
lending and risk management activities of lenders that extend 7(a) and
504 loans to small businesses. The 7(a) and 504 loan programs, named
after the sections of the acts that authorized them, are SBA's two
major business loan guarantee programs.[Footnote 1] As of June 30,
2009, SBA had an outstanding portfolio of $67.6 billion in 7(a) and 504
loans. Because SBA guarantees the individual loans that lenders
originate, it uses the Dun & Bradstreet service, now called the Loan
and Lender Monitoring System (L/LMS), to monitor the individual risk
that each loan poses to the agency in order to identify those lenders
whose SBA loan operations and portfolios may require additional
monitoring or other actions. In 2004, we reviewed the service and found
that it was a positive and necessary step in improving SBA's oversight
of lenders but determined that the agency needed to develop policies
and procedures to ensure that it used the service in a way that
resulted in improved oversight of lenders.[Footnote 2] Since we issued
our report in June 2004, SBA has made progress in developing policies
for using L/LMS and expanding its use. For example, SBA hired a
contractor to develop a lender risk rating system (that is, an off-site
monitoring tool that produces a risk score for each lender) based on L/
LMS data. This system enabled SBA for the first time to monitor the
approximately 4,000 smaller lenders that it had not previously
reviewed. However, questions have been raised about the extent to which
SBA has used its lender risk rating system to improve its oversight of
lenders--for example, to target lenders for on-site review. The SBA
Inspector General reported in May 2008 that SBA had been unable to
sufficiently mitigate the risk posed by lenders that it had identified
as high risk and that SBA's 7(a) program had incurred a cumulative net
loss for four lenders of $329 million as of September 2007.[Footnote 3]
You asked us to review SBA's lender risk rating system and its effect
on the agency's lender oversight program. Specifically, this report
examines (1) how SBA's risk rating system compares with the off-site
monitoring tools used by federal financial regulators and lenders and
the system's usefulness for predicting lender performance and (2) how
SBA uses the lender risk rating system in its lender oversight
activities.
To determine how SBA's lender risk rating system compares with off-site
monitoring tools used by federal financial regulators and lenders, we
compared SBA's system with common industry standards that we identified
through interviews and document reviews. We interviewed officials from
three federal financial regulators--the Office of the Comptroller of
the Currency (OCC), the Board of Governors of the Federal Reserve
System (Federal Reserve), and the Federal Deposit Insurance Corporation
(FDIC)--five of the largest 7(a) lenders, and the five largest 504
lenders.[Footnote 4] We also reviewed relevant literature and analyzed
procedural manuals and other related federal guidance to banks on loan
portfolio monitoring. Although we interviewed federal financial
regulators and reviewed agency documents explaining their off-site
monitoring practices, we did not evaluate their practices, such as by
testing their models. In addition, we compared the techniques that SBA
and its contractor used to develop and validate the lender risk rating
system to our internal control standards.[Footnote 5] To determine the
usefulness of the lender risk ratings in predicting lender performance,
we reviewed documents from SBA and its contractor that described the
factors used in the risk rating system and the process for calculating
the risk rating scores. We also obtained and analyzed the following SBA
data: data on loans approved in 2003 through the end of 2007, the March
2007 and March 2008 lender risk ratings, and the currency rate for each
lender.[Footnote 6] We assessed the reliability of these data and found
them to be sufficiently reliable for our purposes. Using these data, we
undertook a number of evaluative steps to test SBA's model. After we
discussed SBA's modeling approach in detail with SBA officials and the
agency's contractor to document the process used to develop the model,
we developed statistical estimation techniques to assess how well SBA's
risk rating system predicts lender performance. In particular, we
compared the scores from the lender risk rating system to lenders'
actual performance and alternate measures of lender performance that we
developed using SBA data. To determine how SBA uses the lender risk
rating system in its lender oversight activities, we compared SBA's
practices for assessing and monitoring the risk of lenders and loan
portfolios against (1) the industry standards we identified through our
interviews and document reviews and (2) our internal control standards.
We also obtained and analyzed SBA data on risk ratings and on-site
examinations from 2005 through 2008 to determine the characteristics of
lenders that received on-site exams.
We conducted this performance audit from August 2008 to November 2009
in accordance with generally accepted government auditing standards.
Those standards require that we plan and perform the audit to obtain
sufficient, appropriate evidence to provide a reasonable basis for our
findings and conclusions based on our audit objectives. We believe that
the evidence obtained provides a reasonable basis for our findings and
conclusions based on our audit objectives. Appendix I contains a full
description of our objectives, scope, and methodology.
Results in Brief:
SBA's lender risk rating system uses some of the same types of
information that federal financial regulators and selected large
lenders use to conduct off-site monitoring. But the system's usefulness
has been limited because SBA has not followed common industry standards
when validating the system--that is, assessing the system's ability to
accurately predict outcomes. Like the 3 federal financial regulators
and 10 large lenders we interviewed, SBA's contractor developed the
lender risk rating system using loan performance data and prospective,
or forward-looking, measures (such as credit scores). We independently
assessed the lender risk rating system and found that it was generally
successful in distinguishing between high-and low-risk lenders, but it
better predicted the performance of larger lenders. However, the
system's usefulness was limited because the contractor did not follow
validation practices, such as independent and ongoing assessments of
the system's processes and results, consistent with those recommended
by federal financial regulators and our internal control standards. For
example, the agency did not require a party other than the one who
developed the system to perform the validation, and SBA's contractor
did not routinely reassess the factors used in the system as part of
its validations. Further, SBA officials stated that resource
constraints prevented them from using internally generated data to
develop alternate measures of lender performance that could be used to
independently assess or supplement the risk ratings. Federal financial
regulator guidance and our internal control standards suggest that
organizations should use their own data to assess the performance of
risk rating systems developed by vendors. Because SBA does not follow
sound validation practices or use its own data to independently assess
the risk ratings, the effectiveness of its lender risk rating system--
the primary system SBA relies on to monitor and predict lender
performance--may deteriorate as economic conditions and industry trends
change over time. According to SBA officials, the agency's contractor
is currently redeveloping the system because its performance has
deteriorated in recent years.
Although SBA's lender risk rating system has enabled the agency to
perform some off-site monitoring of lenders, the agency does not use
the system to target lenders for on-site review or to inform the scope
of those reviews. FDIC and the Federal Reserve use their off-site
monitoring tools to target lenders for on-site reviews. SBA uses its
risk rating system to monitor lenders and portfolio trends but does not
rely on it to target the riskiest 7(a) and 504 lenders for on-site
review. Instead, SBA focuses on what it thinks is the most important
risk indicator--portfolio size--and targets for review those lenders
with the largest SBA-guaranteed loan portfolios--that is, 7(a) lenders
with at least $10 million in their guaranteed loan portfolio and 504
lenders with balances of at least $30 million. Of the 477 reviews SBA
conducted from 2005 through 2008, 380 (80 percent) were of large
lenders that, based on its lender risk rating system, posed limited
risk to SBA. The remaining 97 reviews (20 percent) were of lenders that
posed significant risk to the agency. As a result, the vast majority of
high-risk lenders were not reviewed. For example, in 2008, 97 percent
of the 1,587 lenders identified as high risk were not reviewed. Of
these lenders, 215 had an outstanding portfolio of at least $4 million.
Because SBA relies on a lender's size to target lenders for on-site
reviews, smaller lenders with high-risk ratings that may still have
significant portfolios of SBA loans have been allowed to participate in
SBA's loan programs with little or no oversight. In addition, SBA does
not use the lender risk rating system to determine the scope of on-site
reviews and does not assess lenders' credit decisions during these
reviews. Federal financial regulators we contacted use the results of
off-site monitoring to identify which areas of a bank's operations they
should review more closely. Moreover, their reviews include an
assessment of the quality of lenders' credit decisions. These practices
provide information on emerging trends in lending that regulators can
use to update their off-site monitoring tools. Finally, internal
control standards require that all federal agencies identify and
analyze risks and determine the best way to manage or mitigate them.
However, regardless of lenders' risk ratings, SBA relies on a standard
on-site review form that includes an assessment of lenders' compliance
with SBA policies and procedures but not an assessment of lenders'
credit decisions. For example, SBA examiners determine whether lenders
have ensured that borrowers met eligibility requirements. SBA officials
told us that it was not the agency's role to assess lenders' credit
decisions. However, we believe that because SBA relies on lenders with
delegated underwriting authority to make the majority of its loans, the
agency should take a more active role in ensuring that these lenders
are making sound credit decisions. Without targeting the riskiest
lenders for on-site reviews or gathering information related to
lenders' credit decisions, SBA cannot effectively assess lenders' risk
or update its risk rating system based on emerging lending trends.
This report contains four recommendations designed to improve SBA's use
of its lender risk rating system and oversight of its lenders. We are
recommending that SBA ensure that its contractor follows sound model
validation practices, including testing of the lender risk rating
system data, processes, and results; utilizing an independent party to
perform its validations; and maintaining complete documentation of the
validation process and results. We also are recommending that SBA use
its own data to assess the lender risk rating system, develop a
strategy for targeting lenders for on-site reviews that relies more on
its lender risk ratings, and consider revising its on-site review
policies and procedures. We provided SBA with a draft of this report
for its review and comment. In written comments, SBA stated that it
generally agreed with our recommendations and outlined some steps that
it plans to take to address them. For example, the agency noted that it
is currently undertaking a redevelopment of its lender risk rating
system and plans to ensure that best practices are incorporated into
the redevelopment validation process. SBA's comments are reprinted in
appendix II.
Background:
In pursuing its mission of aiding small businesses, SBA provides them
with access to credit, primarily by guaranteeing loans through its 7(a)
and 504 loan programs. The 7(a) and 504 loan guarantee programs are
intended to serve small business borrowers who could not otherwise
obtain credit under reasonable terms and conditions from the private
sector without an SBA guarantee. Under the 7(a) program, SBA generally
provides guarantees of up to 85 percent on loans made by participating
lenders that are subject to program oversight by SBA.[Footnote 7] Many
of these participating lenders are preferred lenders that have
delegated underwriting authority. Loan proceeds can be used for most
business purposes, including working capital, equipment, furniture and
fixtures, land and buildings, leasehold improvements, and certain debt
refinancing. The 504 program provides long-term, fixed-rate financing
to small businesses for expansion or modernization, primarily of real
estate. Financing for 504 loan programs is delivered through about 270
certified development companies, nonprofit corporations that were
established to contribute to the economic development of their
communities. For a typical 504 loan project, a third-party lender
provides 50 percent or more of the financing pursuant to a first-lien
mortgage, a certified development company provides up to 40 percent of
the financing through a debenture that is fully guaranteed by SBA, and
a borrower contributes at least 10 percent of the financing.[Footnote
8] Although SBA's 7(a) and 504 loan guarantee programs serve different
needs, both programs rely on third parties to originate loans
(participating lenders for 7(a) loans and certified development
companies for 504 loans). Because SBA generally guarantees up to 85
percent of the 7(a) loans and up to 40 percent of the financing for 504
loan projects, SBA faces the same kind of risk as the lenders if the
loans are not repaid.
The Small Business Programs Improvement Act of 1996 required SBA to
establish a risk management database that would provide timely and
accurate information to identify loan underwriting, collections,
recovery, and liquidation problems.[Footnote 9] In 2003, SBA obtained a
service from Dun & Bradstreet that would allow it to, among other
things, predict the likelihood of a loan defaulting using a combination
of SBA performance data and loan-level credit data. In 2004, we
assessed the new service and found that the system was on par with
industry best practices by providing a tool that could help SBA better
assess the risk exposure of loans in its lenders' portfolios.[Footnote
10] For example, we reported that the Small Business Predictive Score
(SBPS), which is provided through the Dun & Bradstreet service,
appeared to be consistent with private sector best practices because it
was based on sound models.[Footnote 11] The models used to score the
loans rely on data managed by Dun & Bradstreet and are commercial, off-
the-shelf risk scoring models developed by Fair Isaac and validated to
SBA's 7(a) and 504 portfolios. We concluded that without the Dun &
Bradstreet service, it was unlikely that SBA would be able to continue
the same level of risk management of its overall portfolio, its
individual lenders, and their portfolios. However, we also reported
that SBA needed to make better use of the service in overseeing its
lenders and recommended, among other things, that resources within SBA
be devoted to developing policies for the use of the loan monitoring
service. As a result, SBA contracted with Dun & Bradstreet to develop a
system that would rate lenders based on risk. Dun & Bradstreet
subcontracted with another company, TrueNorth, to develop the lender
risk ratings--that is, custom scores calculated using L/LMS data. Work
on the lender risk rating system started in 2004.
The purpose of the lender risk rating system is to improve the way SBA
monitors lenders. The lender risk rating system uses the following
factors for 7(a) lenders:
* past 12 months' actual purchase rate--a historical measure of SBA
purchases from the lender in the preceding 12 months;[Footnote 12]
* problem loan rate--the current delinquencies and liquidations in a
lender's SBA-guaranteed portfolio;[Footnote 13]
* 3-month change in SBPS--a score that was developed to predict the
likelihood of severe delinquency (61 or more days past terms) over the
next 18 to 24 months, including bankruptcies and charge-offs;[Footnote
14] and:
* projected purchase rate--a measure of the amount of SBA guaranteed
dollars in a lender's portfolio that is likely to be purchased by SBA.
[Footnote 15]
Most of the data used to calculate these factors are loan and lender
performance information that come from SBA. The remaining data are
SBPSs or related scores provided by the Dun & Bradstreet service (see
table 1).
Table 1: Sources of Data Used to Calculate Lender Risk Ratings for 7(a)
Lenders:
Factor: Past 12 months' actual purchase rate;
Lender data: Total gross dollars of the lender's loans that were
purchased during the past 12 months;
Data sources: SBA: [Check];
Data sources: Dun & Bradstreet: [Empty];
Data sources: Fair Isaac: [Empty].
Factor: Past 12 months' actual purchase rate;
Lender data: Total gross outstanding dollars of SBA loans at the end of
12-month period;
Data sources: SBA: [Check];
Data sources: Dun & Bradstreet: [Empty];
Data sources: Fair Isaac: [Empty].
Factor: Problem loan rate;
Lender data: Gross outstanding dollars of the lender's loans that are
90 days or more delinquent;
Data sources: SBA: [Check];
Data sources: Dun & Bradstreet: [Empty];
Data sources: Fair Isaac: [Empty].
Factor: Problem loan rate;
Lender data: Gross dollars in liquidation;
Data sources: SBA: [Check];
Data sources: Dun & Bradstreet: [Empty];
Data sources: Fair Isaac: [Empty].
Factor: Problem loan rate;
Lender data: Gross dollars outstanding;
Data sources: SBA: [Check];
Data sources: Dun & Bradstreet: [Empty];
Data sources: Fair Isaac: [Empty].
Factor: 3-month change in SBPS;
Lender data: SBPS;
Data sources: SBA: [Empty];
Data sources: Dun & Bradstreet: [Check];
Data sources: Fair Isaac: [Check].
Factor: Projected purchase rate;
Lender data: Probability of loan purchase;
Data sources: SBA: [Empty];
Data sources: Dun & Bradstreet: [Check];
Data sources: Fair Isaac: [Check].
Factor: Projected purchase rate;
Lender data: Individual loans outstanding;
Data sources: SBA: [Check];
Data sources: Dun & Bradstreet: [Empty];
Data sources: Fair Isaac: [Empty].
Factor: Projected purchase rate;
Lender data: SBA-guaranteed dollars outstanding;
Data sources: SBA: [Check];
Data sources: Dun & Bradstreet: [Empty];
Data sources: Fair Isaac: [Empty].
Source: GAO analysis of SBA data.
[End of table]
For 504 lenders, the risk rating is based on three factors: (1) the
past 12 months' actual purchase rate, (2) the problem loan rate, and
(3) the average SBPS on loans in the 504 lender's portfolio. The third
factor replaced the third and fourth factors used for 7(a) lenders
because it was found during the testing process to be more predictive
of SBA purchases for 504 lenders.
Some federal financial regulators and lenders rely on similar tools to
conduct off-site monitoring. For example, FDIC relies on various off-
site monitoring tools, including a system called the Statistical CAMELS
Off-site Rating that helps the regulator identify institutions that
have experienced noticeable financial deterioration since the last on-
site exam. The Federal Reserve also relies on multiple tools to conduct
off-site monitoring, including a system that enables the regulator to
predict how the risk level of a bank likely will change in comparison
to other banks that received similar ratings on on-site exams. OCC
relies on a process called a core assessment that helps examiners
assess the risk exposure for nine categories of risk, including
quantity, quality, and direction of risk. Moreover, lenders frequently
use models to summarize available relevant information about borrowers
and reduce the information into a set of ordered categories, or scores,
that estimate the borrower's risk of delinquency or default at a given
point in time. Such tools are playing a progressively more important
role in the banking industry. In general, the goal of these models--
whether they are generic or custom, developed internally or by third
parties--is to obtain early indications of increasing risk.
SBA's Lender Risk Rating System Is Similar to Those Used by Federal
Financial Regulators but Is Limited by Insufficient Validation:
SBA's Contractor Uses a Multistep Process to Assign Lender Risk
Ratings:
SBA's contractor takes four steps to assign lender risk ratings each
quarter. First, the contractor separates lenders into peer groups based
on the size of their SBA loan portfolios in order to compare similarly
sized lenders. Second, for each lender, the contractor computes values
for each of the factors. As discussed in more detail in the background,
the four factors for 7(a) lenders are the (1) past 12 months' actual
purchase rate, (2) problem loan rate, (3) 3-month change in the SBPS,
and (4) projected purchase rate. Third, the contractor inputs the value
for each of the factors into an equation to compute a score for each
lender. Fourth, the contractor uses the scores to place lenders into
one of five risk rating categories (1 through 5, with 1 indicating the
least risk).[Footnote 16] Figure 1 illustrates this process for 7(a)
lenders, and the shaded area represents a specific example. The process
is generally the same for 504 lenders.[Footnote 17]
Figure 1: SBA's Lender Risk Rating Process for 7(a) Lenders:
[Refer to PDF for image: illustration]
1) Separates lenders into peer groups based on SBA loan portfolio size:
$0 - $999,999, 1 loan disbursed;
$1M - $3.9M;
$4M - $9.9M;
$10M - $99.9M;
$100M or more.
2) Computes value of each factor for each 7(a) lender:
Projected purchase rate;
Problem loan rate;
3-month change in SBPS;
Past 12 months‘ actual purchase rate.
3) Computes lenders‘ scores (1 - 999) by inputting each lender‘s value
of each factor into an equation.
4) Places lenders, based on their scores, into five risk rating
categories (1 through 5, with 1 indicating the least risk):
$0 - $999,999, 1 loan disbursed (Lender risk score, 1-5, low to high);
$1M - $3.9M (Lender risk score, 1-5, low to high);
$4M - $9.9M (Lender risk score, 1-5, low to high);
$10M - $99.9M (Lender risk score, 1-5, low to high);
$100M or more (Lender risk score, 1-5, low to high).
Sample 7(a) lender: SBA loan portfolio: $7.8M:
Loan portfolio size: $4M - $9.9M;
Lenders' score: 250;
Risk category: $4M - $9.9M (Lender risk score, 2).
Source: GAO.
Note: In step 2, the size of the symbols that represent each factor is
illustrative and not necessarily to scale.
[End of figure]
According to SBA officials, this process for calculating lender risk
ratings will likely change in the near future because its contractor is
redeveloping the lender risk rating system. Several major changes are
being contemplated. First, the contractor plans to use an updated
version of the SBPS. Second, the contractor may use additional
variables to calculate lender risk ratings. Finally, rather than
varying the equation by peer group, SBA officials stated that they are
considering a new variable that captures the size of the lender's
portfolio and the age of its loans. The contractor is still in the
process of designing, testing, and documenting the new risk rating
system.
SBA rarely overrides risk ratings, but it may do so for several
reasons. These include early loan default trends; abnormally high
default or liquidation rates; lending concentrations; rapid growth in
SBA lending; inadequate, incomplete, or untimely reporting to SBA; and
nonpayment of required fees to SBA.[Footnote 18] In addition, SBA may
override a lender risk rating due to issues identified during an on-
site review. For the quarter ending September 30, 2008, SBA overrode
the risk rating assigned by the contractor in 20 cases; in each case,
the risk rating increased.
SBA's Lender Risk Rating System Uses Some of the Same Types of Data
That Federal Financial Regulators and Selected Lenders Rely on to
Conduct Off-Site Monitoring:
SBA's lender risk rating system uses some of the same types of data
that federal financial regulators and selected lenders rely on for off-
site monitoring. The federal financial regulators we interviewed rely
on lender information, performance data, and prospective measures to
conduct off-site monitoring. Although the specific factors included in
each regulator's off-site monitoring tools can vary, each regulator
uses these three types of data. Much of the lender and performance
information they use are from the call reports that banks submit
quarterly and include data on equity, loans past due, and charge-offs.
[Footnote 19] Prospective measures include--when available--borrowers'
credit scores from lender files. One federal regulator is also working
with a third party to obtain predictive scores, similar to the SBPS, to
use as part of its off-site monitoring. The large lenders with whom we
spoke also use performance data to rate loans, focusing on factors such
as portfolio performance, delinquencies, and trends by state and
industry type in order to forecast future losses. Lenders also
incorporate prospective measures, such as FICO scores and SBPSs.
[Footnote 20]
Like federal financial regulators and large lenders, SBA uses
performance data and prospective measures to calculate lender risk
ratings. As we have seen, to calculate risk ratings for 7(a) lenders,
SBA relies on performance data (the past 12 months' actual purchase
rate and the problem loan rate) and prospective measures (the 3-month
change in the SBPS and the projected purchase rate). The 3-month change
in the SBPS is also a portfolio trend that has been incorporated into
the rating system. However, unlike the federal financial regulators,
SBA does not use lender information such as equity and loan
concentrations as inputs into its lender risk rating system. Although
the federal financial regulators and SBA both oversee lenders, their
missions differ, and as a result they may choose to focus on different
variables in conducting off-site monitoring. In general, the mission of
the federal financial regulators is to maintain stability and public
confidence in the nation's financial system. In contrast, SBA's mission
is to aid, counsel, assist, and protect the interests of small business
concerns, including guaranteeing loans to businesses in industries that
lenders may avoid. Therefore, it is understandable that SBA might not
include the same variables as federal financial regulators. In
addition, while it is not an input into the lender risk rating system,
SBA evaluates information such as equity and loan concentrations as
part of other monitoring efforts. Figure 2 summarizes how the data that
SBA uses in its lender risk rating system compare with the data
included in the risk rating systems used by the federal financial
regulators and lenders we interviewed.
Figure 2: Data Used for Off-Site Monitoring:
[Refer to PDF for image: illustrated table]
Lender information: Loan concentrations;
OCC: [Check];
FDIC: [Check];
Federal Reserve: [Check];
Selected lenders: [A];
SBA: [B].
Lender information: Income;
OCC: [Check];
FDIC: [Check];
Federal Reserve: [Check];
Selected lenders: [A];
SBA: [B].
Lender information: Equity;
OCC: [Check];
FDIC: [Check];
Federal Reserve: [Check];
Selected lenders: [A];
SBA: [B].
Performance measures: Portfolio trends;
OCC: [Check];
FDIC: [Check];
Federal Reserve: [Check];
Selected lenders: [Check];
SBA: [Check].
Performance measures: Delinquency;
OCC: [Check];
FDIC: [Check];
Federal Reserve: [Check];
Selected lenders: [Check];
SBA: [Check].
Performance measures: Default;
OCC: [Check];
FDIC: [Check];
Federal Reserve: [Check];
Selected lenders: [Check];
SBA: [Check].
Prospective measures:
OCC: [Check];
FDIC: [Check];
Federal Reserve: [Check];
Selected lenders: [Check];
SBA: [Check].
Source: GAO.
[A] The lenders we interviewed do not collect other lenders'
information to rate their loans.
[B] SBA evaluates loan concentrations during on-site reviews of lenders
and income and equity during performance-based reviews of lenders.
These reviews are discussed in detail later in this report.
[End of figure]
SBA's Lender Risk Rating System Better Predicted the Performance of
Larger Lenders than Smaller Lenders:
When we performed our own independent assessments of the reliability of
the lender risk ratings, we found that they were more reliable at
predicting the performance of the largest lenders. To perform this
independent assessment, we assessed how well the lender risk ratings
predicted the actual performance of lenders (that is, lenders' default
rates).[Footnote 21] Because of data limitations, our analyses focused
on lenders with larger SBA-guaranteed portfolios.[Footnote 22] Overall,
we found that SBA's ratings were able to distinguish between high-and
lower-risk lenders for a majority of the 7(a) and 504 lenders in our
sample for 2007 and 2008.[Footnote 23] However, when we focused on the
ratings' ability to predict the performance of different-sized lenders,
we found that the ratings were more effective at predicting the
performance of lenders with the largest SBA-guaranteed portfolios (that
is, lenders with SBA-guaranteed portfolios of at least $100 million).
(See appendix III for further discussion of how well the lender risk
ratings predicted the performance of 7(a) and 504 lenders.)
How the system was developed may have contributed to the lender risk
ratings being more effective at predicting the performance of the
largest lenders (that is, lenders with SBA-guaranteed portfolios of at
least $100 million). In order to determine how SBA developed the risk
rating system, we reviewed the available documentation of the
development process and discussed the process with SBA officials and
the contractor. According to the contractor, it considered 32 variables
to determine those that were the most predictive for each peer group.
SBA then made a policy decision to use the same factors across all of
the peer groups. Although the documentation did not provide the
justification for this policy decision, SBA officials stated that the
decision was made so that every lender's risk rating was based on
consistent information. Officials were concerned that lenders might be
confused if the factors upon which the ratings were based varied by
peer group, particularly since lenders do move between peer groups. The
contractor ultimately selected four factors, each of which was a
statistically significant predictor of lender performance for at least
one of the peer groups. However, only for the largest peer group (those
with guaranteed portfolios of at least $100 million) were all four
factors statistically significant. According to SBA officials, in peer
groups where a factor was statistically insignificant, it did not
affect the lenders' risk ratings--that is, for some peer groups, the
ratings are determined by less than four factors.
Usefulness of SBA's Lender Risk Rating System Has Been Limited because
SBA Does Not Ensure That Its Contractor Follows Sound Validation
Techniques:
The effectiveness of SBA's lender risk rating system has been limited
because the agency's contractor does not follow sound validation
practices. According to one federal financial regulator, the ability of
models to accurately predict outcomes can deteriorate over time. For
example, changes in economic conditions and industry trends can affect
model outcomes. Validation--the process of assessing whether ratings
adequately identify risks by, for example, comparing predictions to
actual results--helps to ensure that models remain reliable. Federal
financial regulators (OCC, FDIC, and the Federal Reserve) and the Basel
Committee on Banking Supervision (Basel Committee) have developed a
number of common principles that financial institutions should follow
in validating the models they use to manage risk, whether the models
are purchased from a vendor or developed in-house.[Footnote 24]
Validating some aspects of models developed by vendors may be difficult
because of the proprietary nature of the information. But the guidance
from federal financial regulators and the Basel Committee states that
organizations have a responsibility to ensure that vendors follow good
model validation practices.
We identified four key elements of a sound validation policy that
federal financial regulators and our internal control standards
recommend and that some lenders we interviewed implemented. First, all
three parts of a model--the data, processes, and results--should be
validated using multiple techniques. Second, validation should be done
by an independent party. Third, validation should include an ongoing
assessment of the factors used in the model. Finally, the validation
procedures should be documented. We found, however, that SBA had not
adhered to the guidance in validating its lender risk rating system.
First, SBA's validation procedure does not include techniques to
validate all parts of its model. Second, the model is not validated by
an independent party. Third, SBA does not reassess which variables are
the most predictive of lender performance on a routine basis. Finally,
SBA's documentation of the validation procedures and the results of the
validation is not complete. Figure 3 shows how SBA's practices align
with commonly accepted practices.
Figure 3: Commonly Accepted Validation Practices and SBA's Practices:
[Refer to PDF for image: illustrated table]
Model Validation: Validation of the model‘s data inputs;
OCC: Included in guidance or practices;
FDIC: Included in guidance or practices;
Federal Reserve: Included in guidance or practices;
Basel Committee: Included in guidance or practices;
GAO Internal Controls: Included in guidance or practices;
SBA: Included in guidance or practices.
Model Validation: Validation of the model‘s processes;
OCC: Included in guidance or practices;
FDIC: Included in guidance or practices;
Federal Reserve: Included in guidance or practices;
Basel Committee: Included in guidance or practices;
GAO Internal Controls: Included in guidance or practices;
SBA: Partially included in guidance or practices.
Model Validation: Validation of the model‘s results;
OCC: Included in guidance or practices;
FDIC: Included in guidance or practices;
Federal Reserve: Included in guidance or practices;
Basel Committee: Included in guidance or practices;
GAO Internal Controls: Included in guidance or practices;
SBA: Partially included in guidance or practices.
Independent validation;
OCC: Included in guidance or practices;
FDIC: Included in guidance or practices;
Federal Reserve: Included in guidance or practices;
Basel Committee: Included in guidance or practices;
GAO Internal Controls: Included in guidance or practices;
SBA: Not included in guidance or practices.
Ongoing validation of factors used in the model:
OCC: Included in guidance or practices;
FDIC: Included in guidance or practices;
Federal Reserve: Included in guidance or practices;
Basel Committee: Included in guidance or practices;
GAO Internal Controls: Included in guidance or practices;
SBA: Partially included in guidance or practices.
Documentation of validation procedures:
OCC: Included in guidance or practices;
FDIC: Included in guidance or practices;
Federal Reserve: Included in guidance or practices;
Basel Committee: Included in guidance or practices;
GAO Internal Controls: Included in guidance or practices;
SBA: Partially included in guidance or practices.
Source: GAO.
[End of figure]
SBA's Validation Procedure Does Not Include Techniques to Validate All
Parts of Its Model:
Guidance from the federal financial regulators we interviewed and the
Basel Committee states that each of the three parts of a model--the
data, processes, and results--should be validated using a variety of
techniques. According to FDIC guidance, validation should include
ensuring that the data used in the model are accurate and complete,
evaluating the model's conceptual soundness, and analyzing the
estimates the model produces against actual outcomes. The Basel
Committee also states the importance of assessing all the components of
a model. In addition, OCC guidance prescribes three generic procedures
that could be used for validating each part of a model--a review of
logical and conceptual soundness, comparison against other models, and
comparison against subsequent actual events. Further, guidance from the
Federal Reserve states that financial institutions should use a variety
of techniques when validating their models. For example, some lenders
we interviewed compared their internal rating systems with other
commercially available models or compared model predictions against
historical information to test the reliability of their models. In
addition, GAO's internal control standards specify that agencies should
ensure the accuracy of data inputs and information system processing
and results.[Footnote 25] For example, validation should be performed
to verify that data are complete and to identify erroneous data.
Furthermore, these standards state that management should establish
controls over information processing and that output reports should be
reviewed.
Consistent with commonly accepted practices, SBA's contractor has a
documented process for validating the data used in the lender risk
rating system. On the basis of previous reviews and recent interviews
with contractor staff, we found that the contractor's data quality
control process, referred to as DUNSRight, appeared reasonable. In June
2004, we reported that the commercial data that Dun & Bradstreet
collects go through a five-step quality assurance process that includes
continuously updating databases and matching SBA records with Dun &
Bradstreet records, with a 95 percent match of the data on critical
pieces of information.[Footnote 26] In the same report, we also
concluded that SBA's controls over the 7(a) and 504 data used in the
models helped to ensure that the data inputs were sufficiently
reliable. Appendix IV provides information on Dun & Bradstreet's
procedures for ensuring the reliability of the SBPS and how well it
predicts the likelihood that a loan will default.
The contractor that developed the lender risk rating system also
conducts periodic validations of the system that include using
statistical tests to measure the model's predictive ability and
comparing the results of the model against lenders' actual performance.
For the years 2005 through 2007, SBA's contractor assessed whether the
broad risk ratings were generally consistent with the actual
performance of the lenders within each rating group. The contractor
also determined whether each group of lenders (for example, those
lenders rated as 1) performed better than other groups of lenders with
lower risk ratings (that is, 2 through 5).[Footnote 27] However, we did
not see evidence that the contractor validated the processes used to
calculate the ratings. Specifically, neither SBA nor its contractor
could provide documentation showing that the contractor had validated
the theory behind the system or the logical and conceptual soundness of
the model. For example, there was no documentation describing the
processes followed or the link between the computer program and output
that was used to produce the lender risk ratings. Therefore, we could
not rerun the analysis to determine if we would have arrived at the
same conclusion regarding the four factors used in the model. In
addition, the contractor could not provide documentation showing that
it had ensured that the mathematics and computer code were free of
errors. According to officials from the contractor, they took steps to
verify that the processes they followed were sound, including verifying
the computer code they used; however, they did not document these
steps.
Further, the contractor's validation of the model's results was
limited. Consistent with industry standards, SBA's contractor has used
a variety of statistical measures to validate the risk rating system's
results.[Footnote 28] But the documentation did not show that the
contractor checked the model's results against available benchmarks
(such as the default rate or the currency rate) to validate whether the
risk ratings reliably predicted individual lender performance. Rather,
the documentation indicated that the contractor focused its validation
on whether the broad risk ratings were generally consistent with the
actual performance of the lenders within each rating group--groups that
can be comprised of over 2,000 lenders with a wide range of portfolio
sizes and performance levels. Although this technique compares the
model's results to actual performance benchmarks, as suggested by
industry standards, it is limited because it does not provide
information on individual lender performance. According to SBA
officials, the contractor tested how well individual scores produced by
the lender rating system predicted individual lender performance;
however, the results of this analysis were not included in the
documentation we received and were not provided to SBA. Because lender
performance can vary widely within the broad risk categories, the
results of a more refined analysis would allow SBA to identify specific
lenders placed in incorrect risk categories.
Because SBA has never requested documentation from the contractor on
its validation of the model's processes, the agency cannot ensure that
the processes used are sound. In addition, because the contractor does
not document how well the lender risk ratings predict individual
lenders' performance, SBA may not be able to identify which lenders
within the broad risk rating categories are not being rated accurately.
As a result, SBA may be relying on inaccurate ratings or missing out on
opportunities to identify risky lenders and target them for closer
monitoring.
Validation Is Not Conducted by an Independent Party:
Each of the regulators we interviewed (OCC, FDIC, and the Federal
Reserve) recommends in its guidance that validation include an
independent review of the model. For example, OCC guidance states that
model validation should be done by a party that is as independent as
possible from the personnel who constructed the model. In addition,
FDIC guidance states that validation should include competent and
independent review by a reviewer who is as independent as practicable.
Further, Federal Reserve and Basel Committee guidance notes that the
validation process should be independent from the model development and
implementation processes. Our internal control standards also emphasize
the importance of independent review. They state that to reduce the
risk of error, no one individual should control all key aspects of an
activity.[Footnote 29] For example, an individual who is responsible
for developing a model should not be responsible for validating it. An
independent party can be either inside or outside the organization--for
example, the internal audit staff, a risk management unit of the
institution, an external auditor, or another contracted third party.
Some lenders we interviewed that had internal risk rating systems have
had them validated by a separate group within the institution, and
others have invited independent auditors to review their systems.
Contrary to common industry practices and internal control standards,
the same contractor staff that developed and maintain the lender risk
rating system are the officials who validate it. We have previously
reported on SBA's failure to ensure that independent parties routinely
assess the reliability or integrity of its contractors' models.
[Footnote 30] Specifically, we reported in June 2004 that third parties
did not validate the SBPS model that another contractor maintained
because SBA believed that the model was stable and that clients would
inform the company if the models were not reasonably predicting
borrower behavior. Similarly, SBA and its contractor thought it was
sufficient for someone to review the validation conducted by the staff
who developed the model and for Dun & Bradstreet and SBA officials to
review the contractor's work. However, industry standards require that
personnel other than those who developed the model validate it. Because
SBA has not ensured that an independent party validates its lender risk
ratings, certain systemic and structural issues with the design of the
system may go undetected, and the predictive value of the risk ratings
is more uncertain.
SBA Does Not Perform Ongoing Validation to Ensure That the Factors Used
in the System Are the Most Predictive:
Guidance from federal financial regulators and the Basel Committee
states that validation of the factors used in the model should be
ongoing and should take into consideration changes in the environment
(such as changes in economic conditions or industry trends) or
improvements in modelers' understanding of the subject. For example,
OCC guidance states that models are frequently altered in response to
changes such as these. In addition, Federal Reserve guidance states
that a model's methodology should be validated periodically and
modified to incorporate new events or findings as needed. Further, the
Basel Committee notes that validation is an ongoing, iterative process.
Failure to do so could cause the model to become less predictive and
lose its ability to rank order risk over time. According to FDIC
guidance, characteristics of a model need to be validated and refined
when necessary because if management does not select and properly
weight the best predictive variables, the model's output will likely be
less effective. Our internal control standards also specify that
agencies that procure commercial software are responsible for ensuring
that it meets the user's needs and is operated properly.[Footnote 31]
These standards state that controls should be in place to ensure that
computer systems are modified safely by reviewing and testing them
before placing them into operation. The standards also specify that
management should ensure that ongoing monitoring is effective and will
trigger separate evaluations where problems are identified.
SBA's contractor takes some steps to validate the lender risk rating
system's ability to reliably predict lender performance but does not
ensure that the variables used to calculate the risk ratings are the
most predictive of lender performance. We reviewed the validations of
the risk rating system that the contractor conducted in 2005, 2006, and
2007. These validation efforts included testing of the statistical
importance of each of the four factors used in the lender risk rating
system. However, these validations did not routinely include testing of
other factors to account for changes in economic conditions or industry
trends. The 2005 validation effort was the only one that tested
additional factors. SBA's contractor tested three new variables to
determine if they improved the model's ability to predict lender
performance and found that they did not.[Footnote 32] Neither of the
subsequent validations included assessments of additional variables,
and SBA did not requested them. According to SBA officials, SBA and the
contractor identified possible additional variables over the past
several years that they did not test for use in the model because they
wanted more experience with it and the data.[Footnote 33] They also
noted that they always had plans to redevelop the model within 5 years
but could not do so until the agency had signed a second contract with
Dun & Bradstreet that provided funds for a redevelopment. However, if
SBA had asked the contractor to test additional factors on a regular
basis, the agency may have found that an earlier redevelopment effort
or incremental adjustments could have improved the predictive ability
of the model. Because new variables that might take into account
economic changes or industry developments have not been routinely
assessed, the ratings may not be as effective as they could be.
In addition, according to the contractor's validation reports, the
lender risk rating system's predictive ability for 7(a) lenders
decreased from 2005 to 2007.[Footnote 34] This decrease led the
contractor to suggest in 2007 that SBA redevelop the model to improve
its predictive ability and prevent further deterioration. SBA officials
agreed, and the contractor is currently redeveloping the model,
including testing new variables, to keep up with changing economic
conditions and to reflect SBA's and the contractor's experiences
working with the data and the model over the last several years. It
will be important for SBA to ensure that the contractor conducts sound
testing as part of its redevelopment.
SBA's Documentation of Validation Procedures and Results Is Incomplete:
The federal financial regulators' guidance states that a sound
validation policy should include documentation of the validation. For
example, FDIC and OCC guidance states that model validation
documentation should describe the model, how it is used, and its
limitations. Federal Reserve guidance also notes that the validation
process should be documented. In addition, FDIC and OCC have said that
the procedures used to validate the model on an ongoing basis and the
results of these validations should be documented, even if the
institution uses a model developed by a vendor. For example, OCC
guidance states that an institution should seek assurances that the
vendor's model is defensible and works as promised. Further, the Basel
Committee guidance notes that even vendors that are not willing to
reveal proprietary information should provide information on the
validation techniques they use. Complete documentation of the results
of ongoing validations assists users in understanding the model and
facilitates independent reviewers' assessments of the model's validity.
Our internal control standards also specify the importance of
documenting information systems.[Footnote 35] For example, these
standards state that all significant events in developing and
maintaining computer systems should be clearly and completely
documented. This documentation should describe the system, how the data
used in the system are handled, and other controls in place to maintain
the system.
SBA did not ensure that the contractor provided complete documentation
of the results of its validations or documented its validation
procedures. SBA provided us with some documentation of the contractor's
process for validating the data used in the lender risk rating system,
but documentation of the results of the validations was inconsistent
and did not have information on the procedures for validating the
model's processes. For example:
* The validation reports we reviewed (2005 to 2007) did not always
include information on the statistical measure the contractor used to
describe the model's predictive abilities. The 2006 validation report
did not contain this statistic for the 7(a) ratings, and only the 2007
report included it for 504 lender risk ratings.
* The validation reports did not describe the contractor's validation
procedures. As noted previously, SBA did not provide documentation
showing that the contractor validated the mathematics and computer code
used in the model.
* The validation reports did not explain why in 2005 the contractor
considered whether additional variables would improve the model's
ability to predict lender performance but did not consider additional
variables in other years.
* The validation reports did not describe any limitations of the model
that would have helped SBA to use the results accurately.
Officials from the contractor explained that the documentation provided
was typical of that seen in the private sector for such models, but
stated that they would provide more detailed documentation in the
future.
Because SBA does not ensure that its contractor completely documents
its validation procedures and results, it is difficult to assess the
sufficiency of the validations performed. Further, as we noted
previously, it is important for an independent party to validate a
model's reliability. Without clear documentation explaining the model's
limitations, the validation procedures, and the results of the
validations, an independent reviewer would have difficulty conducting a
thorough assessment of SBA's model.
SBA Does Not Use Its Own Data to Assess or Supplement the Contractor's
Validation of the Lender Risk Rating System:
In addition to not ensuring that its contractor follows sound
validation techniques, SBA does not conduct its own analysis of data to
supplement the contractor's validation of the lender risk rating
system. According to the Basel Committee guidance we reviewed,
organizations must have clearly articulated strategies for regularly
reviewing the results of vendor models and the integrity of the
external data used in these systems. Further, OCC guidance states that
vendor models should generally be held to the same minimum validation
standards as internally developed models. When full and complete
details concerning aspects of a vendor product are lacking, OCC and
Basel Committee guidance states that organizations should rely more
heavily on alternative validation techniques to compensate for the lack
of access to full information. This guidance notes that in such cases,
it is critical for organizations to test the results of the vendor's
model at least once a year using their own data on actual performance
to assess the model's predictive ability. This procedure helps to
ensure that the models continue to function as intended and verifies
the reliability and consistency of any external data used. Our internal
control standards state that monitoring should be performed continually
and that it should involve comparisons and reconciliations.[Footnote
36] For example, these standards specify that agencies should compare
information generated from computer systems to actual records. Agencies
should also analyze and reconcile any differences that might be found.
SBA does not use its own data to independently assess the lender risk
rating system's results. According to a 2007 SBA Inspector General
report, SBA has previously rejected using its own data to develop
lender performance benchmarks that could be used in lieu of or in
conjunction with the risk ratings because doing so would be time-
consuming and the benchmarks would have to be monitored and replaced as
program and economic conditions changed.[Footnote 37] However, we found
that SBA data could be useful for developing alternate measures of
lender performance in order to independently validate the lender risk
rating system's results. For example, SBA could perform analyses
similar to those we performed by using its own data to compare risk
ratings with actual lender default rates. Further, SBA could use its
own data to develop alternate measures, such as currency rates, as
performance benchmarks. As we did in our analyses, SBA could compare
how well lender risk ratings predicted actual performance to how well
an alternate measure demonstrated lender's actual performance. Because
of data limitations, our analyses focused on lenders with larger SBA-
guaranteed portfolios. As a result, we were unable to determine how
well these alternate measures predict the performance of lenders with
smaller portfolios, but SBA has more years of data available to
facilitate such analyses. Without performing its own assessment, the
agency may not be able to identify issues with the model's ability to
reasonably predict lender performance and notify the contractor. As a
result, SBA may miss opportunities to identify risky lenders and
mitigate the risks they pose to SBA's portfolio.
SBA Does Not Use Lender Risk Ratings to Target Lenders for On-Site
Review or Tailor the Scope of the Reviews:
SBA Has Used the Lender Risk Rating System to Conduct Some Off-Site
Monitoring of Lenders and Their Portfolios:
SBA uses its lender risk rating system to conduct off-site monitoring
of lenders and their portfolios. In addition to routine on-site
reviews, federal financial regulators and lenders use off-site tools to
monitor lenders' performance and portfolio trends. As part of a
comprehensive risk management strategy, federal financial regulators
use risk ratings to conduct portfolio analysis and identify problem
trends. FDIC relies on a number of off-site monitoring tools to perform
horizontal analyses (that is, compare similar lenders) and analyze
emerging lending trends. For example, when subprime lending first
began, the agency tracked the amount of subprime lending that each of
its lenders did. The Federal Reserve uses various off-site monitoring
tools that focus on asset quality and credit risk to identify banks
whose ratings appear to have deteriorated since their most recent on-
site reviews. For example, it analyzes information related to
nonperforming and performing loans and the changing composition of loan
concentrations. OCC uses its core assessment process to assess how much
risk lenders have taken on and the quality of their risk management to
determine aggregate risk.
Lenders also use off-site monitoring tools to oversee loan portfolios.
For example, one 7(a) lender we interviewed uses various scoring models
to determine, among other things, how each loan's risk rating has
changed since the loan was originated. Other 7(a) lenders with whom we
spoke use off-site monitoring tools that analyze factors such as
geography, industry, management quality, company performance, and
collateral to predict the risk of loans. Another 7(a) lender relies on
several off-site monitoring systems to track portfolio performance--
including delinquencies and trends by state, industry, and North
American Industry Classification System (NAICS) code--and forecast
losses.[Footnote 38] In addition, bank officials we interviewed stated
that they reviewed all troubled loans on a monthly basis.
Similarly, SBA uses its lender risk rating system to obtain quarterly
performance information on all lenders and determine portfolio trends.
SBA officials stated that before they had the risk rating system, they
were not able to analyze the performance of all lenders, especially
lenders with the smallest volume of SBA-guaranteed loans. SBA has
formed a Portfolio Analysis Committee that meets monthly to discuss
portfolio trends identified by analyzing loan and lender performance
data. Comprised of top SBA officials, the committee typically discusses
delinquencies, liquidations, charge-offs, and purchase rate trends by
delivery method (that is, various SBA loan programs) for the 7(a) and
504 portfolios. The committee also discusses changes in loans' SBPSs
(from the end of the quarter in which the loan was disbursed to the
most recent quarter) and the scores' performance in ranking loans. To
date, SBA has taken some actions as a result of these meetings. For
example, SBA officials told us that as a result of discussions about
portfolio performance during these meetings, they discontinued an SBA
program that allowed borrowers to provide limited documentation.
SBA officials told us that the agency also recently began using the
results of the lender risk rating system to conduct "performance-based
reviews." According to SBA officials, the purpose of these reviews is
to perform more in-depth, off-site monitoring that incorporates
lenders' information, such as lender financial ratios from call
reports, that is currently not part of the lender risk rating system.
Specifically, SBA financial analysts are assigned lenders that they
will monitor over time. Each year, the analysts will focus on lenders
with outstanding balances on their SBA portfolios of at least $10
million that are not scheduled for on-site reviews and on all other
preferred lenders regardless of size. With the remaining resources,
they will review small problem lenders--for instance, those with
guaranteed portfolios that are less than $10 million but that received
a lender risk rating of 4 or 5. SBA had conducted 517 of these reviews
as of August 2009.
SBA Has Not Effectively Integrated Its Lender Risk Rating System into
the On-Site Examination Process:
Although SBA has begun some off-site monitoring using its risk rating
system, it does not use the ratings to target lenders for on-site
reviews. FDIC and the Federal Reserve use risk ratings as the primary
tool for identifying lenders that need to be reviewed.[Footnote 39] For
example, FDIC stated that they relied on off-site monitoring to
determine the scope and frequency of on-site exams. Our internal
control standards require that agencies assess and mitigate risks using
quantitative and qualitative methods and then conduct a thorough and
complete analysis of those risks. Although SBA identifies the risks
that lenders pose, it does not mitigate these risks because it chooses
not to target high-risk 7(a) and 504 lenders for on-site reviews.
Instead, the agency targets lenders for reviews based on the size of
their portfolios, focusing primarily on the largest lenders--that is,
7(a) lenders with at least $10 million in their guaranteed loan
portfolio and 504 lenders with balances of at least $30 million. Only
when prioritizing large lenders for review does SBA consider their risk
ratings.[Footnote 40]
We found that in calendar years 2005 to 2008, most of SBA's 477 on-site
reviews were of large 7(a) and 504 lenders that posed limited risk to
SBA. Ninety-nine percent (472 of 477) of the lenders reviewed were
large lenders, and 80 percent (380 of 477) posed limited risk to SBA
(that is, were rated as a 1, 2, or 3 by the lender risk rating system).
The agency has increased the number of on-site reviews performed (from
69 in 2005 to 188 in 2008) because it can now charge lenders for
them.[Footnote 41] However, SBA continues to conduct a limited number
of reviews of high-risk lenders or those with a lender risk rating of 4
or 5 (see figure 4). In 2005, 20 percent (14 of 69) of SBA's on-site
reviews were of lenders that posed significant risk to the agency. In
2008, that proportion was 22 percent (42 of 188 reviews). As a result,
a substantial number of high-risk lenders were not reviewed each year.
For example, in 2008, only 3 percent of the 1,587 lenders that posed
significant risk to SBA were reviewed. Because SBA relies on lenders'
size to target lenders for on-site reviews, smaller lenders that, based
on their high-risk ratings, pose significant risk to SBA have not
received oversight consistent with their risk levels.
Figure 4: SBA On-Site Reviews, 2005 to 2008:
[Refer to PDF for image: stacked vertical bar graph]
Year: 2005;
Frequency, Risk rating 1: 7;
Frequency, Risk rating 2: 18;
Frequency, Risk rating 3: 30;
Frequency, Risk rating 4: 6;
Frequency, Risk rating 5: 8;
Total: 69.
Year: 2006;
Frequency, Risk rating 1: 3;
Frequency, Risk rating 2: 7;
Frequency, Risk rating 3: 37;
Frequency, Risk rating 4: 3;
Frequency, Risk rating 5: 13;
Total: 63.
Year: 2007;
Frequency, Risk rating 1: 32;
Frequency, Risk rating 2: 58;
Frequency, Risk rating 3: 42;
Frequency, Risk rating 4: 17;
Frequency, Risk rating 5: 8;
Total: 157.
Year: 2008;
Frequency, Risk rating 1: 61;
Frequency, Risk rating 2: 44;
Frequency, Risk rating 3: 41;
Frequency, Risk rating 4: 26;
Frequency, Risk rating 5: 16;
Total: 187.
Source: GAO analysis of SBA data.
[End of figure]
Our findings are similar to those of SBA's Inspector General. In a 2007
report, the Inspector General concluded that SBA had made limited use
of lender risk ratings to guide its oversight activities.[Footnote 42]
It observed that the agency reviewed large lenders regardless of their
risk ratings and did not do on-site reviews of smaller lenders with
high-risk ratings. The report recognized that some of the smaller
lenders might not have a sufficient number of loans in their portfolio
to warrant an on-site review but noted that others could have a
significant number of loans. The Inspector General recommended that SBA
develop an on-site review plan or agreed-upon procedures for all high-
risk 7(a) lenders with guaranteed loan portfolios in excess of $4
million. We agree that although not all of the small lenders with high-
risk ratings warrant more targeted monitoring, some do. Of the 1,545
high-risk lenders that we found were not reviewed in 2008, 215 lenders
had an outstanding portfolio of at least $4 million. According to SBA
officials, the agency is developing agreed-upon procedures for
conducting additional reviews of smaller lenders in response to the
Inspector General's recommendation.
Lender Risk Ratings Do Not Inform the Scope of SBA's On-Site Reviews,
and Reviews Do Not Include an Assessment of Lenders' Credit Decisions:
Unlike federal financial regulators, SBA does not rely on its lender
risk ratings to help focus the scope of on-site reviews, and the
reviews do not include an assessment of the lenders' credit decisions.
The federal financial regulators we interviewed rely on results from
their off-site monitoring systems to identify which areas of a bank's
operations they should review more closely. Using the results of the
off-site monitoring, they are able to tailor the scope of their on-site
reviews to the specific areas of lenders' operations that pose the most
risk to the bank. In addition, during on-site reviews, the federal
financial regulators often include an assessment of the quality of
lenders' credit decisions. They told us that the results of their on-
site reviews helped not only to assess the risk that lenders posed, but
also to identify emerging lending trends and areas of banking
operations that may pose significant, new risk to banks in the future.
They are then able to use the results to inform their off-site
monitoring systems. For example, regulators stated that when their on-
site reviews showed an increase in subprime lending, they incorporated
subprime lending data into their off-site monitoring tools. Although
SBA's mission differs from the mission of the federal financial
regulators, internal control standards require all federal agencies to
identify and analyze risk, as well as to determine the best way to
manage or mitigate it.
According to SBA's Standard Operating Procedure for on-site reviews,
the agency assesses a lender's (1) portfolio performance, (2) SBA
management and operations, (3) credit administration practices, and (4)
compliance with statutes and SBA regulations and policies. For the
portfolio performance component, SBA uses L/LMS data to review the
size, composition, performance, and credit quality of a lender's SBA
portfolio. When assessing a lender's SBA operations, SBA evaluates,
among other things, the lender's internal policy and procedural
guidance on SBA lending; the competence, leadership, and administrative
ability of management and staff who have responsibility for the SBA
loan portfolio; and the adequacy of the lender's internal controls. For
the credit administration component, SBA assesses the lender's policies
and procedures for originating, servicing, and liquidating SBA loans.
An SBA contractor then uses this information during file reviews to
determine the degree to which lending policies and procedures are
followed. For the compliance component, SBA's contractor performs file
reviews that focus on the lender's compliance with SBA-specific
requirements.
When performing file reviews, contractor staff do not rely on results
from the lender risk rating system to tailor the scope of the reviews.
Instead, contractor staff rely on a standard form--the lender review
checklist--to conduct all file reviews, regardless of the lender risk
rating or other information available to SBA about the lender's
portfolio. Moreover, these file reviews do not include an assessment of
the quality of the credit decisions made by lenders. Rather, the lender
review checklist focuses primarily on the lenders' adherence to SBA
policies, including those based on statutes or regulations, when making
SBA-guaranteed loans. The checklist includes questions related to,
among other things, the determination of borrower eligibility
(including whether the borrower had any other outstanding SBA loans
that are not current), the calculation of collateral value, and
evidence that all required forms were obtained and reviewed. According
to SBA officials, the file reviews focus on compliance with SBA policy
because it is not SBA's role to evaluate lenders' credit decisions. The
officials did not believe that the agency should be setting policy or
underwriting standards for lenders. However, because SBA relies on
lenders with delegated underwriting authority to make the majority of
its loans, we believe that SBA should take a more active role in
ensuring that these lenders are making sound credit decisions.
We originally reported on SBA's compliance-based reviews in 2002, when
we found that SBA's automated checklist lacked the substance to provide
a meaningful assessment of lender performance.[Footnote 43] We reported
that SBA's on-site reviews were based on reviewers' findings from a
lender questionnaire and a review checklist in order to ensure
objective scoring. The lender questionnaire addressed organizational
structure, oversight policy, and controls. SBA officials said that
prior to the implementation of the automated worksheet scoring process,
on-site reviews were done in a narrative format, and reviewers'
assessments of lender performance were subjective. They noted that the
worksheet format made the reviewers' assessments of lenders more
consistent and objective. As previously mentioned, SBA has since
expanded the scope of its on-site reviews to include more than just a
compliance component and revised the checklist used to conduct file
reviews. But, as noted previously, the revised checklist still focuses
on compliance with SBA policies and procedures.
An example from our February 2009 report on compliance with the credit
elsewhere requirement illustrates SBA's emphasis on ensuring policy
compliance rather than verifying lenders' credit decisions during on-
site reviews.[Footnote 44] Because the 7(a) and 504 programs are
intended to serve borrowers who cannot obtain conventional credit at
reasonable terms, lenders making 7(a) and 504 loans must ensure that
borrowers meet the credit elsewhere requirement. This statutory
requirement stipulates that to receive loans, borrowers must not be
able to obtain financing under reasonable terms and conditions from
conventional lenders. During an on-site review, the contractor is to
determine whether lender policies and practices adhere to SBA's credit
elsewhere requirement. During the review, SBA's contractor explained
that it checks to see that the lender documented its credit elsewhere
determination and cited one of the six factors that SBA has determined
are acceptable reasons for concluding that a borrower could not obtain
credit elsewhere. However, it does not routinely assess the information
lenders provide to support credit elsewhere determinations. Contract
staff answer "yes" or "no" on the checklist that "written evidence that
credit is not otherwise available on terms not considered unreasonable
without guarantee provided by SBA" was in the file. Contractor
officials stated that when the documentation standard is not met, the
examiner will sometimes look at the factual support in the file to
independently determine whether the credit elsewhere requirement was
actually met.
Because SBA officials choose not to rely on lender risk ratings to
inform file reviews conducted during on-site reviews or assess lenders'
credit decisions during the reviews, the agency does not have the type
of information related to the quality of the underwriting standards and
practices of lenders that is necessary to understand the risks that
banks pose to SBA's portfolio. Without this information, the agency
cannot make informed improvements to the lender risk rating system that
would enable it to take into account new emerging lending trends.
Conclusions:
Because SBA relies heavily on its lenders to determine if loans are
eligible for an SBA guarantee and to underwrite the loans, lender
oversight is of particular importance. By working with a contractor to
develop a lender risk rating system, SBA has taken a positive step
toward improving its oversight of lenders. The lender risk rating
system enables SBA for the first time to systematically and routinely
monitor the performance of all lenders, including lenders with the
smallest loan portfolios, which SBA had not routinely monitored.
However, SBA does not ensure that its contractor follows sound
practices when validating the system. Guidance from the federal
financial regulators we interviewed states, among other things, that
validation should be performed by an independent party and should
routinely reassess the factors used to determine risk, taking into
consideration changes in the environment (such as changes in industry
trends). SBA did not require its contractor to ensure that personnel
other than the staff who developed the model validated it or to
routinely reassess the factors used in the system as part of its
validations. Unless SBA ensures that its contractor follows sound model
validation practices, the agency's ability to identify inaccurate
ratings, detect systemic or structural issues with the design of the
model, and determine whether the ratings are deteriorating over time as
economic conditions change will be limited. SBA's contractor is
currently redeveloping the lender risk rating system to improve its
predictive ability. However, the benefits that may be achieved through
the redeveloped lender risk rating system will be limited if SBA
continues the practice of not ensuring that its contractor adopts sound
validation practices. In particular, testing to ensure that the system
effectively evaluates risk is an important element to improve a risk
rating system, regardless of whether such testing occurs during routine
validation efforts or during model redevelopment.
In addition, contrary to federal financial regulator guidance and our
internal control standards, SBA has not used its own data to conduct
independent assessments of the risk rating system to help ensure the
usefulness of the risk ratings. We found that SBA data could be useful
for developing alternate measures of lender performance in order to
independently validate the lender risk rating system's results. Without
performing its own assessment, the agency may not be able to identify
issues with the model's ability to reasonably predict lender behavior
or to notify the contractor of any suspected deterioration. As a
result, SBA may miss opportunities to identify risky lenders and
mitigate the risks they pose to SBA's portfolio.
If SBA improves its validation of the lender risk ratings, the agency
could rely more on them to determine which lenders need an on-site
review. Currently, unlike FDIC and the Federal Reserve, SBA does not
take full advantage of its risk ratings to set the schedules for on-
site reviews. The agency targets lenders for on-site reviews based on
size rather than risk level. As a result, we found that SBA conducted
on-site reviews of only 3 percent of the lenders that the lender risk
rating system identified as high risk in 2008. Of these, 215 had an
outstanding SBA portfolio of at least $4 million. Relying more on the
risk ratings to target lenders for review would enable the agency to
focus on the lenders that pose the most risk to the agency.
Although SBA has made improvements to its off-site monitoring of
lenders, the agency will not be able to substantially improve its
lender oversight efforts unless it improves its on-site review process.
Federal financial regulators rely on results from their off-site
monitoring to tailor the scope of their on-site reviews. SBA does not
rely on its lender risk ratings to inform file reviews conducted during
on-site reviews but rather consistently uses a checklist to examine
lenders. In addition, federal financial regulators routinely assess the
quality of lenders' credit decisions as part of their on-site
examination process. SBA fails to include this component but instead
focuses more on compliance with SBA policies and procedures. For
example, rather than assessing the quality of lender underwriting,
contractor staff focus on whether lenders ensured that the borrowers
met eligibility requirements, including whether borrowers had any other
outstanding SBA loans that are not current. By including an assessment
of lenders' credit decisions as a routine part of their on-site review
process, SBA would be able to determine the quality of the lenders'
underwriting standards and practices and make any necessary changes to
its lender risk rating system to ensure that the tool is relevant and
includes emerging lending trends.
Recommendations for Executive Action:
We recommend that the Administrator of the Small Business
Administration take the following four actions:
To ensure that the lender risk rating system effectively evaluates
risk, when validating the system and undertaking any redevelopment
efforts, the Administrator should:
* ensure that SBA's contractor follows sound model validation
practices. These practices should include (1) testing of the lender
risk rating system data, processes, and results, including a routine
reassessment of which factors are the most predictive of lender
performance; (2) utilizing an independent party to conduct validations;
and (3) maintaining complete documentation of the validation process
and results.
* use SBA's own data to assess how well the lender risk ratings predict
individual lender performance.
To make better use of the lender risk rating system in SBA's oversight
of lenders, the Administrator should:
* develop a strategy for targeting lenders for on-site reviews that
relies more on SBA's lender risk ratings.
* consider revising SBA policies and procedures for conducting on-site
reviews. These revised policies and procedures could require staff to
(1) use lender risk ratings to tailor the scope of file reviews
performed during on-site reviews to areas that pose the greatest risk,
(2) incorporate an assessment of lenders' credit decisions in file
reviews, and (3) use the results of expanded file reviews to identify
information, such as emerging lending trends, that could be
incorporated into its lender risk rating system.
Agency Comments and Our Evaluation:
We requested SBA's comments on a draft of this report, and the
Associate Administrator of the Office of Capital Access provided
written comments that are presented in appendix II. SBA generally
agreed with our recommendations and outlined some steps that it plans
to take to address them. The agency also provided one technical
comment, which we incorporated.
SBA provided detailed comments on each of our four recommendations. In
response to our recommendation to ensure that SBA's contractor follows
sound model validation techniques, SBA noted that the agency is
currently undertaking a redevelopment of its lender risk rating system
and plans to ensure that best practices are incorporated into the
redevelopment validation process. According to the agency, the
redevelopment contract will give SBA greater flexibility to reassess
the predictiveness of the factors used in the model and to refine the
model if necessary. SBA stated that it is also developing an
independent review process as well as increasing the level of
documentation of the validation process.
Regarding our recommendation to use its own data to assess how well the
lender risk ratings predict individual lender performance, SBA stated
that although it remains confident that the lender risk ratings provide
accurate predictions, the agency will determine whether alternative
measures would be useful to supplement the lender risk ratings.
In response to our recommendation to develop a strategy for targeting
lenders for on-site review that relies more on the lender risk ratings,
SBA stated that it agreed with our finding that between 2005 and 2008
on-site reviews had been limited and primarily focused on the largest
lenders, but pointed out that the agency had significantly increased
the number of lenders reviewed since it began charging for on-site
reviews late in fiscal year 2007. The agency also noted that the
largest lenders account for approximately 85 percent of SBA's entire
guaranteed portfolio, while the high-risk lenders that were not
reviewed in 2008 represent 2 percent of SBA's total 7(a) and 504
portfolios. In our report, we recognize that while not all of the small
lenders with high risk ratings warrant more targeted monitoring, some
do. Of the 1,545 high-risk lenders that we found were not reviewed in
2008, 215 lenders had significant portfolios--that is, portfolios of at
least $4 million. While SBA indicated that it plans to continue to
focus on-site reviews on the largest lenders that account for the
majority of the guaranteed portfolio, it stated that it will consider
revising its internal policies to make better use of the lender risk
ratings to prioritize on-site reviews.
Regarding our recommendation to consider revising policies and
procedures for conducting on-site reviews, SBA stated that the agency
is in the process of reprocuring its on-site review contract. According
to the agency, SBA included the ability to conduct on-site reviews that
can be better tailored to specific concerns about individual lender
performance as part of the reprocurement process. SBA also stated that
the agency is in the process of evaluating our recommendation to
include an assessment of lender credit decisions in the on-site review
process and will investigate ways to use the results of the on-site
reviews to inform the lender risk rating system.
As agreed with your offices, unless you publicly announce the contents
of this report earlier, we plan no further distribution until 30 days
from the report date. At that time, we will send copies of this report
to interested congressional committees, the Administrator of the Small
Business Administration, and other interested parties. In addition, the
report will be available at no charge on the GAO Web site at
[hyperlink, http://www.gao.gov].
If you or your staffs have any questions about this report, please
contact me at (202) 512-8678 or shearw@gao.gov. Contact points for our
Offices of Congressional Relations and Public Affairs may be found on
the last page of this report. Key contributors to this report are
listed in appendix V.
Signed by:
William B. Shear:
Director, Financial Markets and Community Investment:
[End of section]
Appendix I: Objectives, Scope, and Methodology:
In this report, we examined (1) how the Small Business Administration's
(SBA) risk rating system compares with the off-site monitoring tools
used by federal financial regulators and lenders and the system's
usefulness for predicting lender performance and (2) how SBA uses the
lender risk rating system in its lender oversight activities.
To determine how SBA's lender risk rating system compares with off-site
monitoring tools used by federal financial regulators and lenders, we
conducted interviews and reviewed documents to identify common industry
standards. We interviewed officials from three federal financial
regulators--the Office of the Comptroller of the Currency (OCC), the
Board of Governors of the Federal Reserve System (the Federal Reserve),
and the Federal Deposit Insurance Corporation (FDIC)--five of the
largest 7(a) lenders, and the five largest 504 lenders.[Footnote 45] We
identified the largest lenders based on the size of their SBA-
guaranteed portfolio in 2007, the most recent data available when we
began our review.[Footnote 46] The documents we reviewed included
relevant literature, procedural manuals and other related federal
guidance to banks on loan portfolio monitoring, and lender procedural
manuals. We then obtained and analyzed documents from SBA on its lender
risk rating system and conducted interviews with agency and contractor
officials responsible for maintaining the system to determine how the
system was developed and validated. We assessed SBA's lender risk
rating system against common industry standards and our internal
control standards.[Footnote 47] In addition, we reviewed our previous
work on SBA and guidance on model validation from the Basel Committee
on Banking Supervision, which provides a forum for banking regulators
from around the world to regularly cooperate on banking supervisory
matters and develop common guidelines.[Footnote 48]
To assess the lender risk rating system's usefulness for predicting
lender performance, we performed independent statistical tests to
determine how well it predicted individual lender performance. To
perform these tests, we first obtained the following data from SBA:
administrative data on loans approved in 2003 through the end of 2007
(including the date the loan was approved, the size of the loan, and
whether and when the loan was purchased); the March 2007 and March 2008
lender performance reports containing risk ratings; and the currency
rate for each lender.[Footnote 49] We assessed the reliability of these
data by reviewing information about the data and performing electronic
data testing to detect errors in completeness and reasonableness. We
found that the data were sufficiently reliable for the purposes of this
report.
Using SBA's data, we undertook a number of evaluative steps to test the
agency's model. First, we assessed how well the lender risk ratings
predicted lender default rates (our measure of actual lender
performance). In order to test how well the lender risk ratings
predicted lender performance, we estimated how well a lender performed
during either the year or 6 months after the score was developed
(depending on the amount of data available) using a logit regression. A
logit regression is a statistical technique that estimates how the odds
of an outcome changes with an attribute of the unit of analysis. In our
case, we estimated how the odds of a loan being purchased by SBA varied
by the lender that made the loan. Additionally, we controlled for the
age of loans and how default rates for all loans changed over the year
or 6 months. To control for the age and changing default rates over
time, we employed a methodology called a discrete time hazard model. We
restructured the data so that there was a separate observation for
every quarter that a loan was at risk of being purchased. Then we
estimated a logit regression and predicted whether the loan was
purchased that quarter. In that regression, we included a dummy
variable for each lender, a dummy variable for each quarter, and a
dummy variable for each quarter since that loan was approved, to
capture the age of the loan.[Footnote 50] The following describes the
regression equation we used:
P(loan i was purchased at time t) = logit(al ,at ,ad):
where the parameters of interest, al, can be transformed to express the
relative odds of a loan being purchased or defaulting for each lender,
with one lender excluded as a reference. We used the coefficients al as
the measures of lender risk. In addition, the coefficients t control
for the differential rate of default by time period, and the
coefficients ad control for the age of the loans.
Once we estimated the performance for each lender, we matched it with
each lender's record in the lender performance report, which contained
the risk rating. For 7(a) loans, we matched our performance measures
with the lender risk rating using a "crosswalk" file obtained from SBA.
[Footnote 51] Because the data we obtained from SBA only included loans
that were approved from January 2003 to December 2007 and a lender had
to have made at least 100 loans during that time period to make our
analysis meaningful, we were only able to obtain measures for 308 of
the 4,673 7(a) lenders in the March 2008 lender performance report. We
were more likely to obtain measures for larger lenders.[Footnote 52]
For example, we were able to obtain measures for 56 of the 60 lenders
with more than $100 million in outstanding SBA-guaranteed loan
balances. In all, the 308 lenders, plus the lender excluded as the
reference case, represented approximately 79 percent of the outstanding
balance and 85 percent of the outstanding loans reported in the March
2008 lender performance report. For 504 lenders, we were able to obtain
measures for 86 of the 270 lenders. We were able to obtain 47 of the 48
lenders in the largest peer group--that is, those lenders with more
than $100 million in outstanding SBA-guaranteed loan balances.
To determine how SBA uses the lender risk rating system in its lender
oversight activities, we reviewed agency documents and conducted
interviews to document SBA's practices for assessing and monitoring the
risk of lenders and loan portfolios. We then compared these practices
against (1) the industry standards we identified through our interviews
with federal financial regulators and lenders and reviews of their
documents and (2) our internal control standards. We also obtained and
analyzed SBA data on risk ratings and on-site examinations from 2005
through 2008 to determine the role that the lender risk ratings played
in identifying lenders for an on-site review.
To analyze the data on risk ratings and on-site examinations, we had to
make a number of assumptions because the risk ratings were reported by
quarter and we planned on reporting them by year. First, we assigned
lender risk ratings in two different ways. For those lenders that were
reviewed, we assigned them the risk rating that they received during
the quarter that immediately preceded the on-site review. For those
lenders that were not reviewed, we assigned them the lowest risk rating
that they received during that given year. Second, we assigned lenders
to peer groups in two different ways.[Footnote 53] For those lenders
that were reviewed, we assigned them the peer group that they were in
during the quarter that immediately preceded their on-site review. For
those lenders that were not reviewed, we assigned them the peer group
they were in when they received their lowest risk rating. Because
lenders are assigned a risk rating four times in a given year, there
were some instances when they received the same low-risk rating
multiple times in a given year but were in different peer groups when
these ratings were assigned. In these instances, we relied on the most
recent, lowest-risk rating score. For example, a lender could have
received a lender risk rating of 4 in the second, third, and fourth
quarter of a given year. However, the lender was in the highest peer
group during the second and third quarters and in the second highest
peer group in the fourth quarter. We would rely on the most recent
quarter's information and assign this lender a risk rating of 4 and the
second highest peer group. Third, we determined the on-site review date
in two ways. For on-site reviews completed in 2005 and 2006, we relied
on the date that the final report for the on-site review was issued to
determine when an on-site review was completed. For on-site reviews
completed in 2007 and 2008, we were able to rely on an additional
variable included in the data that identified the date the on-site
review was completed to determine when the on-site review was
completed.
We conducted this performance audit from August 2008 to November 2009
in accordance with generally accepted government auditing standards.
Those standards require that we plan and perform the audit to obtain
sufficient, appropriate evidence to provide a reasonable basis for our
findings and conclusions based on our audit objectives. We believe that
the evidence obtained provides a reasonable basis for our findings and
conclusions based on our audit objectives.
[End of section]
Appendix II: Comments from the Small Business Administration:
U.S. Small Business Administration:
Washington D.C. 20416:
October 19, 2009:
Mr. William Shear:
Director, Financial Markets and Community Investment Issues:
U.S. Government Accountability Office:
441 G Street, N.W.
Washington, DC 20548:
Re: Report on U.S. Small Business Administration's (SBA) Loan and
Lender Monitoring System (L/LMS):
Dear Mr. Shear:
Thank you for the opportunity to respond to the draft report prepared
by the Government Accountability Office (GAO) titled "Actions Needed to
Improve the Usefulness of the Agency's Lender Risk Rating System,"
report number GAO-10-53. We would like to complement you and your staff
on the work that went into the report.
We are pleased by the draft report's finding that the system (L/LMS)
was generally successful in distinguishing between higher- and lower-
risk lenders", and that by developing the risk rating system,
SBA has taken a positive step toward improving its oversight of
lenders...the lender risk rating system enables SBA for the first time
to systematically and routinely monitor the performance of all lenders.
including lenders with the smallest loan portfolios, which SBA had not
routinely monitored.
We also appreciate GAO's recommendation that SBA should rely more on
L/LLMS in its targeting of lenders for on-site reviews, as it further
demonstrates GAO's belief that L/LMS is a useful tool in evaluating the
relative risk of individual lenders to SBA.
We understand that GAO was asked to compare SBA's risk rating system
against those used by federal financial regulators. However, we agree
with GAO's statement that "although the federal financial regulators
and SBA both oversee lenders, their missions differ, and as a result
they may choose to focus on different variables in conducting off-site
monitoring." We would like to further note that the federal financial
regulators oversee the majority of SBA's lending partners; therefore.
SBA's lender oversight program is designed to provide effective
monitoring of lenders' SBA operations while also avoiding duplication
of the federal financial regulators' oversight efforts. We believe
L/LMS is a critical component of this endeavor.
SBA generally agrees with GAO's recommendations, which focused on two
main issues: the L/LMS validation process and the use of L/LMS results
in the on-site review process. SBA's response to each of the four
recommendations follows. In addition, we have included a technical
correction to GAO's draft report in an attachment to this letter.
1. Ensure that SBA's contractor follows sound model validation
practices. These practices should include (1) testing of the lender
risk rating system data, processes, and results, including a routine
reassessment of which factors are the most predictive of lender
performance; (2) utilizing an independent party to conduct validations;
and (3) maintaining complete documentation of the validation process
and results.
SBA generally agrees with this recommendation and is already taking
steps to address it. As noted in the report, SBA is currently
undertaking a redevelopment of L/LMS; thus the timing of GAO's
recommendations is helpful for SBA to ensure that best practices are
incorporated into the redevelopment validation process. SBA and its
contractors are currently working to increase the level of
documentation of the validation process to be consistent with the more
rigorous standards established by federal financial regulators.
Furthermore, under the new L/LMS contract, SBA has greater flexibility
to reassess the predictiveness of the factors used in the model and
refine the model if necessary. Finally, in regard to the recommendation
that SBA utilize an independent party to conduct validations, we
appreciate GAO's statement that an independent party may include
internal staff not involved in the development of the model, such as
internal audit staff or a risk management unit. This provides SBA with
a workable solution for achieving independent validation without
violating the proprietary rights of our contractors. We are in the
process of establishing an independent review process, which will be
utilized in our current redevelopment.
2. Use SBA's own data to assess how well the lender risk ratings
predict individual lender performance.
SBA remains confident that the lender risk ratings provide an accurate
prediction of lender performance. However, SBA will look into whether
alternate measures would be useful to supplement the lender risk
ratings.
3. Develop a strategy for targeting lenders for on-site reviews that
relies more on SBA's lender risk ratings.
SBA believes that its on-site review is an effective tool in the
monitoring of 7(a) and 504 participants. While we agree with GAO's
comments that between 2005 and 2008 on-site reviews were limited and
primarily focused on the largest lenders, we wish to point out that we
have significantly increased the number of lenders reviewed since SBA
began charging for the cost of on-site reviews late in FY2007.
As noted in the draft report, SBA generally conducts on-site reviews of
7(a) lenders with SBA loan portfolios of $10 million or more and 504
lenders with SBA-guaranteed debentures totaling $30 million or more.
These lenders account for approximately 85 percent of SBA's entire
guaranteed portfolio.
Moreover, SBA notes that the lenders with high risk ratings that were
not reviewed in the 2008 review cycle only represent approximately 2
percent of SBA's total 7(a) and 504 portfolio. SBA chooses to focus its
resources on reviewing lenders that represent the greatest risk to
taxpayer dollars; therefore it must consider both a lender's risk
rating and the impact of that lender on the entire SBA portfolio.
As noted in 13 C.F.R. 120.1051, SBA considers several factors in
determining when to perform an on-site review, including the lender's
risk rating, the size of the lender's portfolio, results of prior on-
site reviews, responsiveness in correcting deficiencies noted in prior
reviews, and other risk-related information. SBA will consider revising
its internal policies to better reflect the use of these additional
factors in prioritizing on-site reviews; however, we expect to continue
to focus our on-site review resources on 7(a) lenders with SBA loan
portfolios of $10 million or more and 504 lenders with SBA-guaranteed
debentures totaling $30 million or more, as these lenders pose the
greatest potential risk to the entire SBA portfolio.
4. Consider revising SBA policies and procedures for conducting on-site
reviews. These revised policies and procedures could require staff to
(1) use lender risk ratings to tailor the scope of file reviews
performed during on-site reviews to areas that pose the greatest risk,
(2) incorporate an assessment of lenders' credit decisions in file
reviews, and (3) use the results of expanded file reviews to identify
information, such as emerging lending trends, that could be
incorporated into its lender risk rating system.
SBA is in the process of reprocuring its on-site review contract. As
part of the reprocurement process, SBA included the ability to conduct
reviews that can be better tailored to specific concerns about an
individual lender, including portfolio performance problems as
evidenced by its risk rating. We are in the process of evaluating GAO's
recommendations regarding the addition of assessment of lender credit
decisions in the reviews to determine how to approach this
recommendation. We will also investigate ways in which the results of
on-site reviews can inform the risk rating system.
Once again, thank you for the opportunity to comment on your report.
Please contact Tiffani Cooper, GAO Liaison, at (202) 205-6702 should
you have any questions.
Sincerely,
Signed by:
Eric R. Zarnikow:
Associate Administrator:
Office of Capital Access:
[End of section]
Appendix III: Predictive Performance of the March 2007 and March 2008
Lender Risk Ratings:
We performed two types of statistical tests to determine how well SBA's
lender risk ratings predicted individual lender performance.[Footnote
54] For both tests, we focused on how well the March 2007 lender risk
ratings predicted the performance of lenders for the following year and
how well the March 2008 lender risk ratings predicted the performance
of lenders for the following 6 months. First, we compared raw scores
from SBA's lender risk rating system to actual default rates for 7(a)
and 504 lenders to determine how well the lender risk ratings
identified the best and worst performing lenders. We divided lenders
into two groups--those with lender default rates in the top 50 percent
of all lender default rates and those with default rates that were in
the bottom 50 percent of all lender default rates. We found that SBA's
risk ratings were generally successful at distinguishing the
performance of about two-thirds of the 7(a) and 504 lenders in our
sample (see tables 2 and 3). For example, table 2 shows that 96 of the
approximately 300 lenders in our sample were in the top 50 percent
based on the March 2007 lender risk ratings and actual lender default
rates, while another 99 lenders were in the bottom 50 percent based on
both rankings. We also compared how well an alternate measure of lender
performance--the currency rate--divided lenders into these same two
performance groups and found that overall, it also correctly separated
about two-thirds of the lenders in our sample.
Table 2: Comparison of Alternative Rankings and Rankings Based on 2007
Lender Risk Rating Raw Scores, 2007 Currency Rates, and 2008 Lender
Risk Rating Raw Scores for 7(a) Lenders:
Comparison of March 2007 lender risk rating and defaults between March
2007 and March 2008:
Ranking based on March 2007 lender risk rating raw score:
Alternative ranking based on defaults: Top 50%:
Top 50%: 96;
Bottom 50%: 55;
Total: 152.
Alternative ranking based on defaults: Bottom 50%;
Top 50%: 55;
Bottom 50%: 99;
Total: 154.
Alternative ranking based on defaults: Total;
Top 50%: 151;
Bottom 50%: 155;
Total: 306.
Comparison of March 2007 currency rate and defaults between March 2007
and March 2008:
Ranking based on March 2007 currency rate:
Alternative ranking based on defaults: Top 50%:
Top 50%: 88;
Bottom 50%: 64;
Total: 152.
Alternative ranking based on defaults: Bottom 50%;
Top 50%: 62;
Bottom 50%: 92;
Total: 154.
Alternative ranking based on defaults: Total;
Top 50%: 150;
Bottom 50%: 156;
Total: 306.
Comparison of March 2007 lender risk rating and defaults between March
2008 and September 2008:
Ranking based on March 2007 lender risk rating raw score:
Alternative ranking based on defaults: Top 50%:
Top 50%: 87;
Bottom 50%: 66;
Total: 153.
Alternative ranking based on defaults: Bottom 50%;
Top 50%: 64;
Bottom 50%: 91;
Total: 155.
Alternative ranking based on defaults: Total;
Top 50%: 151;
Bottom 50%: 157;
Total: 308.
Source: GAO analysis of SBA data.
Note: The number of lenders in the March 2007 lender performance report
that we were able to match with default rates we produced was two less
than in the March 2008 lender performance report.
[End of table]
Table 3: Comparison of Alternative Rankings and Rankings Based on 2007
Lender Risk Rating Raw Scores, 2007 Currency Rates, and 2008 Lender
Risk Rating Raw Scores for 504 Lenders:
Comparison of March 2007 lender risk rating and defaults between March
2007 and March 2008:
Ranking based on March 2007 lender risk rating raw score:
Alternative ranking based on defaults: Top 50%:
Top 50%: 23;
Bottom 50%: 19;
Total: 42.
Alternative ranking based on defaults: Bottom 50%;
Top 50%: 14;
Bottom 50%: 30;
Total: 44.
Alternative ranking based on defaults: Total;
Top 50%: 37;
Bottom 50%: 49;
Total: 86.
Comparison of March 2007 currency rate and defaults between March 2007
and March 2008:
Ranking based on March 2007 currency rate:
Alternative ranking based on defaults: Top 50%:
Top 50%: 28;
Bottom 50%: 14;
Total: 42.
Alternative ranking based on defaults: Bottom 50%;
Top 50%: 13;
Bottom 50%: 31;
Total: 44.
Alternative ranking based on defaults: Total;
Top 50%: 41;
Bottom 50%: 45;
Total: 86.
Comparison of March 2007 lender risk rating and defaults between March
2008 and September 2008:
Ranking based on March 2007 lender risk rating raw score:
Alternative ranking based on defaults: Top 50%:
Top 50%: 24;
Bottom 50%: 18;
Total: 42.
Alternative ranking based on defaults: Bottom 50%;
Top 50%: 17;
Bottom 50%: 27;
Total: 44.
Alternative ranking based on defaults: Total;
Top 50%: 41;
Bottom 50%: 45;
Total: 86.
Source: GAO analysis of SBA data.
[End of table]
We used the same data to perform the second statistical test:
determining the correlation between the rankings based on lender
default rates and (1) the lender risk ratings and (2) the alternate
measure--currency rate. We found that for both 7(a) and 504 lenders,
there was a positive correlation between actual performance (lender
default rates) and the lender risk ratings and currency rate. For the
largest 7(a) lenders (that is, those lenders with SBA-guaranteed
portfolios of at least $100 million), the lender risk ratings were more
correlated to the lender default rates than was the currency rate. For
504 lenders, we found that both measures--the lender risk rating and
the currency rate--performed about the same (see table 4).
Table 4: Results of Correlation Analysis:
Measure: Raw rating score from March 2007;
Comparison: Lender's relative odds of default from March 2007 through
March 2008;
7(a): $100 million or more: .48; (50);
7(a): Between $10 million and $100 million: .34; (183);
7(a): Total: .31; (308);
504: $100 million or more: .42; (39);
504: Between $30 million and $100 million: .42; (47);
504: Total: .40; (86).
Measure: Gross currency rate from March 2007;
Comparison: Lender's relative odds of default from March 2007 through
March 2008;
7(a): $100 million or more: .17; (50);
7(a): Between $10 million and $100 million: .37; (183);
7(a): Total: .35; (308);
504: $100 million or more: .48; (39);
504: Between $30 million and $100 million: .42; (47);
504: Total: .42; (86).
Measure: Raw rating score from March 2008;
Comparison: Lender's relative odds of default from March 2008 through
September 2008;
7(a): $100 million or more: .54; (56);
7(a): Between $10 million and $100 million: .21; (187);
7(a): Total: .23; (308);
504: $100 million or more: .32; (47);
504: Between $30 million and $100 million: .44; (39);
504: Total: .38; (86).
Measure: Gross currency rate from March 2008;
Comparison: Lender's relative odds of default from March 2007 through
September 2008;
7(a): $100 million or more: .30; (56);
7(a): Between $10 million and $100 million: .16; (187);
7(a): Total: .16; (308);
504: $100 million or more: .34; (47);
504: Between $30 million and $100 million: .37; (39);
504: Total: .34; (86).
Source: GAO analysis of SBA data.
Note: The numbers in parentheses represent the number of lenders in
each category.
[End of table]
[End of section]
Appendix IV: Small Business Predictive Score:
The Small Business Predictive Score (SBPS) predicts loan performance.
Specifically, it predicts the likelihood of severe delinquency (61 or
more days past terms) over the next 18 to 24 months, including
bankruptcies and charge-offs.[Footnote 55] It is an off-the-shelf
product that was developed by Fair Isaac using consumer and business
credit bureau data. The model is able to produce scores--ranging from 1
to 300, 1 being highest risk and 300 being lowest risk--using either a
mix of consumer and business data, only data from the consumer credit
bureaus, or only business data from Dun & Bradstreet. According to SBA
officials, approximately 74 percent of its 7(a) loans and 83 percent of
its 504 loans are scored using both consumer and business data.
Approximately 17 percent of its 7(a) loans and 8 percent of its 504
loans are scored using consumer data only, while 9 percent of its 7(a)
loans and 504 loans are scored with Dun & Bradstreet data only.
As we reported in 2004, Dun & Bradstreet collects these data from
various sources and processes them through a five-step quality
assurance process.[Footnote 56] First, Dun & Bradstreet collects data
from more than 150 million businesses globally and continuously updates
its databases more than 1 million times daily based on real-time
business transactions. Second, it matches SBA records with its records
and achieves at least a 95 percent match of the data on 11 critical
pieces of information used to identify the borrower. Third, Dun &
Bradstreet assigns a unique identifier to each company. Fourth, Dun &
Bradstreet identifies the corporate linkage of a business's branches or
subsidiaries with their parent entity to help SBA understand their
complete corporate exposure between borrowers and their parent
entities. Finally, Dun & Bradstreet generates predictive indicators of
a business's potential inability to repay a loan. Dun & Bradstreet
officials refer to this process as the DUNSRight process.
We performed independent tests to determine how well the SBPS predicted
the performance of 7(a) loans. Specifically, we used a logit regression
to determine how well the SBPS at loan origination predicted the
default of loans with disbursement amounts above and below $150,000.
[Footnote 57] We examined loans that were approved between 2003 and
2007 and default rates over the period of January 2007 to September
2008.
We found that the origination SBPS was predictive for loans that were
both less than $150,000 and more than $150,000. However, the SBPS was
estimated to have a larger effect on the performance of loans that were
less than $150,000. Table 5 shows the coefficients from the logistic
regression we ran. The coefficient estimated for the sample of loans
that were less than $150,000 is more negative than that for loans that
were more than $150,000, indicating that an increase in the SBPS (which
represents a decrease in the predicted risk of the loan) lowers the
rate of default by a greater increment. Additionally, as shown in the
last column, the difference in the coefficients between the two groups
is statistically significant.
Table 5: Predictive Ability of SBPS for Loans below and above $150,000:
SPBS score:
Subset of data: SPBS score: Below $150,000: -0.0243; (0.000297);
Subset of data: SPBS score: Above $150,000: -0.0189; (0.000760);
SPBS score: Difference between the effects: 0.00555; (0.000815).
Source: GAO analysis of SBA data.
Note: Standard errors of the logit regression are in parentheses. The
logistic regressions corrected for the age of the loans and economic
conditions. Expressed in terms of a change in odds, a one-point
increase in the origination SBPS will lower the odds of default in a
specific quarter by 2.4 percent for loans below $150,000 and 1.9
percent for loans above $150,000.
[End of table]
[End of section]
Appendix V: GAO Contact and Staff Acknowledgments:
GAO Contact:
William B. Shear, (202) 512-8678 or shearw@gao.gov:
Staff Acknowledgments:
In addition to the contact named above, Paige Smith (Assistant
Director), Triana Bash, Ben Bolitzer, Tania Calhoun, Emily Chalmers,
Marc Molino, Jill Naamane, Anh Nguyen, Carl Ramirez, and Stacy Spence
made key contributions to this report.
[End of section]
Footnotes:
[1] The proceeds of 7(a) loans may be used for working capital and
other general business purposes, while the proceeds of 504 loans may be
used for fixed capital. Section 7(a) of the Small Business Act, as
amended, codified at 15 U.S.C. § 636(a); Section 504 of the Small
Business Investment Act of 1958, as amended, codified at 15 U.S.C. §
696.
[2] GAO, Small Business Administration: New Service for Lender
Oversight Reflects Some Best Practices, but Strategy for Use Lags
Behind, [hyperlink, http://www.gao.gov/products/GAO-04-610]
(Washington, D.C.: June 8, 2004).
[3] SBA, Office of Inspector General, Oversight of SBA Supervised
Lenders, Report no. 8-12 (Washington, D.C.: May 9, 2008).
[4] The federal financial regulators we selected have policies and
procedures for monitoring credit risk that are relevant to SBA. We
focused on the largest lenders because they would be the most likely to
have off-site monitoring tools similar to SBA's lender risk rating
system. According to SBA, there are approximately 5,000 SBA lenders.
Although our sample of 10 large lenders is nongeneralizable, it offers
perspectives on how some lenders conduct off-site monitoring.
[5] GAO, Standards for Internal Control in the Federal Government,
[hyperlink, http://www.gao.gov/products/GAO/AIMD-00.21.3.1]
(Washington, D.C.: November 1999) and Internal Control Management and
Evaluation Tool, [hyperlink, http://www.gao.gov/products/GAO-01-1008G]
(Washington, D.C.: August 2001).
[6] The currency rate is the sum of the dollar balance of guaranteed
loans that are less than 30 days past due divided by the dollar balance
of the total portfolio of guaranteed loans outstanding.
[7] The American Recovery and Reinvestment Act of 2009 authorized SBA
to temporarily increase the maximum 7(a) guarantee from 85 percent to
90 percent. SBA lenders consist of private banks, credit unions, and
small business lending companies. Small business lending companies are
nondepository institutions licensed by SBA that are not subject to
state or federal supervision or examination other than oversight
conducted by SBA.
[8] A debenture is an unsecured debt backed only by the
creditworthiness of the borrower. Debentures have no collateral, and
SBA takes a junior lien position on the project property. The yields
may vary from high to low, depending on who backs the debenture.
[9] Public Law No. 104-208, Div. D, § 102, 110 Stat. 3009-724, 3009-
725, codified at 15 U.S.C. § 633, as amended.
[10] [hyperlink, http://www.gao.gov/products/GAO-04-610].
[11] The SBPS predicts the likelihood of a loan becoming severely
delinquent.
[12] When a loan defaults, the lender asks SBA to honor the guarantee
(that is, purchase the loan). The 12 months' actual purchase rate is
calculated by dividing total gross dollars of the lender's loans
purchased during the past 12 months by the sum of total gross
outstanding dollars of SBA loans at the end of the 12-month period and
total gross dollars purchased during the past 12 months.
[13] The problem loan rate is calculated by dividing the sum of total
gross outstanding dollars of a lender's loans that are 90 days or more
delinquent and gross dollars in liquidation by total gross dollars
outstanding.
[14] According to SBA officials, the SBPS was validated to be
predictive of loan purchases, as well as delinquencies.
[15] The projected purchase rate is calculated by multiplying the
amount of a lender's guaranteed loan dollars outstanding by the
probability of their purchase. This total is then divided by the
lender's total SBA-guaranteed dollars outstanding.
[16] According to SBA, lenders with a risk rating of 1 are considered
strong in every respect and typically score well above their peer group
averages for all or nearly all of the rating factors. The SBA
operations of an SBA lender rated as a 2 are considered good and
typically are above average for all or nearly all of the rating
factors. Similar to lenders rated as a 2, lenders rated as a 3 are
considered about average for all or nearly all of the rating factors
but have room for improvement, should monitor their portfolios closely,
and should consider methods to improve loan performance. Lenders rated
as a 4 or 5 are considered below or well-below average, respectively,
for all or nearly all rating factors that are used to calculate the
lender risk ratings.
[17] The process for assigning lender risk ratings to 504 lenders
differs from the process for 7(a) lenders in two ways. First, the 504
lender risk ratings are based on three factors: (1) past 12 months'
actual purchase rate, (2) problem loan rate, and (3) average SBPS of
each lender's portfolio. Second, the peer groups are sized differently.
The 504 peer groups consist of lenders with portfolios of (1)
$100,000,000 or more; (2) $30,000,000 to $99,999,999; (3) $10,000,000
to $29,999,999; (4) $5,000,000 to $9,999,999; and (5) less than
$5,000,000.
[18] SBA lenders are required to report monthly to SBA on the status of
their SBA-guaranteed portfolio. To offset some of the costs of the 7(a)
program, SBA assesses lenders two fees on each 7(a) loan, an up-front
guarantee fee that may be passed on to the borrower and an annual
servicing fee. 15 U.S.C. §§ 636(a)(23), (18).
[19] Call reports are quarterly reports that collect basic financial
data on commercial banks in the form of a balance sheet and income
statement (formally known as Report of Condition and Income).
[20] A FICO score is a credit score derived from the credit model
developed by the Fair Isaac Corporation. The FICO score is calculated
by all three of the major credit bureaus from reported payment
information. A higher FICO score indicates better credit, and a FICO
score below 600 is considered poor.
[21] Our measure of defaults is the purchase rate.
[22] In order to estimate default rates, we needed a meaningful number
of loans for each lender. Therefore, we excluded from our sample 7(a)
and 504 lenders that had less than 100 loans approved between January
2003 and December 2007. As a result, our sample of lenders does not
generally include lenders with smaller guaranteed portfolios (such as
portfolios of less than $10,000,000).
[23] We identified 308 7(a) lenders in our sample that had at least 100
loans approved between January 2003 and December 2007. These 308
lenders' loans represented about 79 percent of the total outstanding
portfolio balance and about 85 percent of the total outstanding SBA-
guaranteed loans, based on the March 2008 lender performance report.
For each of these lenders, we determined performance by estimating the
relative odds of a loan in that portfolio being purchased (or
defaulting), correcting for the age and current economic conditions.
For more information on the method used, see appendix I.
[24] The Basel Committee on Banking Supervision provides a forum for
banking regulators to regularly cooperate on banking supervisory
matters. Its objective is to enhance understanding of key supervisory
issues and improve the quality of banking supervision worldwide. It
seeks to do so by facilitating the exchange of information on national
supervisory issues, approaches, and techniques with a view to promoting
common understanding. At times, the committee develops guidelines and
supervisory standards in various areas--for example, the Basel
Committee's Accord Implementation Group has developed guiding
principles on the validation of rating systems.
[25] [hyperlink, http://www.gao.gov/products/GAO/AIMD-00.21.3.1] and
[hyperlink, http://www.gao.gov/products/GAO-01-1008G].
[26] [hyperlink, http://www.gao.gov/products/GAO-04-610].
[27] For example, the contractor determined whether those lenders that
were rated as a 1 had lower rates of purchases than those groups of
lenders that were rated as 2, 3, 4, or 5. The SBA contractor focused on
two variables--purchase rates and cumulative net cash yields--to assess
how well the risk ratings rank ordered lenders by group.
[28] In particular, the contractor used the K-S statistic, which tests
whether the distribution of a variable from a sample matches some other
probability distribution. For example, the K-S statistic can test
whether purchases follow a pattern based on a lender's risk rating or
whether they follow a random distribution. Guidance from federal
financial regulators states that this statistic is commonly used in the
banking industry.
[29] [hyperlink, http://www.gao.gov/products/GAO/AIMD-00.21.3.1] and
[hyperlink, http://www.gao.gov/products/GAO-01-1008G].
[30] [hyperlink, http://www.gao.gov/products/GAO-04-610].
[31] [hyperlink, http://www.gao.gov/products/GAO/AIMD-00.21.3.1] and
[hyperlink, http://www.gao.gov/products/GAO-01-1008G].
[32] According to the 2005 validation report, the contractor performed
a stepwise regression to determine if using last 24-month purchases,
last 12-month charge-offs, or a modified problem loan rate would
increase the model's ability to predict future purchases among 7(a)
lenders. The contractor found that there would be no benefit to using
these variables.
[33] These additional variables included the age of the portfolio and
type of loan product.
[34] The K-S statistic for 7(a) lender ratings decreased from 36 in
2005 to a range of 27 to 29 in 2007.
[35] [hyperlink, http://www.gao.gov/products/GAO/AIMD-00.21.3.1] and
[hyperlink, http://www.gao.gov/products/GAO-01-1008G].
[36] [hyperlink, http://www.gao.gov/products/GAO/AIMD-00.21.3.1] and
[hyperlink, http://www.gao.gov/products/GAO-01-1008G].
[37] SBA, Office of Inspector General, SBA's Use of the Loan and Lender
Monitoring System, Report no. 7-21 (Washington, D.C.: May 2, 2007).
[38] NAICS was developed as the standard for federal statistical
agencies in classifying business establishments for the collection,
analysis, and publication of statistical data related to the business
economy of the United States. NAICS was developed under the auspices of
the Office of Management and Budget and adopted in 1997 to replace the
old Standard Industrial Classification system.
[39] According to OCC officials, they review all lenders on a regular
schedule.
[40] Lender risk ratings are used to prioritize reviews for lenders
within the same peer group.
[41] According to SBA, it implemented fee-based reviews in late fiscal
year 2007.
[42] SBA, Report no. 7-21.
[43] GAO, Small Business Administration: Progress Made but Improvements
Needed in Lender Oversight, [hyperlink,
http://www.gao.gov/products/GAO-03-90] (Washington, D.C.: Dec. 9,
2002).
[44] GAO, Small Business Administration: Additional Guidance on
Documenting Credit Elsewhere Decisions Could Improve 7(a) Program
Oversight, [hyperlink, http://www.gao.gov/products/GAO-09-228]
(Washington, D.C.: Feb. 12, 2009).
[45] The federal financial regulators we selected have policies and
procedures for monitoring credit risk that are relevant to SBA. We
focused on the largest lenders because they would be most likely to use
off-site monitoring tools similar to SBA's lender risk rating system.
[46] According to SBA, there are approximately 5,000 SBA lenders.
Although our sample of 10 large lenders is nongeneralizable, it offers
perspectives on how some lenders conduct off-site monitoring.
[47] GAO, Standards for Internal Control in the Federal Government,
[hyperlink, http://www.gao.gov/products/GAO/AIMD-00.21.3.1]
(Washington, D.C.: November 1999) and Internal Control Management and
Evaluation Tool, GAO-01-1008G (Washington, D.C.: August 2001).
[48] GAO, Small Business Administration: New Service for Lender
Oversight Reflects Some Best Practices, but Strategy for Use Lags
Behind, [hyperlink, http://www.gao.gov/products/GAO-04-610]
(Washington, D.C.: June 8, 2004).
[49] The currency rate is the sum of the dollar balance of guaranteed
loans that are less than 30 days past due divided by the dollar balance
of the total portfolio of guaranteed loans outstanding. For comparison
purposes, we subtracted the currency rate from 100, so that lower
currency rates would be consistent with higher default rates.
[50] This regression was weighted by the guaranteed amount of the loan
at the time of approval.
[51] We tested the crosswalk file obtained from SBA by comparing the
outstanding balance in the March 2008 lender performance report to the
amount disbursed by lenders in the administrative data for the lenders
that we matched. The correlation was .95 for 7(a) lenders and .99 for
504 lenders. We also compared the number of loans in the lender
performance report and the number of loans in the administrative data.
The correlation was .99 for 7(a) lenders and .99 for 504 lenders.
[52] Note that for one 7(a) and one 504 lender, we did not obtain a
ranking because that lender was the reference category to which the
other lenders' odds were relative.
[53] SBA assigns lenders to different peer groups based on their
portfolio size.
[54] In order to estimate default rates, we needed a meaningful number
of loans for each lender. Therefore, we excluded from our sample 7(a)
and 504 lenders that had less than 100 loans approved between January
2003 and December 2007. As a result, our sample of lenders does not
generally include lenders with smaller guaranteed portfolios (such as
portfolios of less than $10,000,000).
[55] According to SBA officials, the SBPS was validated to be
predictive of loan purchases, as well as delinquencies.
[56] GAO, Small Business Administration: New Service for Lender
Oversight Reflects Some Best Practices, but Strategy for Use Lags
Behind, [hyperlink, http://www.gao.gov/products/GAO-04-610]
(Washington, D.C.: June 8, 2004).
[57] Our measure of default is the purchase rate.
[End of section]
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