Information Resource Management Internal Control Issues 	 
(10-MAR-05, GAO-05-288R).					 
                                                                 
In a recently completed report for Congress, we evaluated how the
U.S. Department of Agriculture's (USDA) Rural Housing Service	 
(RHS) makes eligibility determinations for its rural housing	 
programs. As part of that review, we used 2000 census data to	 
determine the populations of the rural areas that received RHS	 
housing program loans and grants. We obtained information on the 
RHS loans and grants provided to communities, from October 1998  
through April 2004, from databases maintained by USDA's 	 
Information Resource Management (IRM) in St. Louis, Missouri. As 
with any system, the accuracy of the data and the process used	 
for entry affects reliability and usefulness for management and  
reporting purposes. During our review, we identified several	 
issues that raised concerns about the accuracy of the information
in the IRM databases. For example, while we originally intended  
to geocode (that is, match) 5 years of the national RHS housing  
loan and grant portfolio to specific communities, the time needed
to ensure the reliability of the data required us to limit much  
of our analysis to five states (Arizona, California, Maryland,	 
Massachusetts, and Ohio). This report is a follow-up on our	 
report to Congress, and its purpose is to discuss the		 
implications of the data issues for your management and reporting
functions. In this report, we describe (1) the types of 	 
inaccuracies we encountered with the RHS data and (2) what, if	 
any, reviews and systems controls are in place to detect or	 
control database errors.					 
-------------------------Indexing Terms------------------------- 
REPORTNUM:   GAO-05-288R					        
    ACCNO:   A19036						        
  TITLE:     Information Resource Management Internal Control Issues  
     DATE:   03/10/2005 
  SUBJECT:   Data integrity					 
	     Eligibility determinations 			 
	     Federal aid for housing				 
	     Information resources management			 
	     Internal controls					 
	     Population statistics				 
	     Program evaluation 				 
	     Rural housing programs				 
	     Data bases 					 
	     Data collection					 
	     2000 Decennial Census				 

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GAO-05-288R

United States Government Accountability Office Washington, DC 20548

March 10, 2005

The Honorable Russell T. Davis
Administrator
Rural Housing Service
U.S. Department of Agriculture
1400 Independence Avenue, SW
Washington, D.C. 20250-1300

Subject: Information Resource Management Internal Control Issues

Dear Mr. Davis:

In a recently completed report for Chairman Robert W. Ney, we evaluated
how the U.S. Department of Agriculture's (USDA) Rural Housing Service
(RHS) makes

1

eligibility determinations for its rural housing programs. As part of that
review, we used 2000 census data to determine the populations of the rural
areas that received RHS housing program loans and grants. We obtained
information on the RHS loans and grants provided to communities, from
October 1998 through April 2004, from databases maintained by USDA's
Information Resource Management (IRM) in St. Louis, Missouri. As with any
system, the accuracy of the data and the process used for entry affects
reliability and usefulness for management and reporting purposes. During
our review, we identified several issues that raised concerns about the
accuracy of the information in the IRM databases. For example, while we
originally intended to geocode (that is, match) 5 years of the national
RHS housing loan and grant portfolio to specific communities, the time
needed to ensure the reliability of the data required us to limit much of
our analysis to five states (Arizona, California, Maryland, Massachusetts,
and Ohio).

This report is a follow-up on our report to Chairman Ney, and its purpose
is to discuss the implications of the data issues for your management and
reporting functions. In this report, we describe (1) the types of
inaccuracies we encountered with the RHS data and (2) what, if any,
reviews and systems controls are in place to detect or control database
errors. We also make recommendations intended to improve the accuracy of
RHS loan and grant databases.

1GAO, Rural Housing: Changing the Definition of Rural Could Improve
Eligibility Determinations, GAO-05-110 (Washington, D.C.: Dec. 3, 2004).

                         GAO-05-288R Internal Controls

To meet these objectives, we contacted officials at RHS headquarters. In
addition, we spoke with state office and St. Louis, Missouri IRM officials
to discuss procedures used to record and check the information entered
into the Dedicated Loan Origination and Servicing System, Guaranteed Loan
System, and the Multifamily Housing Information System databases; reviewed
RHS documents and plans regarding databases system improvements; and
applied GAO's standards for internal control.

We conducted our review from November 2004 through January 2005 in
accordance with generally accepted government auditing standards.

Results in Brief

Our analysis of information in USDA's IRM loan and grant databases raised
concerns about the accuracy of the databases. In reviewing 29,000 records
for five states we found incorrect, incomplete, and inconsistent entries.
For example, over 8 percent of the community names or zip codes were
incorrect. Additionally, inconsistent spellings of community names
distorted the number of unique communities in the database. More than 400
entries lacked sufficient information (i.e., street addresses, community
names, and zip codes) that are needed to identify the community to which
the loan or grant had been made. As a result, some communities served by
RHS were double counted, others could not be counted, and the ability to
analyze the characteristics of communities served was compromised.

Because data from these systems are used to inform Congress, senior agency
management, and the public about the reach and effectiveness of RHS
programs, eliminating erroneous data will help ensure that key decisions
and analyses are reliably supported. However, we found RHS lacks
appropriate reviews and database entry processes that could prevent or
detect inaccurate or incomplete data in its normal course of business. For
example, RHS does not have procedures for second-party review of the data
in IRM systems. Moreover, while the databases have edit functions in place
that are intended to prevent the entry of nonconforming data (such as the
entry of a community name in a street address field), the functions are
not preventing incorrect or incomplete entries.

Background

The federal government has provided housing assistance to eligible
residents of rural America since the 1930s. Over time, Congress has
expanded the eligibility categories and changed population limits for
determining what areas are eligible for the programs. Currently, the
Housing Act of 1949, as amended, sets forth eligibility criteria
requirements for rural housing programs. Communities with population
levels up to 25,000 may be determined eligible, but as a community's
population increases, the statute imposes additional requirements that
include being "rural in character," having a serious lack of mortgage
credit, or not being located in a metropolitan statistical area (a county
or counties associated with a

core urbanized area of 50,000 or more people). RHS uses judgment to make
decisions on what areas are "rural in character" and uses population as
the primary factor in determining eligibility.

IRM Inaccuracies Include Incorrect or Incomplete Data Fields and
Inconsistent Entry of the Same Data

During our review of records for five states, we identified errors and
inaccuracies that included incorrect, incomplete, and inconsistent
entries. The level of inaccuracy in the records we reviewed raises
questions about the accuracy of the IRM databases as a whole. For example,
when we attempted to geocode the loans and grants on a nationwide basis,
we found that about 7 percent of the community names or zip codes within
the databases were incorrect, while about 8 percent were incorrect in the
five states. Additional inaccuracies we identified included:

o  	Community names were not spelled uniformly throughout the databases.
While many communities were identified consistently in the three different
databases, in numerous instances the same community names had different
spellings, and thus were counted multiple times. Initially, from 29,000
records, we identified 3,222 unique communities in the five states that
received loans and grants. After we corrected for the variations in the
names, the number of unique communities decreased by 208 to 3,014. If such
inaccuracies occurred at the same rate for the rest of the states, RHS
would be significantly overestimating the number of communities it served.

o  	In many cases, so little information was available that we were not
able to identify the communities that had received loans or grants. Thus
we could not identify recipients of more than 400 RHS loans or grants
because the databases lacked information on the street address, name of
community, and zip code. Since population is the primary factor in
determining eligibility, questions arise as to how RHS management can
evaluate eligibility decisions without sufficient information to identify
the community where a loan or grant was made.

o  	In some cases the communities listed were not officially recognized as
"places" by the Census Bureau (Census). According to Census, a "place" is
a concentration of population either legally bounded as an incorporated
place or delineated for statistical purposes as a Censusdesignated place.
If the community listed is not a recognized "place," RHS management would
not have census information available to evaluate eligibility
determinations. For example, Miller, Maryland, was listed in the RHS data
as a community receiving a loan. However, an Allegany County (Maryland)
Boards and Commission staff member stated that to the best of his
knowledge, Miller was never a town, only a farm. We also found a listing
for Central Valley, California, which

should have been listed as Shasta Lake, California-Central Valley has been
part of the incorporated city of Shasta Lake, California, since 1993.

o  	Community names were sometimes listed in the wrong field. For example,
in the Guaranteed Loan System database, we found the community name listed
in the street address field for 73 loans or grants.

Improved Internal Control Would Allow RHS to Better Assess and Verify IRM
Data

On the basis of our review, we determined that RHS lacked sufficient
internal control to ensure the accuracy of IRM data and to help decision
makers reliably assess whether RHS is meeting its accountability goals and
strategic and annual performance goals. According to GAO's Standards for
Internal Control in the Federal Government and related documents, an
agency's system of internal control should include appropriate measures
designed to ensure the validity, accuracy, and completeness of the data in
agency systems and that erroneous

2

data are captured, reported, investigated, and promptly corrected.

The controls that RHS has implemented to ensure the completeness and
accuracy of its databases do not appear to be sufficient. According to one
senior RHS administration official, entering correct loan and grant data
at the field level has been a continuous and frustrating problem. The
official noted that field staff responsible for entering data do not
recognize the importance of uniformly recording correct and complete data.
One agency control for helping to ensure that data are correct would be to
include a second-party review of the data. However, RHS said that they do
not have procedures requiring that the data entered into IRM systems at
state and local levels undergo such a review.

Although there is no second-party review, according to USDA's Fiscal Year
2004 Annual Plan, the databases RHS uses do contain a variety of "edits"
to minimize the risk of inaccurate data input. Staff in state offices we
visited said that the types of errors we found would have been caught if
the edit functions that are built into the systems had worked as intended.
For example, we should not have found key fields left blank or street
address information in the community field and vice versa. These officials
agreed that the high number of nonconforming data entries we identified
indicated that an assessment was needed, particularly to determine if the
edit functions were not detecting the errors or if RHS staff were
overriding the edits.

2GAO, Standards for Internal Control in the Federal Government,
GAO-AIMD-00-21.3.1 (Washington, D.C.: November 1999) provides guidance to
agencies to help them assess, evaluate, and implement effective internal
controls that can be helpful in improving their operational processes and
GAO, Internal Control Management and Evaluation Tool, GAO-01-1008G
(Washington, D.C., August 2001) assists agencies maintain or implement
effective internal control and, when needed, helps them determine what,
where, and how improvements can be made.

Since these data form the basis of information used to inform Congress
(and the public) about the effectiveness of RHS programs, data accuracy is
central to RHS program management and the ability of Congress and other
oversight bodies to evaluate the agency and its programs. The agency has
worked to improve its management information systems (e.g., since 2002,
the agency has spent $10.3 million to improve its management information
systems including developing single and multifamily program data
warehouses, which were designed to improve its reporting capabilities);
however, the system still relies upon information collected and entered
from state and local field offices. Unless steps are taken to ensure that
the data entered into the systems are accurate, simply upgrading the
systems will not result in correct information.

Conclusions

In reviewing RHS data for selected states, we identified various errors
that raise questions about the accuracy of the databases in their
entirety. Although the agency is making efforts to improve its management
information systems, our findings suggest additional measures could ensure
more accurate data entry and reporting, particularly at the field level.
In addition to improving the accuracy of the information, such an effort
could ensure that RHS's investment in system upgrades would provide more
meaningful and useful information to the agency, Congress, and the public.

Recommendations for Executive Action

To improve data entry and accuracy and, in turn, better ensure accurate
internal reporting and reporting to Congress, we recommend that the
Administrator, RHS, take the following actions:

o  	Issue an Administrative Notice to field management and staff
explaining how data are used for management and reporting purposes and
advising them of the need to establish a second-party review to help
ensure that data in the three IRM databases are accurate and complete.

o  Require that each state office correct errors in existing information.

o  	Take corrective action to ensure that system edit functions are in
place and properly functioning.

Agency Comments and Our Evaluation

We provided a draft of this report to USDA for review and comment. The
Acting Undersecretary for Rural Development wrote that USDA recognizes
that accurate and complete loan and grant address data are a critical
component and management resource for its single-family and multifamily
housing programs and emphasized the importance of correctly inputting the
initial address information for loans and grants in the IRM systems to
ensure precision and uniformity. In

response to our recommendations, the Acting Secretary agreed to (1) issue
an Administrative Notice to field management and staff explaining the
importance of entering accurate and complete data into the three loan and
grant databases and establishing a second-party review of address data
input, where necessary; (2) correct existing address information
identified as incorrect in the databases, if possible; and (3) where
needed, enhance system edit functions so that input errors can be
curtailed or eliminated (as budget resources permit).

We are pleased that USDA agrees with us on the importance of accurately
entering loan and grant data and having effective system edit functions,
as well as acting on our recommendations to achieve those goals. However,
the qualifications used in the response raise some concerns. First, GAO's
internal control standards require that design features contribute to data
accuracy and that erroneous data are captured, reported, investigated, and
promptly corrected. Until USDA can demonstrate that its edit functions or
other data entry design features can ensure the accuracy and completeness
of the data in the IRM databases, second-party review would be necessary.
Second, based on our assessment of the problems with the data systems, it
does not appear to us that fixing them as recommended should require a
significant level of additional resources. USDA's complete written
comments appear in the enclosure.

                                     -----

We are sending copies of this report to the Chairman, Subcommittee on
Housing
and Community Opportunity, House Committee on Financial Services, and
other
interested congressional parties. We will make copies available to others
upon
request. This report will also be available at no charge on GAO's Web site
at
http://www.gao.gov.

This report was prepared under the direction of Andy Finkel, Assistant
Director.
Other major contributors included Mark Egger, Richard LaMore, Barbara
Roesmann, and Thomas Taydus. If you have any questions about this report,
please contact me at [email protected] or Andy Finkel at [email protected] or
either
of us at (202) 512-8678.

Sincerely yours,

William B. Shear
Director, Financial Markets and

Community Investments

Enclosure

Enclosure I Comments from the Department of Agriculture

                                  Enclosure I

(250225)

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