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United States Government Accountability Office:

Washington, DC 20548:

March 10, 2005:

The Honorable Russell T. Davis:
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 eligibility determinations for its rural housing 
programs.[Footnote 1] 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.

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.


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:

* 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.

* 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.

* 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 Census- 
designated 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.

* 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 data are captured, reported, investigated, and promptly 
corrected.[Footnote 2]

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 

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.

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 


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:

* 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.

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

* 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

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 or Andy Finkel at or either of us at (202) 512-8678.

Sincerely yours,

William B. Shear:

Director, Financial Markets and Community Investments:


Comments from the Department of Agriculture:


FEB 25 2005:

William B. Shear:
Director, Financial Markets and Community Investment: 
United States Government Accountability Office:
441 G Street, NW: 
Room 2A10: 
Washington, DC 20548:

Dear Mr. Shear:

Thank you for providing the United States Department of Agriculture 
(USDA), Rural Development, with your draft report entitled Information 
Resource Management Internal Control Issues, Report Number GAO-05-288R. 
For your consideration, Rural Development offers the following comments 
on the draft report and requests that a copy of these continents be 
included in your final report.

The draft report indicates that Rural Development's data systems were 
difficult to use for geocoding information. The systems Rural 
Development uses for its loan and grant databases capture basic address 
information, like street address, town or city, and zip code. 
Historically, the address information has been used for certain 
reporting and mailing purposes. The purpose of the address information 
in the systems is not for geocoding it to designations such as census 
tracks or Metropolitan Statistical Areas. While geocoding is 
increasingly relied upon for program reporting purposes, Rural 
Development's data systems may have some limitations in this regard 
since only primary address information is captured. For instance, the 
systems do not identify a loan or grant to a specific census track. 
Census tracks are a common element useful for geocoded type reporting, 
and had our systems included this information, it may have provided 
useful information to the Government Accountability Office.

Nevertheless, Rural Development recognizes that accurate and complete 
loan and grant address data is a critical component and management 
resource for its Single Family and Multi-Family Housing programs. It is 
important that the initial address information for a loan or grant 
input into the Dedicated Loan Origination and Servicing System, the 
Guaranteed Loan System, or the Multifamily Housing Information System, 
be done carefully to ensure precision and uniformity.

Rural Development will issue an Administrative Notice to field 
management and staff that explains the importance of entering accurate 
and complete data into the three loan and grant databases, and for 
establishing a second-party review of address data input, where 
necessary. Existing address information identified as being incorrect 
in the databases will be rectified, if possible. Where needed, Rural 
Development will enhance system edit functions so that data input 
errors for address information can be curtailed or eliminated. Any 
needed system enhancements will be given high priority; however, the 
enhancements would be dependant upon the necessary budget resources to 
complete the necessary development and implementation.

Rural Development is committed to the future of rural communities, and 
intends to continue improving the opportunities for decent, safe, and 
affordable housing in Rural America.

Thank you for the opportunity to comment on the report. If you have any 
questions, please contact John M. Purcell, Director, Financial 
Management Division, at (202) 692-0080. 

Signed by: 

Acting Under Secretary: 
Rural Development: 

[End of section]



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

[2] GAO, 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.