Joint Report: COVID-19 Data Sharing Project Finds Billions Paid to Same Likely Fraudsters

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JOINT 
REPORT 
 
 
U.S. Department of Labor, Office of Inspector General 
U.S. Small Business Administration, Office of Inspector General 
 
 
 
 
 
COVID-19: Data Sharing Project Finds 
Billions Paid to Same Likely Fraudsters 
Under Both the Unemployment 
Insurance and Economic Injury Disaster 
Loan Programs 
 
 
 
 
 
 
Joint Report to: 
U.S. Department of Labor, Employment and Training Administration 
U.S. Small Business Administration, Office of Capital Access 
 
 
 
 
December 5, 2024 
 
DOL OIG Report No. 19-25-001-03-315 
SBA OIG Report No. 25-06 

 
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SBA OIG Report No. 25-06 
U.S. Department of Labor 
Office of Inspector General 
 
Mission Statement 
 
To serve the American people, DOL, and Congress 
by providing independent and objective oversight 
of Departmental programs through audits and 
investigations and by combatting the influence of 
labor racketeering in the workplace. 
 
 
 
 
 
 
 
 
 
 
U.S. Small Business Administration 
Office of Inspector General 
 
Mission Statement 
 
To provide independent, objective, and timely 
oversight to improve the integrity, accountability, 
and performance of SBA and its programs for the 
benefit of the American people. 
 
 
 
 
 
 
 
 
 
 
 
For information on how to report fraud, abuse, or mismanagement, please see 
the last page of this document. 
 

 
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Offices of Inspector General 
U.S. Department of Labor 
U.S. Small Business Administration 
Joint Report 
COVID-19: Data Sharing Project Finds 
Billions Paid to Same Likely Fraudsters 
under Both the Unemployment Insurance 
and Economic Injury Disaster Loan 
Programs 
 
OVERVIEW . . . 
 
WHY WE CONDUCTED THE JOINT PROJECT 
The unemployment insurance (UI) and 
Economic Injury Disaster Loan (EIDL) 
programs provide eligible people and 
businesses with needed relief in the face of 
crises. However, both programs are at risk of 
ineligible individuals attempting to obtain 
benefits. In 2020, soon after Congress 
expanded both programs in response to the 
adverse economic effects caused by the 
Coronavirus Disease 2019 (COVID-19) 
pandemic, both DOL OIG and SBA OIG 
respectively began reporting on heightened 
risks of fraud and found similar fraud 
indicators. 
 
Given the similarities in potential fraud 
indicators in both programs, DOL and SBA 
OIGs conducted a joint project to answer the 
following question:  
 
Could data sharing between the 
Employment and Training Administration 
(ETA) and SBA mitigate the risk of 
fraudulent UI benefit payments and SBA 
disaster program disbursements? 
 
To answer this question, the two OIGs 
entered into a data use agreement to share 
respective pandemic-related data to 
perform data matching analyses. 
 
WHAT WE FOUND 
We found data sharing and matching 
between ETA and SBA could mitigate the risk 
of fraudulent UI benefit payments and SBA 
disbursements. Both OIGs found data 
matching worked as a tool to identify potential 
fraud. DOL OIG identified more than 
$1.3 billion in potentially fraudulent UI and 
EIDL payments made to the same likely 
fraudsters. Matching to a larger dataset, SBA 
OIG identified over $2.25 billion in potentially 
fraudulent EIDLs disbursed, including nearly 
$1.4 billion in EIDL disbursements not 
previously identified by SBA OIG or SBA. 
 
People may be both employed and operating 
a small business, so they may be eligible to 
receive assistance from both programs. 
However, during the pandemic, no data 
sharing mechanism on potential fraud for UI 
and COVID EIDLs existed between ETA and 
SBA. If data sharing and matching had 
existed, the agencies could have conducted a 
higher level of review by matching applicants 
across both programs to mitigate fraudulent 
payments. The implications of fraud impacting 
more than one agency extends beyond 
significant monetary losses, potentially 
impacting expeditious, efficient deployment 
of assistance and decreasing public trust. 
 
WHAT WE RECOMMENDED 
We made five recommendations: four to 
facilitate improved fraud controls via 
collaboration and one (for SBA) to reevaluate 
eligibility. Specifically, we recommended DOL 
and SBA collaborate to evaluate their 
authorities on data sharing and to develop 
further fraud prevention resources. ETA 
stated agreement with one of two 
recommendations. DOL OIG will monitor 
ETA’s corrective action plans to resolve the 
recommendations. SBA agreed with the 
three recommendations, and SBA OIG 
assesses its planned actions will resolve 
those recommendations. 

 
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Contents 
 
 
Background ..................................................................................................................... 1 
Objective and Methodology ............................................................................................. 3 
Results ............................................................................................................................ 3 
Data Matching Finds Same Likely Fraudsters Paid Under Both the UI and 
EIDL Programs ....................................................................................................... 4 
Best Practices for Data Sharing within the Federal Government .......................... 6 
Conclusion ...................................................................................................................... 7 
Recommendations .......................................................................................................... 7 
Analysis of Agency Responses ....................................................................................... 8 
DOL OIG Analysis of Agency Response .................................................................... 8 
SBA OIG Analysis of Agency Response .................................................................. 12 
Tables 
 
Table 1: DOL OIG Data Matching Results ...................................................................... 5 
Table 2: SBA OIG Data Matching Results....................................................................... 5 
Appendices 
 
Appendix A: Scope and Methodology .......................................................................... A-1 
Appendix B: Prior Relevant Coverage .......................................................................... B-1 
Appendix C: U.S. Department of Labor Response ...................................................... C-1 
Appendix D: U.S. Small Business Administration Response....................................... D-1 
Appendix E: Acknowledgments .................................................................................... E-1 

 
 
 
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U.S. Department of Labor 
Office of Inspector General 
200 Constitution Ave, NW 
Washington, DC 20210 
U.S. Small Business Administration 
Office of Inspector General 
409 Third St, SW 
Washington, DC 20416 
DOL and SBA Inspectors General Joint Report 
 
José Javier Rodriguez 
Assistant Secretary 
  for Employment and Training 
U.S. Department of Labor 
 
Isabella Casillas Guzman 
Administrator 
U.S. Small Business Administration 
 
 
The Office of Inspector General (OIG) for the U.S. Department of Labor (DOL) and the 
OIG for the U.S. Small Business Administration (SBA) are issuing this joint report to 
bring to your attention billions of dollars paid because of potential fraud by the same 
likely fraudsters under both DOL’s unemployment insurance (UI) program and SBA’s 
COVID-19 Economic Injury and Disaster Loan (EIDL)1 programs. The two OIGs 
identified this issue through a data use agreement and subsequent data sharing 
and matching project, highlighting an opportunity for the Employment and Training 
Administration (ETA) and SBA to collaborate on data matching2 to mitigate fraud under 
both programs. 
 
BACKGROUND 
 
In March 2020, in response to the adverse economic effects caused by the COVID-19 
pandemic, Congress expanded eligibility for both the UI and EIDL programs as part of 
the Coronavirus Aid, Relief, and Economic Security Act. 
 
Administered jointly by the federal and state governments, the UI program is overseen 
by ETA and is the first economic line of defense against the collective impact of 
unemployment. It acts as a safety net for individuals who lose their jobs through no  
 
 
 
1 The COVID-19 EIDL program includes COVID-19 EIDLs, Emergency EIDL Grants (also referred to as 
“advances” by SBA), Targeted EIDL Advances, and Supplemental Targeted Advances. In this joint report, 
we refer to these different disbursement types as COVID-19 EIDLs. 
2 Data matching is the comparison of different datasets to identify similarities in the records each dataset 
contains. Matches can be made using one or more data elements, such as name, address, email, 
bank account number, et cetera, for verifying or establishing the eligibility of applicants. 

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fault of their own. The UI program requires states to make benefit payments in a timely 
manner, providing needed assistance to unemployed workers while ensuring claimants 
meet eligibility requirements. The expansion of UI eligibility in response to the pandemic 
included the creation of new programs; however, these programs were highly 
susceptible to fraud. 
 
Of more than $888 billion in total federal and state pandemic-related UI benefits,3 
DOL OIG has identified more than $46.9 billion in potentially fraudulent UI benefits paid 
in six specific high-risk areas.4 Two of the six high-risk areas identified as having the 
largest amount of potentially fraudulent payments were for claims with Social Security 
numbers (SSN): (1) filed in multiple states and (2) using suspicious emails. Further, in 
2023, the Government Accountability Office (GAO) estimated the pandemic-related 
fraud rate for the UI program at 11 to 15 percent for the period April 2020 to 
May 2023 and estimated up to $135 billion was lost to fraud.5 
 
The EIDL program, overseen by SBA’s Office of Capital Access (OCA), provides loans 
of up to $2 million to help small businesses, agricultural enterprises, and nonprofit 
organizations that suffered substantial economic injury due to a declared disaster to pay 
for expenses that could have been met had the disaster not occurred. The loans are 
intended to help meet working capital needs such as fixed debt payments and operating 
expenses such as payroll.6 The Coronavirus Aid, Relief, and Economic Security Act and 
subsequent legislation expanded EIDL eligibility and added two additional programs, 
creating the COVID-19 EIDL program. Of the over $400 billion in disbursed COVID-19 
EIDL funds, SBA OIG estimated $136 billion in COVID-19 EIDLs were disbursed to 
potential fraudsters.7 
 
Starting in 2020, both OIGs respectively reported8 on the high risk of fraud in pandemic 
programs, including from identity theft and self-certification.9 In February 2021, 
DOL OIG began reporting on specific indicators of potential fraud identified through 
data analytics, including suspicious email accounts and claims filed across multiple 
states, that were linked to billions of dollars in UI benefit payments. Similarly, in 
 
 
 
3 DOL OIG, Semiannual Report to Congress, Vol. 90 (November 2023) 
4 To date, DOL OIG has issued four alert memoranda on the topic of potential UI fraud identified in 
high-risk areas, identifying a cumulative total of $46.9 billion in potential fraud. Those reports are available 
at the following hyperlinks: February 2021, June 2021, September 2022, and September 2023. 
5 GAO, Unemployment Insurance: Estimated Amount of Fraud during Pandemic Likely Between 
$100 Billion and $135 Billion, Report No. GAO-23-106696 (September 2023),  
https://www.gao.gov/assets/gao-23-106696.pdf 
6 SBA stopped accepting COVID-19 EIDL applications in January 2022 and is no longer accepting 
requests for loan increases or reconsiderations. 
7 SBA OIG, Report No. 23-09 (June 2023) 
8 Full citations for related DOL OIG and SBA OIG reports can be found in Appendix B. 
9 DOL OIG, Report No. 19-20-001-03-315 (April 2020) and SBA OIG, Report No. 20-16 (July 2020) 

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July 2020,10 SBA OIG began reporting on potential fraud indicators and, in June 2023, 
issued the Fraud Landscape white paper highlighting the various fraud schemes 
identified through data analytics.11 
 
OBJECTIVE AND METHODOLOGY 
 
Given the similarities in potential fraud indicators in both programs, DOL and SBA OIGs 
conducted a joint project to answer the following question: 
 
Could data sharing between ETA and SBA mitigate the risk of fraudulent 
UI benefit payments and SBA disaster program disbursements? 
 
To answer this question, the two OIGs shared pandemic-related data then separately 
analyzed and matched two datasets from the respective pandemic programs: 
 
1. a DOL OIG dataset containing information on UI benefits paid for claims with 
SSNs filed in multiple states and used to file UI claims with suspicious email 
accounts; and 
 
2. an SBA OIG dataset containing information on COVID-19 EIDLs with SBA 
hold codes, which are designations SBA can place in the EIDL system to identify 
fraudulent loans or suspected fraudulent loans. 
 
Additionally, SBA OIG prepared a third dataset containing all COVID-19 EIDLs (rather 
than only those with hold codes) disbursed after the dates DOL OIG had issued its first 
three alert memoranda (February 2021, June 2021, and September 2022). Further, the 
two OIGs conducted interviews with ETA’s National Office and SBA’s OCA to gain 
insights into the data exchange efforts with other federal agencies when implementing 
their respective pandemic programs. See Appendix A for more details. 
 
RESULTS 
 
We found data sharing and matching between ETA and SBA could mitigate the risk of 
fraudulent UI benefit payments and SBA disbursements. Both OIGs found data 
matching worked as a tool to identify potential fraud. DOL OIG data matched the two 
shared datasets and found more than $1.3 billion in potentially fraudulent UI and EIDL 
payments were made to the same likely fraudsters. Then, SBA OIG matched the DOL 
OIG dataset with the third dataset it had created and found a total of over $2.25 billion in 
 
 
 
10 To date, SBA OIG has issued six reports on potential COVID-19 EIDL fraud. Those reports are 
available at the following hyperlinks: Report No. 20-16, July 28, 2020; Report No. 21-02, 
October 28, 2020; Report No. 21-15, May 6, 2021; Report No. 22-06, November 30, 2021;  
Report No. 22-17, September 12, 2022; and Report No. 22-22, September 29, 2022. 
11 SBA OIG, Report No. 23-09 (June 2023) 

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potentially fraudulent EIDL disbursements. Of that $2.25 billion, SBA OIG found nearly 
$1.4 billion that neither it nor SBA had previously identified as potential fraud (newly 
identified potential fraud). 
 
As both OIGs have individually reported, the unprecedented infusion of federal funds 
into the UI and disaster assistance programs incentivized individuals and organized 
criminal groups with a high-value target to exploit. In addition, program weaknesses 
and the sheer volume of applications during the COVID-19 pandemic allowed criminals 
to defraud the programs. Because people may be both employed and separately 
operating a small business—and therefore potentially eligible for relief under both 
the UI and EIDL programs—receiving benefits under one of these two programs 
does not necessarily mean that involvement in the other program is potentially 
fraudulent. 
 
The data sharing and matching performed by DOL OIG and SBA OIG demonstrates 
a best practice for a collaborative method to mitigate fraud. During the COVID-19 
pandemic, no data sharing mechanism existed between ETA and SBA. If a data sharing 
mechanism had been in place, the agencies could have conducted a higher level of 
review by matching applicants across both programs to mitigate fraudulent payments 
through additional verification controls. The implications of the same likely fraudsters 
impacting more than one agency extends beyond significant monetary losses. 
Unmitigated fraudulent activity may affect expeditious, efficient deployment of 
assistance to eligible recipients and also decrease public trust in the government’s 
ability to safeguard taxpayer funds while effectively administering assistance. 
 
Data Matching Finds Same Likely Fraudsters Paid Under Both the UI and EIDL 
Programs 
 
As of September 2023, DOL OIG’s auditors, investigators, and data scientists had 
collaboratively identified $46.9 billion in potential UI fraud paid in six specific high-risk 
areas. For this joint project, DOL OIG performed data matching between the two 
datasets. DOL OIG found: 
 
• 3,850 EIDLs associated with suspicious emails were used to receive over 
$163 million in UI benefit payments and over $224 million in EIDL disbursements, 
totaling over $387 million; and 
 
• 11,901 multistate claimants obtained over $409 million in UI benefit payments 
and over $523 million in EIDL disbursements, totaling over $933 million. 
 
In total, DOL OIG found that the same claims that received over $573 million in 
potentially fraudulent UI benefit payments also received over $747 million in potentially 
fraudulent EIDL disbursements, resulting in significant potential fraud amounting to 
more than $1.3 billion (see Table 1). 
 
 

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Table 1: DOL OIG Data Matching Results 
UI Fraud Indicator 
How Many 
EIDLs 
Matched UI 
Fraud 
Indicator? 
Potential 
Fraud, UI 
Benefit 
Payments 
Potential 
Fraud, EIDL 
Disbursements 
Potential 
Fraud, 
Totals 
Suspicious emails 
3,850 
$163,652,583 
$224,330,400 
$387,982,983 
Multistate claimants 
11,901 
$409,933,026 
$523,168,586 
$933,101,612 
Totals 
15,751 
$573,585,609 
$747,498,986 
$1,321,084,595 
Source: EIDL dataset received on July 14, 2023, and matched to UI dataset on August 9, 2023 
 
SBA OIG took a slightly different approach to its data matching. It created a third 
dataset containing the COVID-19 EIDLs disbursed after DOL OIG had issued its 
February 2021, June 2021, and September 2022 alert memoranda. It then matched that 
third dataset with the DOL OIG dataset to identify if data sharing would have mitigated 
potential fraud from occurring. SBA OIG found: 
 
• 1,124 EIDLs that SBA had already flagged with hold codes, totaling nearly 
$178 million;12 
 
• 6,164 EIDLs that were identified as part of SBA OIG’s Fraud Landscape white 
paper, totaling nearly $690 million; and 
 
• 10,971 in newly identified potentially fraudulent EIDLs, totaling nearly $1.4 billion. 
 
In total, SBA OIG found that the information from the same individuals who received 
over $2.25 billion in COVID-19 EIDL disbursements matched DOL OIG-identified 
potential fraudsters (see Table 2). 
 
Table 2: SBA OIG Data Matching Results 
Identified Fraud 
EIDLs with 
Potentially 
Fraudulent 
Disbursements 
Potentially 
Fraudulent EIDL 
Disbursements 
Suspected/confirmed fraud hold codes 
1,124 
$177,932,998 
Captured within the Fraud Landscape white 
paper 
6,164 
$689,899,605 
Newly identified potential fraud 
10,971 
$1,382,855,478 
Totals 
18,259 
$2,250,688,081 
Source: SBA OIG analysis of UI data received on July 14, 2023, and EIDL data as of August 9, 2023 
 
12 The $178 million identified here is a subset of the $747 million identified by DOL OIG’s comparative 
analysis. 

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Best Practices for Data Sharing within the Federal Government 
 
While agencies are not mandated to share data or conduct data matching, examples 
exist of how these tools can help mitigate fraud. In a 2023 fraud alert, the Pandemic 
Response Accountability Committee (PRAC), utilizing SBA and Social Security 
Administration program data, identified $5.4 billion in disbursed potentially fraudulent 
pandemic relief funds linked to questionable SSNs.13 Also, in 2023, a GAO report called 
on federal agencies to improve fraud risk management efforts.14 The report identified 
the use of data analytics as one of five key areas for improvement to manage fraud risk, 
namely data matching as a tool to enable agencies to identify, prevent, and respond to 
fraud. 
 
Both reports demonstrate data matching as a tool to identify fraud, waste, abuse, 
and mismanagement. This is in large part due to data sharing improving identity 
verification by: (1) providing more complete applicant data, (2) enhancing existing 
controls by addressing potentially incomplete or missing information, and (3) helping 
in the development of new controls to identify risks that might have otherwise gone 
unnoticed without the additional shared data. Importantly, best practices for data 
sharing require sharing program-critical data elements such as bank account 
numbers, phone numbers, physical addresses, email addresses, and Internet 
Protocol addresses. 
 
The authority15 under which DOL OIG and SBA OIG conducted this effort is different 
than what would be required for ETA and SBA to share data. The Privacy Act of 1974, 
as amended by the Computer Matching and Privacy Protection Act of 1988, provides 
that agencies may enter into data sharing agreements to perform data matching to 
establish or verify eligibility for a federal benefit program. However, the agencies need 
to comply with the Privacy Act’s requirements16 to enter into a written data sharing 
agreement prior to engaging in any data matching. Critical to this process is determining 
what data may be shared per the routine uses of data authorized by the current System 
of Records Notice (SORN). If need be, the agencies may modify their current SORNs to 
allow for the exchange of program-critical data elements needed to match applicants 
across both programs to identify potential fraudsters for a higher level of review to 
mitigate fraudulent payments. 
 
 
 
13 PRAC, Fraud Alert: PRAC Identifies $5.4 Billion in Potentially Fraudulent Pandemic Loans Obtained 
Using over 69,000 Questionable Social Security Numbers, Report No. PRAC-2023-02 (January 2023), 
https://www.oversight.gov/reports/other/fraud-alert-prac-identifies-54-billion-potentially-fraudulent-
pandemic-loans-obtained 
14 GAO, Report to Congressional Committees: Fraud Risk, Management, Key Areas for Federal Agencies 
and Congressional Action, Report No. GAO-23-106567 (April 2023), https://www.gao.gov/assets/gao-23-
106567.pdf 
15 Authority of Inspector General, 5 U.S.C. § 406(j)(2) 
16 Privacy Act of 1974, 5 U.S.C. § 552a(a)(8); (o) 

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In addition, both DOL and SBA have experience with sharing and matching data. For 
example, DOL partners with the U.S. Department of Health and Human Services so that 
state workforce agencies (SWA)17 can compare information on individuals receiving UI 
benefits with data from the National Directory of New Hires. Similarly, an information 
exchange agreement between DOL and the Social Security Administration enables 
SWAs to compare data on individuals receiving Social Security benefits with those 
applying for or receiving UI benefits. SBA’s experience with sharing and matching 
data includes its collaboration with the U.S Department of the Treasury, comparing 
applicants for small business loans with the Do Not Pay list.18 SBA also collaborates 
with the Federal Emergency Management Agency (FEMA) to ensure individuals who 
receive disaster program loans do not receive duplicate benefits under FEMA’s 
Individuals and Households Program,19 in turn allowing FEMA to perform the same 
check. 
 
Sharing program-critical data can provide valuable information for various agency 
purposes, including achieving specific program goals, identifying patterns of unusual 
activity, and making correlations and informed decisions. Additionally, data sharing can 
help government agencies prioritize efforts, identify improvements, promote best 
practices, and aid public trust in government operations. 
 
CONCLUSION 
 
This collaborative effort—made possible by a data use agreement—allowed DOL OIG 
to identify $1.3 billion paid to the same potential fraudsters under both the UI and 
EIDL programs. Additionally, matching to a larger dataset, SBA OIG identified over 
$2.25 billion in potentially fraudulent EIDLs disbursed, including nearly $1.4 billion in 
newly identified, potentially fraudulent COVID-19 EIDL disbursements that may not 
have been otherwise identified. These findings highlight a significant opportunity for 
ETA and SBA to use data analytics to collaboratively develop additional controls for 
detecting and mitigating fraud. Through the sharing and matching of key data, ETA and 
SBA could detect potentially fraudulent activities before disbursing federal funds to 
ineligible individuals, thus more effectively safeguarding taxpayer dollars and ensuring 
program integrity. 
 
RECOMMENDATIONS 
 
To facilitate improved fraud controls, we recommend the following for each agency. 
 
 
 
17 SWA refers to the body that administers the UI program within a state, district, or territory. 
18 The Do Not Pay list is a service that agencies can use at no cost to check many data sources at one 
time to verify a recipient's eligibility for payment. 
19 FEMA’s Individuals and Households Program provides financial and direct services to eligible 
individuals and households affected by a disaster who have uninsured or under-insured necessary 
expenses and serious needs. 

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For ETA, DOL OIG recommends the Assistant Secretary for Employment and Training 
to: 
 
1. Evaluate its authority to share data and develop fraud prevention resources and 
controls with other federal entities, including SBA, that include data sharing 
mechanisms to detect and mitigate fraud. 
2. Collaborate with SBA to conduct a joint study to assess and identify the UI claim 
data elements that should be shared for data matching with disaster program 
data elements for the purpose of detecting potentially fraudulent activities under 
both the UI and SBA disaster assistance programs. 
 
For SBA, SBA OIG recommends the Administrator direct the Associate Administrator for 
OCA to: 
 
1. Evaluate its authority to share data and develop fraud prevention resources and 
controls with other federal entities, including DOL, that include data sharing 
mechanisms to detect and mitigate fraud. 
2. Collaborate with DOL to conduct a joint study to assess and identify disaster 
program data elements that should be shared for data matching with UI claim 
data elements for the purpose of detecting potentially fraudulent activities under 
both the UI and SBA disaster assistance programs. 
3. Reevaluate eligibility for the 10,971 potentially fraudulent EIDLs and recover 
funds from ineligible recipients. 
 
ANALYSIS OF AGENCY RESPONSES 
 
The full agency responses are contained in Appendices C and D, respectively.  
 
DOL OIG Analysis of Agency Response 
 
In its September 26, 2024, response to a draft of this report, ETA responded directly to 
our two recommendations to facilitate improved fraud controls via collaboration. ETA 
stated it agreed with Recommendation 1 and disagreed with Recommendation 2.  
 
The agency also included information on five areas of its program and operations, 
such as its access to the states’ UI claims data and the challenges posed by limited 
resources. Regarding those five areas, we addressed agency comments on two areas 
within our response to the recommendations and separately synopsized agency 
comments in two other areas and provided our corresponding responses. In relation to 
the fifth and last area of additional agency comment, we appreciate that ETA is aligning 
its risk management efforts with the GAO’s Fraud Risk Framework.  
 
We reviewed ETA’s response in full and did not make any changes to our report. Our 
synopsis of agency comments and our corresponding analyses follow. 

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Recommendation 1 
 
Evaluate its authority to share data and develop fraud prevention resources and 
controls with other federal entities, including SBA, that include data sharing 
mechanisms to detect and mitigate fraud. 
 
Status: Unresolved 
 
ETA stated it agreed with the recommendation and has already taken such action 
through the development of a fraud risk profile. Based on this action, ETA stated it: 
(1) identified and implemented data sharing mechanisms with other federal entities, 
most recently including the Social Security Administration and the U.S. Department of 
the Treasury, to mitigate the highest residual risks within the UI program; (2) discussed 
the recommendation with SBA; and (3) determined additional action is not warranted 
at this time, given other priorities for the UI program and the level of complexity and 
effort required to share data. ETA asserted SBA would have to enter into data 
sharing agreements with the individual SWAs, an assertion we address under 
Recommendation 2. ETA also noted it continues to streamline access to important 
payment integrity data sources through NASWA’s Integrity Data Hub and that all 
53 SWAs have entered into data sharing agreements with the data hub. 
 
We commend ETA for the actions it has taken to detect and mitigate fraud within the UI 
program, including evaluating risk. However, during our collaborative efforts with SBA 
OIG, a data use agreement and subsequent data sharing and analysis facilitated our 
identification of $1.3 billion in pandemic-related UI and EIDL payments made to the 
same likely fraudsters. We therefore strongly encourage ETA to leverage its authority to 
establish data sharing mechanisms in collaboration with SBA. By implementing these 
mechanisms with SBA, ETA could not only strengthen its fraud controls but also 
achieve proactive and tangible benefits, such as preventing significant losses of 
program funds to fraud. 
 
DOL OIG does not agree the actions ETA described meet the full intent of the 
recommendation. As such, this recommendation remains unresolved and we will 
reassess the status upon receipt of ETA’s corrective action plan. 
 
Recommendation 2 
 
Collaborate with SBA to conduct a joint study to assess and identify the UI claim data 
elements that should be shared for data matching with disaster program data elements 
for the purpose of detecting potentially fraudulent activities under both the UI and SBA 
disaster assistance programs. 
 
Status: Unresolved 
 
 

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ETA disagreed with the recommendation, stating it has limited resources and must 
prioritize its areas of focus. The agency also stated: (1) the report did not demonstrate 
how investing in the study would improve fraud prevention and detection efforts in a 
cost-effective manner beyond its existing practices and resources and (2) ongoing data 
sharing would require data sharing agreements between SBA and 53 SWAs. ETA 
asked that, instead of the recommendation for a proposed study, the OIG help it 
navigate a government-wide resolution that provides for interagency collaboration. It 
specified that such help would be both appreciated and more cost effective. ETA also 
proposed an alternative approach: it committed to meeting with SBA to further explore 
the possibility of using SBA data to improve UI program integrity. 
 
DOL OIG does not agree the actions described meet the intent of our recommendation. 
We commend ETA's willingness to engage with SBA to explore collaboration. We also 
understand conducting a study might be uneconomical for ETA. We are also open 
to alternative, less costly suggestions. The report demonstrates investment in 
collaboration between ETA and SBA could specifically identify key data elements 
to help detect potentially fraudulent activities within both programs. When subject 
matter experts discuss data and other information, patterns tend to become clear and 
emerging trends can be identified. For example, as noted in our report, DOL OIG and 
SBA OIG uncovered $1.3 billion in newly identified potential fraud through a similar 
process. Identifying key data elements would assist the agencies in preparing to combat 
fraud during future national disasters. Both agencies possess in-depth knowledge of 
their respective programs and can work together to identify overlapping areas that may 
be vulnerable to fraud.  
 
Also, regarding ETA’s statement on data sharing agreements between SBA and the 
SWAs, we remind ETA of the need for corrective action on a recommendation issued in 
our September 2023 alert memorandum.20 We recommended the Principal Deputy 
Assistant Secretary of Employment and Training obtain direct access to UI claims 
data from all SWAs. ETA access to UI claims data through such a centralized 
system could be the foundation to facilitate data sharing efforts with SBA. Ultimately, 
whether this collaboration is formalized through a data sharing agreement of ETA and 
SBA’s own design or facilitated via the U.S. Department of the Treasury’s Do Not Pay 
system, the OIG looks forward to ETA and SBA exploring alternatives to improve 
collaboration. 
 
DOL OIG does not agree the actions ETA described meet the full intent of the 
recommendation. As such, this recommendation remains unresolved and we will 
reassess the status upon receipt of ETA’s corrective action plan. 
 
 
 
20 DOL OIG, Report No. 19-23-012-03-315 (September 25, 2023) – Recommendation 1 

Data Sharing Project Finds Billions Paid to Same Likely Fraudsters 
– 11 – 
DOL OIG Report No. 19-25-001-03-315 
SBA OIG Report No. 25-06 
Other Management Comments 
 
UI Data Owned by SWAs and Disclosure Governed Under State Laws 
 
ETA noted UI data is owned by SWAs and its disclosure is governed under state laws. 
The agency stated it generally does not have access to individual-level SWA UI data. 
ETA also expressed concerns regarding the lack of a SORN that could be modified to 
facilitate the exchange of individual-level SWA UI claims data for data matching 
purposes. ETA stated each of the 53 SWAs would need to establish individual 
state-level data sharing agreements with SBA to enable data matching. 
 
DOL OIG is aware that SWAs own UI data. However, the OIG has previously expressed 
in more than one report to ETA that its authority under the Social Security Act and 
20 C.F.R. Part 603 allows ETA to access and collect SWA UI data. Additionally, the OIG 
identified a SORN that ETA published on the DOL website, which is currently under 
development and is designed specifically to allow for the ease of data matching. This 
draft SORN includes a section titled, “Authority for Maintenance of the System,” which 
references federal laws that allow ETA to collect individual state-level UI data.21 These 
laws grant ETA the authority to access UI data. Furthermore, one of the procedures 
outlined in the SORN allows for the disclosure of UI claims data to another federal 
agency or entity when DOL determines the information is necessary to address a 
suspected or confirmed breach or to prevent, minimize, or remedy the risk of harm to 
individuals, the agency’s operations, a recipient agency’s operations, the federal 
government, or national security resulting from a suspected or confirmed breach. 
DOL OIG sees potential fraud as potential harm, given the risk of impact to individuals’ 
livelihoods that fraud poses. 
 
Expiration of Pandemic Programs 
 
ETA noted the OIG’s analysis was based on an expired pandemic program, using data 
from an SBA program that ended in January 2022. ETA also reiterated its commitment 
to improving eligibility determination and reducing improper payments through data 
sharing initiatives. However, it stated it will not allocate limited resources to pursuing a 
data sharing partnership based on analysis from an expired program. 
 
While DOL OIG and SBA OIG used pandemic UI data for this report, ongoing issues 
within the UI program persist. DOL OIG work has demonstrated criminals continue to 
focus on the program since the pandemic, adapting their tactics to exploit systemic 
weaknesses. UI and disaster loan programs have been enacted to combat other 
disasters throughout the country, and the OIG expects this will continue to be 
necessary. Although the COVID-19 pandemic-related programs have expired, ongoing 
cooperation with SBA would be instrumental in preventing fraudulent payments in future 
crises of a similar scale or the next pandemic. 
 
 
 
21 Specifically, this includes Title III of the Social Security Act (42 U.S.C. 501-503) and 20 C.F.R. Part 603. 

Data Sharing Project Finds Billions Paid to Same Likely Fraudsters 
– 12 – 
DOL OIG Report No. 19-25-001-03-315 
SBA OIG Report No. 25-06 
SBA OIG Analysis of Agency Response 
 
The following section summarizes the status of our recommendations and the actions 
necessary to close them. 
 
Recommendation 1 
 
Evaluate its authority to share data and develop fraud prevention resources and 
controls with other federal entities, including DOL, that include data sharing 
mechanisms to detect and mitigate fraud. 
 
Status: Resolved 
 
Management agreed with the recommendation, stating that they will approach this not 
with DOL directly but as a collaborative, “whole of government” approach. SBA will 
collaborate with appropriate centralized federal entities to evaluate authorities to share 
data and will conduct a joint study with centralized entities to assess and identify 
program data elements that should be shared for the purpose of detecting potentially 
fraudulent activities. SBA discussed this approach with DOL and determined that it 
would be more beneficial to address this recommendation on a broader scale. 
 
SBA plans to implement this recommendation by September 25, 2026. 
 
The recommendation will be closed upon completion of the joint study resulting in a 
determination of what data elements should be shared. 
 
Recommendation 2 
 
Collaborate with DOL to conduct a joint study to assess and identify disaster program 
data elements that should be shared for data matching with UI claim data elements for 
the purpose of detecting potentially fraudulent activities under both the UI and SBA 
disaster assistance programs. 
 
Status: Resolved 
 
Management agreed with the recommendation, stating that they will approach this 
not with DOL directly but as a collaborative, “whole of government” approach with 
appropriate centralized federal entities to evaluate authorities to share data and 
develop centralized fraud prevention resources and controls that include data sharing 
mechanisms to detect and mitigate fraud occurring in federal programs across the 
entire federal space. SBA discussed this approach with DOL and determined that it 
would be more beneficial to address this recommendation on a broader scale. 
 
SBA plans to implement this recommendation by September 24, 2027. 
 
 

Data Sharing Project Finds Billions Paid to Same Likely Fraudsters 
– 13 –
DOL OIG Report No. 19-25-001-03-315 
SBA OIG Report No. 25-06 
The recommendation will be closed upon implementation of data sharing mechanisms 
to detect and mitigate fraud. 
Recommendation 3 
Reevaluate eligibility for the 10,971 potentially fraudulent EIDLs and recover funds from 
ineligible recipients. 
Status: Resolved 
Management agreed with the recommendation, stating that, once OIG provides SBA the 
additional DOL criteria regarding the identified population, SBA will perform a high-level 
review of a sample of the identified loans. 
SBA plans to implement this recommendation by September 26, 2025. 
The recommendation will be closed upon completion of eligibility reviews for an 
agreed upon size of sample loans for potential fraud and possible recovery of funds. 
Both OIGs appreciate the cooperation and courtesies ETA and OCA extended to us 
during this audit. Staff from both OIGs who contributed to this report are listed in 
Appendix E. 
Larry D. Turner 
Inspector General 
U.S. Department of Labor 
Hannibal “Mike” Ware 
Inspector General 
U.S. Small Business Administration 

Data Sharing Project Finds Billions Paid to Same Likely Fraudsters 
– 14 – 
DOL OIG Report No. 19-25-001-03-315 
SBA OIG Report No. 25-06 
For any agency questions, please contact the following staff directly: 
 
DOL OIG 
 
Michael Kostrzewa, Audit Director 
(972) 850-4003 
 
Carolyn R. Hantz, Assistant Inspector General for Audit 
(202) 693-5170 
 
SBA OIG 
 
John Provan, Director of Disaster Assistance Programs Group 
(817) 688-9780 
 
Andrea Deadwyler, Assistant Inspector General for Audits 
(202) 205-6586 
 

 
– A-1 – 
DOL OIG Report No. 19-25-001-03-315 
SBA OIG Report No. 25-06 
Appendix A: Scope and Methodology 
 
The OIGs for DOL and for SBA engaged in a joint project to determine if data sharing 
between ETA and SBA could mitigate the risk of fraudulent UI benefit payments and 
SBA disaster assistance program disbursements.  
 
We reviewed federal laws, regulations, policies, procedures, and internal 
memorandums pertaining to DOL’s UI program and SBA’s COVID-19 EIDL program. 
We also met with officials from ETA and OCA to discuss consideration be given to data 
sharing and the extent to which they work with other agencies. 
 
DOL OIG conducted a comparative analysis to determine whether key data elements 
linked to potentially fraudulent UI benefit payments matched the corresponding data 
elements related to potentially fraudulent EIDL disbursements. Specifically, DOL OIG 
compared its dataset (the dataset of UI claims field with SSNs associated with 
multistate claims and with suspicious email accounts) with the corresponding dataset 
associated with COVID-19 EIDL disbursements that SBA OIG had identified and 
flagged with hold codes.  
 
SBA OIG created a third dataset of all COVID-19 EIDLs disbursed after DOL OIG had 
issued its first three alert memoranda. SBA OIG then performed a comparative analysis 
between that third dataset and DOL OIG’s dataset. SBA OIG matched recipients based 
on common identifier fields such as suspicious email accounts, SSNs, addresses, and 
phone numbers. SBA OIG analyzed whether data sharing would have benefited SBA. 
SBA OIG also compared the dates of the alert memoranda issued by DOL OIG to the 
disbursement dates of COVID-19 EIDLs to identify potential fraud. 
 
This report was prepared in alignment with OIG quality control standards and the 
Council of the Inspectors General on Integrity and Efficiency’s Quality Standards for 
Inspection and Evaluation, which requires that we plan and perform the review to obtain 
sufficient and appropriate evidence to provide a reasonable basis for our conclusions 
and observations based on our objective. We believe the evidence obtained provides a 
reasonable basis for our conclusions and observations based on our objectives. 
 

 
– B-1 – 
DOL OIG Report No. 19-25-001-03-315 
SBA OIG Report No. 25-06 
Appendix B: Prior Relevant Coverage 
 
Since March 2020, both DOL OIG and SBA OIG have issued several reports of 
significant relevance to this report. Those reports include the following: 
 
DOL OIG 
 
Semiannual Report to Congress (issued each spring and fall), Vols. 83-90 (2020-2023), 
https://www.oig.dol.gov/semiannual.htm 
 
U.S. Department of Labor Top Management Challenges (issued each fall), 2020-2023, 
https://www.oig.dol.gov/topchallenges.htm 
 
Alert Memorandum: ETA Needs to Incorporate Data Analytics Capability to Improve 
Oversight of the Unemployment Insurance Program,  
Report No. 19-23-012-03-315 (September 25, 2023), 
https://www.oig.dol.gov/public/reports/oa/2023/19-23-012-03-315.pdf 
 
Alert Memorandum: Potentially Fraudulent Unemployment Insurance Payments in 
High-Risk Areas Increased to $45.6 Billion,  
Report No. 19-22-005-03-315 (September 21, 2022), 
https://www.oig.dol.gov/public/reports/oa/2022/19-22-005-03-315.pdf 
 
Alert Memorandum: The Employment and Training Administration Needs to Issue 
Guidance to Ensure State Workforce Agencies Provide Requested Unemployment 
Insurance Data to the Office of Inspector General,  
Report No. 19-21-005-03-315 (June 16, 2021), 
https://www.oig.dol.gov/public/reports/oa/2021/19-21-005-03-315.pdf 
 
Alert Memorandum: The Employment and Training Administration (ETA) Needs to 
Ensure State Workforce Agencies (SWA) Implement Effective Unemployment Insurance 
Program Fraud Controls for High-Risk Areas,  
Report No. 19-21-002-03-315, (February 22, 2021), 
https://www.oig.dol.gov/public/reports/oa/2021/19-21-002-03-315.pdf  
 
Advisory Report: CARES Act: Initial Areas of Concern Regarding Implementation of 
Unemployment Insurance Provisions, 
Report No. 19-20-001-03-315, (April 21, 2020), 
https://www.oig.dol.gov/public/reports/oa/2020/19-20-001-03-315.pdf 
 
 

Data Sharing Project Finds Billions Paid to Same Likely Fraudsters 
– B-2 – 
DOL OIG Report No. 19-25-001-03-315 
SBA OIG Report No. 25-06 
SBA OIG 
 
COVID-19 Pandemic EIDL and PPP Loan Fraud Landscape, 
Report No. 23-09 (June 27, 2023), 
https://www.sba.gov/document/report-23-09-covid-19-pandemic-eidl-ppp-loan-fraud-
landscape 
 
Follow-up Inspection of SBA’s Internal Controls to Prevent COVID-19 EIDLs to Ineligible 
Applicants, 
Report No. 22-22 (September 19, 2022),  
https://www.sba.gov/document/report-22-22-follow-inspection-sbas-internal-controls-
prevent-covid-19-eidls-ineligible-applicants 
 
COVID-19 Economic Injury Disaster Loan Applications Submitted from Foreign IP 
Addresses, 
Report No. 22-17 (September 12, 2022),  
https://www.sba.gov/document/report-22-17-covid-19-economic-injury-disaster-loan-
applications-submitted-foreign-ip-addresses 
 
COVID-19 EIDL Program Recipients on the Department of Treasury's Do Not Pay List, 
Report No. 22-06 (November 30, 2021),  
https://www.sba.gov/document/report-22-06-covid-19-eidl-program-recipients-
department-treasurys-do-not-pay-list 
 
SBA’s Handling of Identity Theft in the COVID-19 Economic Injury Disaster Loan 
Program, 
Report No. 21-15 (May 6, 2021),  
https://www.sba.gov/document/report-21-15-sbas-handling-identity-theft-covid-19-
economic-injury-disaster-loan-program 
 
Inspection of Small Business Administration’s Initial Disaster Assistance Response to 
the Coronavirus Pandemic, 
Report No. 21-02 (October 28, 2020),  
https://www.sba.gov/document/report-21-02-inspection-small-business-administrations-
initial-disaster-assistance-response-coronavirus-pandemic 
 
Management Alert: Serious Concerns of Potential Fraud in Economic Injury Disaster 
Loan Program Pertaining to the Response to COVID-19,  
Report No. 20-16 (July 28, 2020), 
https://www.sba.gov/document/report-20-16-serious-concerns-potential-fraud-eidl-
program-pertaining-response-covid-19

 
– C-1 – 
DOL OIG Report No. 19-25-001-03-315 
SBA OIG Report No. 25-06 
Appendix C: 
U.S. Department of Labor Response 
 
U.S. Department of Labor 
Response to Draft Report 
 
 
 
The agency’s response to our draft report follows. 
 

U.S. Department of Labor    
Assistant Secretary for  
  Employment and Training 
   Washington, D.C.  20210
FROM: 
JOSÉ JAVIER RODRÍGUEZ 
SUBJECT: 
Response to Draft Joint Report – COVID-19:  Data 
Sharing Project Finds Billions Paid to Same Likely 
Fraudsters Under Both the Unemployment Insurance and 
Economic Injury Disaster Loan Programs, Report No.    
19-24-XXX-03-315
The U.S. Department of Labor's (Department) Employment and Training Administration (ETA) 
appreciates the opportunity to respond to the above-referenced draft joint report from the 
Department’s Office of Inspector General (OIG) and the U.S. Small Business Administration 
(SBA) OIG.  Below are some points the Department would like to share related to the themes 
discussed in the draft joint report, followed by the Department’s responses to the OIG’s 
recommendations. 
ETA is actively demonstrating its commitment to align existing risk management efforts with 
the Government Accountability Office’s (GAO) Fraud Risk Framework.  The Department 
takes its oversight of federally funded programs very seriously.  Strengthening Unemployment 
Insurance (UI) program integrity, by reducing improper payments and mitigating fraud risks, 
remains a top priority for the Department.  In recent years, the Department implemented 
recommendations made by the GAO to help improve UI fraud risk management, which includes 
aligning existing risk management efforts with the leading practices in GAO’s Fraud Risk 
Framework1
0F .   
GAO’s recommendations spurred the Department to develop a UI Fraud Risk Profile, 
supplementing and enhancing its robust payment integrity efforts, and further strengthening an 
organizational culture that views the creation, evaluation, monitoring, and evolution of risk 
mitigation strategies as an ongoing process.  ETA also announced the release of a new UI Fraud 
Risk Management webpage for state workforce agencies (SWA) to access information on the 
Department’s UI fraud risk management activities and to update states on new fraud risk 
mitigation strategies and initiatives.2
1F   GAO’s leading practices are now well embedded in the 
daily UI program integrity work.  The Department also agrees wholeheartedly with GAO that 
data analytics activities are a critical component of an overall antifraud strategy.   
1 GAO, A Framework for Managing Fraud Risks in Federal Programs, GAO-15-593SP, issued July 2015, 
https://www.gao.gov/assets/gao-15-593sp.pdf.  
2 See Training and Employment Notice (TEN) No. 32-23, Unemployment Insurance (UI) Fraud Risk Management 
Resources, issued June 27, 2024, https://www.dol.gov/agencies/eta/advisories/ten-32-23.   
September 26, 2024
MEMORANDUM FOR: 
CAROLYN R. HANTZ  
Assistant Inspector General for Audit 

2 
 
UI data is owned by SWAs and its disclosure is governed under state laws.  The OIG notes in 
their draft report that UI is “administered jointly by the federal and state governments.”  To 
clarify, the UI program is a federal-state partnership program based upon federal law and 
administered by state workforce agencies (SWA) under state law.  UI data is owned by SWAs 
and its access and use are governed by state laws that conform with certain requirements set forth 
in federal regulation.2F3  The Department generally does not have access to individual-level SWA 
UI data and the draft joint report suggests that ETA modify its current System of Record Notices 
(SORN) to accommodate the envisioned data exchange.  However, as ETA indicated in 
discussions with the OIG, ETA does not have a SORN that could be modified to allow for the 
exchange of this data, nor does ETA have the authority to perform the suggested data matching.  
Each of the 53 SWAs that operate UI programs would need to enter into individual, state-level 
data sharing agreements with the SBA to conduct the type of data sharing suggested in the draft 
joint report.   
 
ETA is actively demonstrating its commitment to strengthen data sharing with federal 
agencies.  As part of the UI antifraud strategy, the Department is committed to pursuing access 
to necessary external data sources, including data sharing with other federal agencies and third 
parties that can provide support to SWAs in identifying potential fraud and improper payments, 
and helping with accurate determinations of UI eligibility.   
 
These efforts include streamlining SWAs access to additional data sources through the National 
Association of State Workforce Agencies’ (NASWA) UI Integrity Data Hub (IDH), which is a 
key payment integrity tool to aid states in detecting and preventing UI fraud.  Recently, the 
Department announced a new data sharing partnership between the U.S. Department of 
Treasury’s (Treasury) Bureau of the Fiscal Service (Fiscal Service) and NASWA to provide 
SWAs with access to Do Not Pay data sources and services through the IDH.3F4  Additionally, the 
Department worked with the Social Security Administration (SSA) to establish a data sharing 
agreement to provide SWAs with streamlined access to SSA’s Prisoner Update Processing 
System data through NASWA’s UI Interstate Connection Network.4F5  Furthermore, the 
Department maintains a data sharing agreement with the U.S. Department of Health and Human 
Services’ Office of Child Support Services to provide states with access to the National 
Directory of New Hires data.5F6  All these data sharing partnerships provide SWAs with access to 
important data sources to help reduce fraud and/or confirm UI program eligibility.  Each of these 
 
3 See 20 C.F.R. Part 603. 
4 See TEN No. 28-23, Announcement of a New Data Sharing Partnership Between the U.S. Department of 
Treasury’s (Treasury) Bureau of the Fiscal Service (Fiscal Service) and the National Association of State Workforce 
Agencies’ (NASWA) Unemployment Insurance (UI) Integrity Center to provide State UI Agencies Access to Do Not 
Pay Working System (DNP) Data Sources and Services through the UI Integrity Data Hub (IDH), issued May 2, 
2024, https://www.dol.gov/agencies/eta/advisories/ten-28-23.   
5 See Unemployment Insurance Program Letter (UIPL) No. 01-22, Announcing the Availability of an Incarceration 
Data Exchange and Instructions to Access the Data Exchange between the Unemployment Insurance (UI) Interstate 
Connection Network (ICON) and the Social Security Administration (SSA) Prisoner Update Processing System 
(PUPS), issued October 29, 2021, https://www.dol.gov/agencies/eta/advisories/unemployment-insurance-program-
letter-no-01-22.   
6 See TEN No. 05-20, National Directory of New Hires (NDNH), State Directory of New Hires (SDNH), and Other 
Improper Payment Prevention and Detection Resources, Tools, and Services Available to States, issued September 
24, 2020, https://www.dol.gov/agencies/eta/advisories/training-and-employment-notice-no-05-20. 

3 
 
data sharing partnerships support risk mitigation efforts to address the highest UI risks identified 
in the Department’s UI Fraud Risk Profile.      
 
The draft joint report suggests that data sharing between ETA and SBA could mitigate the risk of 
fraudulent UI payments and SBA disbursements, based on the data matching conducted by the 
OIG.  Additionally, the draft joint report asserts that if data sharing and matching had existed, the 
agencies could have conducted a higher-level review by matching applicants across both 
programs to mitigate fraudulent payments.  However, while the Department is committed to 
seeking data sharing opportunities to address the highest UI program risks, ETA disagrees with 
the OIGs’ assessment regarding this data sharing partnership. 
 
The OIG’s analysis was based on an expired pandemic program.  The OIG’s analytics were 
based on cross-matching with data from an SBA program the OIGs jointly acknowledge ended in 
January 2022.  The Department reiterates its commitment to identifying and pursuing data 
sharing initiatives that could support more accurate eligibility determination and reduce improper 
payments but will not allocate limited resources to pursing a data sharing partnership based on 
analysis from an expired program.  
 
ETA has limited resources and must prioritize its areas of focus.  ETA has limited resources 
and relies on several factors, such as the priority level of the residual risk identified in the 
Department’s recently developed UI Fraud Risk Profile, insight from its oversight bodies such as 
GAO and the OIG, and other evidence to make decisions on how these resources are allocated.  
This includes analyzing the highest residual risks to the UI program after evaluating the impact 
of existing antifraud controls.   
 
The draft joint report identifies “$1.3 billion in potentially fraudulent UI and Economic Injury 
Disaster Loan (EIDL) payments made to the same likely fraudsters.”  This assessment is based 
on individuals with Social Security Numbers from two groups:  (1) those who filed in multiple 
states and (2) those using suspicious emails.  However, the draft joint report fails to acknowledge 
that:  (1) workers may be eligible to file in multiple states under certain conditions and (2) 
suspicious email addresses may be a flag, but the OIG does not define what they consider 
“suspicious” in this audit.  Both issues are potential flags of suspicion, but, not conditions certain 
of fraud.  The Supreme Court has found that payment must be made “when due” and may not be 
held merely on a program official or auditor’s suspicions.  Additionally, the draft joint report 
acknowledges that people may be potentially eligible for relief under both the UI and EIDL 
programs and receiving benefits under one of these two programs does not necessarily mean that 
involvement in the other program is potentially fraudulent.    
 
ETA has already identified these two groups as fraud risks to the UI program and developed 
and/or strengthened existing mitigation strategies to address both risks.  SWAs currently review 
claims for suspicious emails and multistate filings through different fraud detection tools, 
including the IDH.  The IDH was specifically designed to cross-match suspicious data elements 
being used across UI claims, including, but not limited to suspicious email addresses.  
Additionally, the IDH has a multi-state cross-matching (MSCM) functionality to flag UI claims 
filed in multiple states.  Matching UI data with SBA data would not help SWAs proactively 
identify UI claims filed across multiple states.   

4 
 
The Department has and continues to strongly encourage states to actively participate in the IDH 
on a regular basis, and IDH participation has increased significantly since the onset of the 
pandemic.  For example, in March of 2020, only 34 states had an IDH Participation Agreement 
(PA), 21 states were using the Suspicious Actor Repository (SAR), which provides information 
on suspicious UI claims data elements, including suspicious email addresses, and three states 
were using the MSCM, which was quite new at the time, having only been live in the IDH 
production environment since November 2019 – about five months.  ETA continues to support 
ongoing enhancements to the IDH by funding additional fraud prevention capabilities such as an 
identity verification (IDV) and risk scoring solution, which became available to states in July 
2020, as well as a Bank Account Verification (BAV) service, which became available to states in 
February 2022.  Currently, all 53 states have a signed IDH PA, 51 states are using the SAR, 51 
states are using the MSCM, 46 states are using the IDV solution, and 43 states are using the 
BAV service.  Furthermore, in the Department’s Fiscal Year 2025 President’s Budget and the UI 
Transformation Plan6F7, requiring the use of IDH is identified as a proposed legislative reform.   
 
Without additional funding from Congress, ETA must continue to prioritize its areas of focus. 
The draft joint report has not demonstrated additional value for ETA to further pursue the 
exchange of these data elements with SBA.   
 
Responses to the Recommendations 
 
Please find below each of the recommendations contained in the draft joint report, followed by 
ETA’s proposed corrective actions to address the recommendations. 
 
Recommendation 1:  Evaluate its authority to share data and develop fraud prevention 
resources and controls with other federal entities, including SBA, that include data sharing 
mechanisms to detect and mitigate fraud. 
 
ETA Response:  ETA agrees with this recommendation and asserts that it has already taken such 
action through the development of a UI Fraud Risk Profile that aligns with GAO’s Fraud Risk 
Framework.  Through the efforts of strengthening UI fraud risk management activities, building 
the UI Fraud Risk Profile, and analyzing the results, the Department has designed a risk response 
to identified risks.  As noted by GAO in their Framework for Managing Fraud Risks in Federal 
Programs, effective managers of fraud risks use the program’s fraud risk profile to help decide 
how to allocate resources to respond to residual fraud risks, which may include actions to accept, 
reduce, share, or avoid the risk.  Specifically, managers may allocate resources to prevent or 
detect fraud risks that exceed their risk tolerance, but they may decide not to allocate resources to 
further reduce unlikely, low-impact risks that fall within their risk tolerance.   
 
To mitigate the highest residual risks to the UI program, the Department has identified and 
implemented data sharing mechanisms with other federal entities - most recently including SSA 
and Treasury.  The Department continues to streamline access to important payment integrity 
data sources through the UI IDH since all 53 states have entered into agreements to share 
 
7 See Unemployment Insurance Transformation Plan, Building Resilience: A plan for transforming unemployment 
insurance, issued April 2024, https://oui.doleta.gov/unemploy/transformation_plan.asp.  

5 
 
individual claims-level data with the IDH for the purposes of ensuring the accuracy of payments 
and preventing fraud and improper payments. 
   
The Department has discussed this concept with SBA and determined that additional action is 
not warranted at this time, given other priorities for the UI program (such as expanding 
additional data sharing opportunities with Treasury) and the level of complexity and effort with 
existing authorities to share data, insofar as it would require SBA to enter into data sharing 
agreements with each individual state.   
 
Recommendation 2:  Collaborate with SBA to conduct a joint study to assess and identify 
the UI claim data elements that should be shared for data matching with disaster program 
data elements for the purpose of detecting potentially fraudulent activities under both the 
UI and disaster assistance programs. 
 
ETA Response:  ETA disagrees with this recommendation, given that ETA has limited resources 
and must prioritize its areas of focus.  This draft joint report has not demonstrated how investing 
in an additional study specific to the UI and EIDL programs will improve fraud prevention and 
detection efforts in the UI program cost-effectively beyond existing practices and resources.  
Additionally, ongoing data sharing between the UI program and SBA will require SBA to enter 
into data sharing agreements with each of the 53 SWAs administering UI programs.   
 
Instead of requesting ETA to invest in an additional study of two programs with eligibility 
criteria that are not mutually exclusive, ETA asks the OIG for help in navigating a government-
wide resolution that provides for interagency collaboration.  This type of data matching may be 
helpful to law enforcement when prosecuting cases involving fraud across multiple programs.  
The OIG’s leadership on a broad-based interagency effort would be appreciated and be more 
cost-effective than a limited scope study based on expired programs.  
 
As an alternative approach, ETA is committed to meeting with SBA to further explore the 
possibility of using SBA data to support UI program integrity.  This activity will include 
determining if there is an appropriate return on investment for both the UI program and SBA 
and/or engaging with our partners in Treasury’s Fiscal Service to assess the possibility of 
streamlining SWAs’ access to SBA data sources through the Do Not Pay system.  ETA, working 
in collaboration with the Department’s Chief Evaluation Office and the Department’s Office of 
the Chief Financial Officer, is responsible for this recommendation. 
 

 
– D-1 – 
DOL OIG Report No. 19-25-001-03-315 
SBA OIG Report No. 25-06 
Appendix D: 
U.S. Small Business Administration Response 
 
U.S. Small Business Administration 
Response to Draft Report 
 
 
The agency’s response to our draft report follows. 
 

U.S. SMALL BUSINESS ADMINISTRATION 
WASHINGTON, DC 20416 
To: 
Hannibal “Mike” Ware 
Inspector General 
U.S. Small Business Administration 
From:  
Jihoon Kim, Director, Office of Financial Program Operations, 
Office of Capital Access  
Date:  
September 23, 2024 
 
Subject: 
Response to OIG Draft Report – COVID-19: Data Sharing Project Finds Billions 
Paid to Same Likely Fraudsters Under Both the Unemployment Insurance and 
Economic Injury Disaster Loan Programs (Project 23801) 
Thank you for providing the Office of Capital Access (OCA) the opportunity to respond to 
OIG’s Draft Report entitled, “COVID-19: Data Sharing Project Finds Billions Paid to Same 
Likely Fraudsters Under Both the Unemployment Insurance and Economic Injury Disaster Loan 
Programs.” The OIG’s audit objective for this draft report was to determine if “data sharing 
between ETA and SBA mitigate the risk of fraudulent UI benefit payments and SBA disaster 
program disbursements.”  
We appreciate the role the Office of Inspector General (OIG) plays in working with management 
in ensuring that our programs are effectively managed, and for the feedback provided in this 
draft report. We offer the following response to the recommendations: 
Recommendation 1:  Evaluate its authority to share data and develop fraud prevention resources 
and controls with other federal entities, including DOL, that include data sharing mechanisms 
to detect and mitigate fraud.  
SBA Response:  
SBA agrees with this recommendation, however, will approach this not with DOL directly but as 
a collaborative, “whole of government” approach. SBA will collaborate with appropriate 
centralized federal entities to evaluate authorities to share data and will conduct a joint study 
with centralized entities to assess and identify program data elements that should be shared for 

the purpose of detecting potentially fraudulent activities. SBA has discussed this approach with 
DOL and determined that it would be more beneficial to address this recommendation on a 
broader scale.  
Recommendation 2:  Collaborate with DOL to conduct a joint study to assess and identify the 
UI claim data elements that should be shared for data matching with disaster program data 
elements for the purpose of detecting potentially fraudulent activities under both the UI and 
disaster assistance programs.  
SBA Response:  
SBA agrees with this recommendation, however, will approach this not with DOL directly but as 
a collaborative, “whole of government” approach with appropriate centralized federal entities to 
evaluate authorities to share data and develop centralized fraud prevention resources and controls 
that include data sharing mechanisms to detect and mitigate fraud occurring in federal programs 
across the entire federal space.  SBA has discussed this approach with DOL and determined that 
it would be more beneficial to address this recommendation on a broader scale.   
Recommendation 3: Reevaluate eligibility for the 10,971 potentially fraudulent EIDLs and 
recover funds from ineligible recipients.     
SBA Response:  
SBA agrees. Once OIG provides SBA the additional DOL criteria regarding the identified 
population, SBA will perform a high-level review of a sample of the identified loans.  

 
– E-1 – 
DOL OIG Report No. 19-25-001-03-315 
SBA OIG Report No. 25-06 
Appendix E: Acknowledgments 
 
Staff who contributed to this report follow. 
 
DOL OIG 
 
Michael Kostrzewa 
Audit Director 
 
Lawrence Alli 
Audit Manager 
 
Charmane Miller 
Auditor-in-Charge 
 
Reed Rubey 
Senior Auditor 
 
Daphne Jones 
Senior Auditor 
 
Le Nguyen 
Assistant Counsel 
 
Jon Heinz 
Assistant Counsel 
 
Dennis Asante 
Data Scientist 
 
Dr. LaKeisha L. Jones 
Statistician 
 
Carla Orvis Hunt 
Writer-Editor 
 
 
SBA OIG 
 
John Provan 
Audit Director 
 
Marvin Houle 
Audit Manager 
 
Mona D’Amore 
Auditor-in-Charge 
 
Courtney Schlieter 
Assistant Counsel 
 
Sam Bronson 
Data Analyst Team Lead 
 
Christopher McGraw 
Statistician 
 
Sharon Leffel 
Writer-Editor 

 
 
Make a Difference 
To report fraud, waste, or mismanagement, contact the U.S. Department of Labor’s 
Office of Inspector General: 
 
Online: https://www.oig.dol.gov/hotline.htm 
Telephone: (800) 347-3756 
Fax: (202) 693-7020 
 
or write to us at: 
 
Office of Inspector General, U.S. Department of Labor,  
200 Constitution Avenue NW, Room S-5506,  
Washington DC 20210 
 
To report fraud, waste, or mismanagement, contact the U.S. Small Business 
Administration’s Office of Inspector General: 
 
Online: https://www.sba.gov/oig/hotline 
Telephone: (800) 767-0385 
 
or write to us at: 
 
Office of Inspector General, U.S. Small Business Administration, 
409 Third Street, SW (5th Floor), 
Washington DC 20416

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