UIPL 22-21 Change 2.pdf

EMPLOYMENT AND TRAINING ADMINISTRATION

ADVISORY SYSTEM

U.S. DEPARTMENT OF LABOR

Washington, D.C. 20210

CLASSIFICATION

Unemployment Insurance

CORRESPONDENCE SYMBOL

OUI/DPM

DATE

April 27, 2023

RESCISSIONS

None

EXPIRATION DATE

Continuing

ADVISORY: UNEMPLOYMENT INSURANCE PROGRAM LETTER NO. 22-21,

Change 2

TO: STATE WORKFORCE AGENCIES

FROM: BRENT PARTON

Acting Assistant Secretary

SUBJECT: Additional American Rescue Plan Act (ARPA) Funding and Support for States to Strengthen Unemployment Insurance (UI) Program Integrity, including

Identity (ID) Verification, Fraud Prevention and Detection, and Overpayment

Recovery Efforts in All Unemployment Compensation (UC) Programs and

Required and Strongly Recommended Strategies, Tools, and Services for UI

Fraud Risk Mitigation and Improper Payment Reduction

1. Purpose. To provide states with information on both required and strongly recommended strategies, tools, and services for UI fraud risk mitigation, improper payment reduction, and overpayment recovery; and to announce the availability of up to $200 million in additional

ARPA funding and support for states to strengthen UI program integrity, including ID verification, fraud prevention and detection, and overpayment recovery efforts in all UC programs.

2. Action Requested. Submissions for the funding opportunities under this Unemployment

Insurance Program Letter (UIPL) are due by the close of business on July 26, 2023. The

U.S. Department of Labor’s (DOL or the Department) Employment and Training

Administration (ETA) requests that State Workforce Agency Administrators:

• Review the funding opportunity described in this UIPL to ensure appropriate staff is aware of the required and strongly recommended strategies, tools, and services for UI fraud risk mitigation and improper payment reduction; and to determine if the state will apply for these funds.

• Coordinate with appropriate state staff to develop a grant application that outlines how the state intends to use the awarded funds to strengthen UI program integrity, including

ID verification, fraud prevention and detection, and overpayment recovery efforts in all

UC programs as describe in Section 4.g.ii. of this UIPL.

• Submit the budget narrative, grant application, SF-424 (OMB Approval No. 4040-0004), and SF-424A (OMB Approval No. 4040-0006) forms via www.grants.gov.

http://www.grants.gov/

3. Summary and Background.

a. Summary – Over the last several years, the Department has made available funding opportunities to states to take significant action to combat UI fraud and reduce improper payments in the administration of UC programs by implementing, strengthening, and enhancing ID verification, fraud prevention and detection, digital authentication, and internal security. With this UIPL, the Department is making available an additional $200 million in ARPA funding to states to further support their UI fraud prevention, improper payment reduction, and overpayment recovery efforts in all UC programs by improving tools, services, and investigations, as well as evaluating and upgrading integrity strategies to address emerging trends and new fraud schemes.

Evidence-based ID verification is the strongest method for states to ensure that the Social

Security Number (SSN) used for a UI application belongs to the person applying.

Evidence-based ID verification includes activities such as an individual presenting documentation (virtually or in person) to establish their identity. However, recognizing resource constraints and the impact they can have on the timely processing of benefits, the Department requires that, at a minimum, states use a risk-based approach to determine which claims are subject to evidence-based ID verification. A risk-based approach means that states are using cross-matches and data analytics at different points throughout the life of the claim (described further in Section 4.a. of this UIPL).

States are required to conduct certain integrity controls aimed at fraud prevention and detection activities and certain overpayment recovery activities. However, simply deploying a fraud prevention and detection tool, implementing an ID proofing solution, or adding a new cross-match should not be the only action a state takes. States are expected to consider where in the UI process a tool, solution, or resource is best used and how investigations will be prioritized to reduce improper payments. These tools, strategies, and activities should undergo continuous review and data analysis for effectiveness and to ensure equitable access for legitimate claimants. Additionally, these reviews should provide an opportunity for continuous evaluation to ensure timely and accurate payments to eligible individuals. Section 4.b. and 4.c. of this UIPL provides states with information on required and recommended strategies, tools, and services for

UI fraud risk mitigation, improper payment reduction, and overpayment recovery.

Section 4.d. of this UIPL provides details on evaluating data to ensure effectiveness and equity in ID verification and fraud prevention and detection.

While addressing fraud and mitigating improper payment risks, it is also critical that states protect victims of UI ID fraud. States should ensure the state’s UI fraud reporting instructions are understandable. States should also have established processes and clear communication protocols in place when tips involving UI ID fraud are received. Section

4.e. of this UIPL provides information on protecting individuals impacted by UI ID fraud.

Section 4.f. of this UIPL reminds states of the many resources available to support states with UI integrity efforts.

To enable states to continue strengthening UI program integrity, this UIPL announces the availability of up to $200 million in additional ARPA funding for the implementation of tools, services, and activities discussed throughout the UIPL. ETA will review and approve proposed projects/activities prior to awarding the funds available under this grant opportunity. Section 4.g. of this UIPL describes the methodology for determining individual state allocations and outlines the allowable use of funds made available under this opportunity.

As a condition of receiving funding under this UIPL, states must agree to continued information disclosure with the Department’s Office of Inspector General (DOL-OIG) as described in Section 4.h. of this UIPL. States will be required to report on the quarterly progress and implementation of each project/activity to their ETA Regional Office.

Section 4.i. of this UIPL provides application instructions and Section 4.j. of this UIPL details reporting requirements.

This UIPL focuses specifically on articulating a vision of effective methods of ID verification, fraud prevention and detection, and overpayment recovery efforts, as well as providing funds to support states in implementing new methods and enhancing their existing processes. ETA will continue to provide states with technical assistance and future guidance that promotes continuous improvement and enhancement for integrity and equitable access in the UI system.

b. Background – On March 11, 2021, the President signed ARPA into law (Public Law

(Pub. L.) 117-2). Section 9032, ARPA, creates a new Section 2118 of the Coronavirus

Aid, Relief, and Economic Security (CARES) Act (Pub. L. 116-136) and provides for a

$2,000,000,000 appropriation to the Secretary of Labor (Secretary) to detect and prevent fraud, to promote equitable access, and to ensure timely payment of benefits to eligible workers with respect to UC programs. ARPA sets out the allowable uses of these funds, including to make grants for such purposes to states or territories administering UC programs.

State UI agencies entered the COVID-19 pandemic after experiencing the lowest claims workload, and thus lowest administrative funding, in 50 years, which significantly impacted resources and staffing levels. As pandemic shutdowns began impacting the nation’s labor market, states had to rapidly increase staffing levels with minimal time for the proper training needed to respond to the unprecedented increase in claims volume.

During this time, states also had to quickly transition to fully remote operations to mitigate the spread of COVID-19 in their agencies. Simultaneously, states were asked to implement complicated new temporary pandemic UC programs, with new eligibility requirements, for individuals not typically eligible for UI benefits, such as self-employed and certain gig economy workers. Many states were challenged by antiquated UI information technology (IT) systems and/or were in the process of modernizing their IT systems, while also implementing and administering the temporary pandemic UC programs. To add further complication to state UC program operations, the frequency and complexity of fraud attacks against state UC programs increased significantly during the pandemic. States were forced to respond to and address relentless and sophisticated fraud attacks that continued to evolve to circumvent the prevention and detection tools and strategies states had in place.

The DOL-OIG issued two alert memorandums,1 identifying potentially fraudulent unemployment benefits paid in four specific high-risk areas, which included individuals with SSNs: (1) filed in multiple states, (2) of deceased persons, (3) used to file UI claims with suspicious email accounts, and (4) of federal prisoners. The Department has taken action to support states in actively and aggressively addressing UI fraud and reducing improper payments and many actions have targeted the specific types of fraud identified by the DOL-OIG. Additionally, in June 2022, the U.S. Government Accountability

Office (GAO) added “the UI system to its list of federal areas at ‘High Risk’ for waste, fraud, abuse, and mismanagement, or in need of broad-based transformation.”2

Furthermore, GAO issued two reports3 recommending the Department assess fraud risks to the UI program in alignment with GAO’s Fraud Risk Framework.4 The Department is actively working to enhance its existing UI fraud risk management processes, using

GAO’s Fraud Risk Framework as a guide, and will continue to identify and address UI fraud risks. UI program integrity remains a top priority for the Department and the entire

UI system. ETA’s efforts to address fraud risks and improve integrity in the UC programs includes providing guidance, technical assistance, funding to states to combat fraud and reduce improper payments, and requiring states to submit an Integrity Action

Plan (IAP) as part of its State Quality Service Plan. ETA is also investing in developing new and enhancing existing tools, datasets, and resources and making them available to aid states in more quickly identifying potential improper payments and fraud.

On August 11, 2021, the Department issued UIPL No. 22-21, which provided states with

$140 million in ARPA funding for fraud detection and prevention, including ID verification and overpayment recovery activities, in all UC programs. The Department also made available up to $525 million in CARES Act funding to assist states with efforts

1 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) and 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).

2 See GAO Report issued on June 7, 2022, entitled “Unemployment Insurance: Transformation Needed to Address

Program Design, Infrastructure, and Integrity Risks” at https://www.gao.gov/assets/gao-22-105162.pdf.

3 See GAO Report issued October 27, 2021, entitled “Additional Actions Needed to Improve Accountability and

Program Effectiveness of Federal Response” at https://www.gao.gov/assets/gao-22-105051.pdf and GAO Report issued January 23, 2023, entitled “Unemployment Insurance: Data Indicate Substantial Levels of Fraud during the

Pandemic; DOL Should Implement an Antifraud Strategy” at https://www.gao.gov/assets/gao-23-105523.pdf.

4 See A Framework for Managing Fraud Risks in Federal Programs at https://www.gao.gov/assets/gao-15-593sp.pdf.

https://www.oig.dol.gov/public/reports/oa/2021/19-21-002-03-315.pdf https://www.oig.dol.gov/public/reports/oa/2022/19-22-005-03-315.pdf https://www.gao.gov/assets/gao-22-105162.pdf https://www.gao.gov/assets/gao-22-105051.pdf https://www.gao.gov/assets/gao-23-105523.pdf https://www.gao.gov/assets/gao-15-593sp.pdf to prevent and detect fraud and to recover fraud overpayments in certain CARES Act UC programs. See UIPL Nos. 28-20; 28-20, Change 1; 28-20, Change 2; and 28-20, Change

4. Additionally, UIPL No. 23-21 provided up to $260 million in funding to assist states with activities that promote equitable access to all UC programs. Under UIPL No. 11-22, ETA awarded grant funding to selected states to participate in the ARPA UI Navigator

Program which helps workers learn about, apply for, and, if eligible, receive UI benefits and related services (i.e., navigate the UI program) and supports state agencies in delivering timely benefits to workers—especially individuals in groups that are historically underserved, marginalized, and adversely affected by persistent poverty and inequality. UIPL No. 02-22, provided up to $200 million in funding to support states with implementation of recommendations made following a Tiger Team consultative assessment for fraud prevention and detection, promoting equitable access, and ensuring the timely payment of benefits, including backlog reduction, for all UC programs.

4. Guidance. UI program integrity includes ID verification, fraud prevention and detection, improper payment reduction, fraud risk mitigation, the recovery of overpayments, the prevention of underpayments, the timely and accurate payment of benefits, and ensuring equitable access in all UC programs. ETA continuously develops and oversees implementation of integrity strategies that target the root causes of improper payments. The

Department continues to update its antifraud strategies and is committed to ensuring its UI fraud risk management activities are conducted in alignment with GAO’s Fraud Risk

Framework. GAO’s Fraud Risk Framework calls for a strategic approach for assessing and managing fraud risks. Since the UI program is a federal-state partnership, which means both the Department and state UI agencies are responsible for ensuring UI program integrity, states must also evaluate UI fraud risks and implement and maintain sufficient controls to effectively prevent fraud and reduce improper payments.

a. ID Verification in UC Programs. Section 1137(a)(1), of the Social Security Act (SSA), provides for states to require that individuals furnish their SSN as a condition of eligibility for benefits. As noted in Section 3.A.(1) of UIPL No. 35-95, any system planned or implemented to provide ease and convenience for filing claims must provide safeguards, including a way to ensure that the name and SSN used to establish eligibility for UC belongs to the individual filing the claim. Therefore, this provision of the SSA requires that states verify an individual’s identity to ensure that the individual filing the claim is the owner of the name and SSN used when establishing eligibility. The strongest method by which states can ensure the name and SSN belong to the individual applying for UC is by conducting evidence-based verification. Evidence-based verification includes activities such as an individual presenting ID documents (i.e., official government-issued documentation, control over a device, account or address known to be associated with an identity, or biometric information) at a physical location, through a virtual platform, or through other state-developed processes or procedures that validate or verify an individual’s identity.

Evidence-based verification is most effective at preventing ID fraud:

• during the UC application process,

• immediately following the completion of an initial claim,

• during any break in the claim series (e.g., additional and reopened claims), or

• when a claim is prioritized for investigation based on results of cross-matching or data analytics and evidence-based verification has not already been completed.

The Department encourages states to employ different fraud prevention and ID verification strategies at different points throughout the life of the claim. At a minimum, states must use a risk-based approach to determine which claims should be subject to evidence-based ID verification. A risk-based approach involves states using cross-matches and data analytics to identify suspicious activity that may be indicative of fraud.

States must prioritize the investigation of claims having the greatest risks, and where appropriate, require the completion of evidence-based ID verification.

Cross-matching and data analytics are most effective when conducted in real-time during the UC application and/or initial claims process. Crossmatching and data analytics should also be conducted when a state identifies a change to key user data (e.g., bank account or mailing address information) on an existing claim, which may raise suspicion of “claim hijacking” or “claim or account takeover”. The state should immediately take action by flagging the claim for investigation and conducting account verification services (AVS)/bank account verification (BAV) and/or other data analysis to ensure the change was made by the legitimate owner of the claim.

As workloads fluctuate and fraud schemes evolve, the Department expects states to continuously monitor their fraud management operations and collective ID verification efforts for effectiveness and adaptation.

i. ID Proofing. As defined by the National Institute of Standards and Technology

(NIST) 5, ID proofing is the process by which a credentialed service provider

(CSP)6 collects, validates, and verifies information about a person to establish that an individual is who they claim to be. ID proofing is one of many options states may use to conduct evidence-based ID verification. States implementing ID proofing in their UC programs must implement solutions/services that balance equitable access with alignment to NIST digital identity guidelines. For example, 5 NIST Special Publication (SP) 800-63 provides technical requirements for implementing digital identity services.

The publication includes: an overview of identity frameworks; using authenticators, credentials, and assertions in a digital system; and a risk-based process to select assurance levels at https://pages.nist.gov/800-63-3/sp800-63-

3.html.

6 NIST SP 800-63 defines a CSP, as a trusted entity that issues or registers subscriber authenticators and issues electronic credentials to subscribers. A CSP may be an independent third-party or issue credentials for its own use.

https://pages.nist.gov/800-63-3/sp800-63-3.html https://pages.nist.gov/800-63-3/sp800-63-3.html states that utilize ID proofing are required to provide a non-digital alternative option such as in-person ID verification at locations like American Job Centers.

States are encouraged to continue to refine and expand non-digital ID verification option(s) with funds from this opportunity, leveraging resources in their states where individuals can go or have gone to have their identity proofed.

The Department has piloted the use of Login.gov, the federal government's secure sign-in service operated by the General Services Administration, to provide ID verification for UI services conducted online. The Department plans to expand the availability of this service to other states and encourages states to contact their

ETA Regional Office to learn more about Login.gov and how to participate. In addition, the Department is launching a new service to provide in-person, evidence-based ID verification at U.S. Postal Service locations in states across the country.

b. Fraud Prevention and Detection Activities. An antifraud strategy describes existing fraud control activities as well as any new control activities a program may adopt to address residual fraud risks. ETA issued UIPL No. 23-20, on May 11, 2020, reminding states of required and recommended program integrity functions for the UC programs. In this UIPL, ETA is consolidating and clarifying these activities and expanding the recommended program integrity functions as outlined below. ETA reiterates the importance of conducting the required program integrity functions and encourages states to incorporate all recommended functions into a state’s fraud management operations.

States must continue to use, operate, and maintain the required integrity controls and the required overpayment recovery activities discussed below at all times, including during times of mass unemployment events, absent specific statutory authorization allowing suspension of such controls or activities. ETA also strongly encourages states to use, operate, and maintain the recommended integrity controls and recommended overpayment recovery activities discussed below during such periods.7

In accordance with UIPL Nos. 02-16 and 02-16, Change 1, states must ensure that the fraud prevention and detection technologies/strategies they use do not create barriers that prevent or limit access for some individuals in violation of applicable federal equal opportunity or nondiscrimination laws. This may include identifying potential barriers that may impact historically underserved and marginalized populations when making design decisions and training team members on equity-related issues and processes.

7 The DOL-OIG issued reports raising concerns that some states suspended and ceased operating some of the required and recommended integrity controls during portions of the pandemic. See DOL-OIG Report No. 19-22-

006-03-315, COVID-19: ETA and States Did Not Protect Pandemic-Related UI Funds from Improper Payments

Including Fraud or from Payment Delays; and DOL-OIG Report No. 19-21-002-03-315, 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.

https://www.oig.dol.gov/public/reports/oa/2022/19-22-006-03-315.pdf https://www.oig.dol.gov/public/reports/oa/2022/19-22-006-03-315.pdf https://www.oig.dol.gov/public/reports/oa/2021/19-21-002-03-315.pdf

States should continuously evaluate their fraud prevention and detection activities from the perspective of equitable access.

i. Required Fraud Prevention and Detection Activities. States must use, operate, and maintain the following integrity controls to prevent and detect fraud.

• ID Verification (Section 1137(a)(1) of the Social Security Act and UIPL

No. 35-95) including proper notification and adjudication when an eligibility issue arises (UIPL No. 16-21);

• National Directory of New Hires cross-match (UIPL Nos. 13-19 and 19-

11, TEN No. 05-20);

• Quarterly Wage Records cross-match (20 C.F.R. 603.23);

• Systematic Alien Verification for Entitlement (SAVE) (Section 1137(d) of the Social Security Act (42 U.S.C. §1320b-7); and

• Referral of allegations reasonably believed to constitute UC fraud, waste, abuse, mismanagement, or misconduct to DOL-OIG (UIPL No. 04-17, Change 1).

ii. Recommended Fraud Prevention and Detection Activities. ETA strongly recommends states implement, use, operate, and maintain the following integrity controls.

• UI Integrity Center’s Integrity Data Hub (IDH) (see Section 4.f.iii.D. of this UIPL for details on IDH functionalities/resources);

• Digital Authentication, such as Multifactor Authentication (MFA);

• Device Fingerprint/Reputation Management, which establishes a combination of inputs (i.e., digital identity) to assist in the authentication of a user’s identity during ongoing use of online state UI systems;

• Fraud Risk Scoring (i.e., Case Management Prioritization), which includes using sophisticated risk analytics to assign a risk-based score to claims to detect suspicious activity early in the claims process, as well as minimize the number of false positives to protect legitimate claimants from being flagged for suspected fraud and avoid disproportionately assigning high risk scores to particular groups of claimants;

• Comparisons and cross-matches that detect shared characteristics (e.g., phone numbers, mailing addresses, email addresses, and banking information) on multiple claims;

• Social Security Administration cross-matches (i.e., Unemployment

Insurance Query (UIQ), Prisoner Update Processing System (PUPS), Death Master File) (see Section 4.f.vii. of this UIPL for details regarding

PUPS);

• Federal, state, and local incarceration cross-matches;8

• Deceased Records cross-matches;

• Vital Statistics cross-matches;

• State Directory of New Hires cross-match;

• Department of Motor Vehicle cross-match;

• Interstate Benefits (IB) cross-match;

• State Identification Inquiry (SID) and IB8606 enhancements made to the

Interstate Connection (ICON) network cross-match to prevent concurrent claim filing in multiple states;

• State Information Data Exchange System (SIDES) (Training and

Employment Notice (TEN) No. 12-16) (see Section 4.f.vi. of this UIPL for details regarding SIDES);

• Use of a unique identifier to identify claimants instead of using the full

SSN;

• Fictitious employer cross-matches;

• Periodic IT security assessments and audits consistent with NIST-compliant IT security guidelines (UIPL No. 04-21);

• Adequate internal controls to protect the integrity and security of state assets (UIPL No. 14-17); and

• Implement a cross-functional integrity task force to develop and implement state-specific action plans to reduce UI improper payments

(UIPL No. 19-11);

iii. Effectively Conducting Fraud Prevention and Detection Activities. As noted above, simply deploying a fraud prevention and detection tool, implementing an

ID proofing solution, or adding a new cross-match is not the most effective strategy for fraud prevention and ID verification. To effectively prevent and detect fraud, the state should consider where in the UI process every tool, solution, and resource is best used and how investigations are prioritized to prevent fraud and reduce improper payments.

States should think strategically about how cross-match results are triaged and prioritize claims for investigation that have a higher probability of fraud or the potential to result in large improper payments. States should be judicious in deciding which cross-matches trigger an immediate hold on benefits, and which require further investigation before a payment series is stopped. ID verification investigations are time sensitive, especially in situations where payment has

8 Data sets from jails and prisons may not be updated in real time and therefore may lag in the reported incarceration entrance and/or release dates. Additionally, data sets may contain unreliable identity information. ETA reminds states to factor these things in when reviewing incarceration data cross-match results. After receiving incarceration cross-match information, states must conduct appropriate investigations to determine eligibility. See UIPL No. 01-

22.

already been made on a claim and the individual fails to respond by the deadline.

After the response deadline passes and no response is received, states should act quickly to stop future payments from occurring by issuing an immediate failure to respond denial (Section 4 of UIPL No. 16-21).

Further, states should consider the frequency of cross-matches within the life of the claim – some are more effective when run often and continuously throughout the claim lifecycle. For example, a multi-state cross-match may be most effective if conducted during the initial claim application or immediately following the initial claim and prior to issuing payment. Vital statistics, deceased records, and incarceration cross-matches are critical activities that are effective if conducted during the initial claim process, and prior to issuing first payment, and may also be highly effective at continuing to confirm UI eligibility throughout the life of the claim. Other activities, such as a suspicious email domain cross-match or

AVS/BAV may be appropriate to run once or on an ad hoc basis when an email address or bank account is suspect, updated, or changed on a claim.

States should take the following three actions to strengthen fraud prevention and detection using the IDH:

1. Take advantage of, and use, all IDH functionality;

2. Implement IDH web service/real-time connectivity, if possible; and

3. Submit all UC initial and continued claims to the IDH in real-time, or daily, at minimum.

c. Overpayment Recovery Activities. UIPL No. 23-20 also reminded states of required and recommended overpayment recovery activities.9 Overpayment recovery is critical to protect both state UI trust funds and federal funds and must be given the same priority as fraud prevention and detection activities.

i. Required Overpayment Recovery Activities. States must implement, use, and maintain the following activities to recover overpayments.

• Benefit Offsets (Title II, Subtitle A of the Middle-Class Tax Relief and

Job Creation Act of 2012, UIPL No. 05-13, and Section 5 of UIPL No. 13-

20, Change 2);

• Treasury Offset Program (TOP) for applicable covered debt (Bipartisan

Budget Act of 2013, UIPL Nos. 02-19, 12-14, and 04-20);10

9 States may, under limited circumstances, elect to waive recovery of certain established non-fraud overpayments.

For overpayments in the regular UI program, these circumstances are defined in state law. For overpayments under the temporary pandemic-related UC programs, refer to UIPL Nos. 20-21 and 20-21, Change 1.

10 Covered debt includes past-due debts that are the result of claimant fraud or unreported earnings, uncollected employer contributions, and any penalties and interest assessed on such debt (26 U.S.C. § 6402(f)(4)).

• Cross Program Offset Recovery Agreement (CPORA) (UIPL No. 05-13);

and

• Interstate Reciprocal Offset Recovery Arrangement (IRORA) (UIPL No.

05-13).

ii. Recommended Overpayment Recovery Activities. ETA strongly recommends that states implement, use, and maintain the following activities to recover overpayments.

• Negotiating repayment plans;

• Accepting repayments through various methods (e.g., online, via debit/credit card);

• State Income Tax Offset Program;

• Wage garnishments;

• Property liens and assessments;

• Offsets of lottery winnings, homestead exemptions, and other benefits;

• Active participation in probate and/or bankruptcy proceedings regarding an individual with an outstanding overpayment;

• Skip tracing;

• Work proactively and collaboratively with banks and financial institutions to detect suspicious activity, ensure that accounts are not unduly suspended, and recover overpayments (UIPL No. 19-21);

• Civil actions;

• Credit bureau referrals;

• State/federal prosecution;

• Penalties and interest on overpayments in compliance with state and federal law;

• Collection agency referrals when state staff is limited, or debt is uncollectable by other means;11 and

• Other recovery methods as determined by state law or policy.

iii. Effectively Conducting Overpayment Recovery Activities. ETA recommends that states consider an escalated approach to claimant communications for overpayment recovery activities. For example, an individual with a non-fraud overpayment may successfully resolve their overpayment after receiving clear communication with instructions on how to establish a repayment plan and a clear explanation regarding any overpayment waiver processes. Only if the non-fraud overpayment is not waived and an individual fails to establish or comply with a repayment plan after a period of time that the state deems appropriate, should the

11 The immediate deposit and withdrawal standards prohibit states from paying third-party collection agencies out of a recovered overpayment. See 3304(a)(3), FUTA; 303(a)(4), SSA; 3304(a)(4), FUTA, 303(a)(5), SSA.

state send an escalating notice for further recovery activities. States may contact their ETA Regional Office to be connected to the Department’s Office of

Unemployment Insurance Modernization (OUIM) for support with plain language conversions to simplify terminology complexity when communicating with claimants as described in Section 4.f.iv. of this UIPL.

d. Evaluating Data to Ensure Effectiveness and Equity in ID Verification and Fraud

Prevention and Detection. A critical part of fraud risk management includes evaluating outcomes using a risk-based approach and adapting activities to improve fraud risk management. States should monitor and evaluate the effectiveness of fraud prevention and improper payment reduction activities, to adapt to changing risks and continuously improve the effectiveness of their fraud management operations. This includes collecting and analyzing data for fraud trends and identifying potential control deficiencies.

Effective monitoring and evaluation focuses on measuring outcomes and progress toward the achievement of objectives, rather than simply reviewing outputs and progress in implementing control activities. Results of the monitoring and evaluations should be used to improve the design and implementation of fraud risk management activities.

As states are implementing and refining processes for digital authentication, ID proofing, cross-matching, data analytics, and other fraud prevention and detection activities, states must consider and address any equitable access impacts. One of the most common barriers to equitable access is an ID proofing process that is difficult to complete.

Examples of difficulty in completing ID proofing processes may involve individuals with limited English proficiency; individuals with limited access to, or understanding of, technology; or instructions that are unclear or cumbersome. Another common barrier is states erroneously flagging legitimate claim activity as suspicious. This can result in delays for eligible individuals to receive UI benefits – a matter which is further exacerbated when states are experiencing high workload volumes, making it difficult for individuals to contact the state unemployment agency. States must ensure there is at least one timely, effective, and accessible non-digital alternative to online ID verification.

This non-digital option should not be overly burdensome on applicants, limit access to public benefits programs or the timely receipt of benefits, or stigmatize members of the public in any way.

ETA strongly recommends that states implement data collection and analysis to review their fraud prevention and detection activities – monitoring for barriers to equitable access and taking swift action to mitigate such barriers.12 The data for this analysis may come from system datapoints, customer surveys, periodic user interviews, and case samples. States should work with their service providers or with their in-house fraud

12 As described in UIPL No. 11-14, the Department’s regulations also require state compliance with the U.S. Office of Management and Budget (OMB) guidelines on the collection of data based on race or ethnicity. See 29 CFR

§ 38.41(d). States must provide information about the reasons for a data request, and the ways in which the data may be used before asking about a claimant’s race/ethnicity, sex, age, or disability status.

management operations to identify and resolve any barriers or equitable access impacts resulting from ID proofing practices and data analytics and cross-matching services.

When using a CSP for ID proofing or a third-party solution, ETA recommends that states establish, within their contracts, a process to receive Personally Identifiable Information

(PII) and data on an individual’s ID proofing status (i.e., verified, not verified, pending, inconclusive) within a service provider’s system or solution. To be able to properly respond to customer inquiries, states should have access to such information in real-time

(if possible), but no later than 24 hours after an individual started the ID proofing process and whenever there is a change in the ID proofing status. By knowing the individual’s

ID proofing status, the state can also ensure that appropriate instructions and next steps are provided to the individual. The Department outlined stringent technical, service level, business performance, and equity requirements in its solicitation for ID proofing services described in TEN No. 06-21. ETA recommends that states incorporate similar provisions in their ID proofing solicitations and contracts with service providers.

Attachment VI to this UIPL describes recommended contract provisions for ID proofing services and solutions.

DOL-OIG recently issued an Alert Memorandum13 highlighting concerns about states’ use of ID verification service providers, specifically those employing the use of facial recognition technology, and the impact these ID proofing services may have on equitable and secure access to UI benefits. ETA strongly encourages states to carefully review ID proofing solutions that use biometrics such as facial recognition. While these solutions may help to reduce ID fraud, they may have negative implications for14or lead to violations of states’ nondiscrimination obligations under Section 188 of Workforce

Innovation and Opportunity Act (WIOA). States are reminded that a non-digital alternative option for ID verification must be available and not require substantially more time, hardship, or delay to complete. Furthermore, states using ID proofing solutions that employ the use of facial recognition technology, must test the system for biases15 and work with the service provider to identify and resolve any biases or barriers to equitable access resulting from the ID proofing process.

13 Alert Memorandum: ETA and States Need to Ensure the Use of Identity Verification Service Contractors Results in Equitable Access to UI Benefits and Secure Biometric Data, Report No. 19-23-005-03-315 (March 31, 2023).

14 For instance, recent research indicates that, depending on how it is implemented, certain biometric technology may have a disproportionate adverse impact on protected groups. See, e.g., National Institute of Standards and

Technology (NIST), NIST Study Evaluates Effects of Race, Age, Sex on Face Recognition Software (Dec. 19, 2019), https://www.nist.gov/news-events/news/2019/12/nist-study-evaluates-effects-race-age-sex-face-recognition-software (finding demographic differentials in the majority of the 189 face recognition algorithms studied, and noting that “a false positive in a one-to-many search puts an incorrect match on a list of candidates that warrant further scrutiny”).

15 States should be aware that 29 CFR § 38.51 requires UI program administrators to conduct statistical or other quantifiable data analyses of demographic records and data to determine whether their UI programs and activities are being conducted in a nondiscriminatory way.

https://www.oig.dol.gov/public/reports/oa/2023/19-23-005-03-315.pdf https://gcc02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.nist.gov%2Fnews-events%2Fnews%2F2019%2F12%2Fnist-study-evaluates-effects-race-age-sex-face-recognition-software&data=05%7C01%7CAzhdam.Rebecca%40dol.gov%7C06fe3abd3c8149ce480708dadde4124a%7C75a6305472044e0c9126adab971d4aca%7C0%7C0%7C638066268866735081%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=pwbj%2BLW%2F%2Fr5oM0X90Yk9PVKC%2FoYdz1NvsFnbhdQfwNU%3D&reserved=0 https://gcc02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.nist.gov%2Fnews-events%2Fnews%2F2019%2F12%2Fnist-study-evaluates-effects-race-age-sex-face-recognition-software&data=05%7C01%7CAzhdam.Rebecca%40dol.gov%7C06fe3abd3c8149ce480708dadde4124a%7C75a6305472044e0c9126adab971d4aca%7C0%7C0%7C638066268866735081%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=pwbj%2BLW%2F%2Fr5oM0X90Yk9PVKC%2FoYdz1NvsFnbhdQfwNU%3D&reserved=0

Below are a few examples of data points and information that can be used to conduct meaningful analysis, monitor equity outcomes, and make necessary changes to ensure equitable access.

• PII and data on an individual’s ID proofing status (i.e., verified, not verified, pending, inconclusive) within a service provider’s system or solution to identify any disparate results amongst demographic groups or specific friction points within the ID proofing process, such as:

o Data from individuals who successfully verify through alternative method(s) after failing initial screenings, including appeals data;

o Number of ID proofing attempts each user is making;

o Time spent in the system at each identification step;

o Wait time for customer service requests related to ID proofing;

o Location, device type, and connection type;

o The strength of the identification match; and o System, monitoring, and incident reports.

• How many claimants used a non-digital option to verify their ID including:

o what caused them to be unable to access the technology (if applicable);

o what caused them to be denied by the technology (if applicable); and o which alternative access option was used.

• Which claims were flagged as suspicious and warranting further investigation, including:

o the length of time to resolve these investigations; and o the outcome of these investigations, such as whether they resulted in a fraudulent overpayment, non-fraudulent overpayment, suspected/confirmed ID fraud, claim abandoned during the ID verification process, or a non-issue (i.e., “false positive”), by demographic group.

Additionally, ETA strongly recommends conducting root cause analysis to identify the source of specific instances where legitimate claimants have been adversely affected by

UI program integrity measures (i.e., fraud risk scoring, fraud prevention and detection activities, ID proofing systems or solutions). State root cause analysis should seek to identify issues that may exist at larger scale and may merit more systemic modifications to the state’s overall fraud risk mitigation and improper payment reductions strategies, including ID verification and fraud prevention and detection activities.

e. Protecting Victims of UI ID Fraud. States must provide individuals who suspect that they are victims of UI ID fraud with options to report such activity and, once fraud has been confirmed, states must take actions to protect the UI ID fraud victim. To meet these requirements, ETA strongly recommends that states provide a reporting mechanism for

UI ID fraud on their websites, communicate status updates for such investigations, and take action to protect the victim when the state determines that UI ID fraud has occurred.

i. Providing a reporting mechanism for UI ID fraud on state websites. As described in Section 5 of UIPL No. 16-21, states must provide individuals who suspect that their ID has been stolen with easily accessible options to report such theft or fraudulent activity. This may include dedicated phone options, email addresses, or an online portal by which individuals can notify the state agency.

States may also provide links to resources from other agencies that specialize in protecting consumers and their PII, such as the Federal Trade Commission’s

Consumer website at IdentityTheft.gov.

In December 2022, the Department published updated website content on the UI

ID fraud reporting website at www.dol.gov/fraud. ETA issued TEN No. 14-22, on January 4, 2023, strongly encouraging states to align their website content and communications for individuals who experience UI ID fraud with the new content, resources, and reporting requirements outlined at https://www.dol.gov/fraud.

ii. Communicating status updates. ETA strongly recommends that states clearly communicate their UI fraud reporting requirements on their state website(s) and have in place established processes and procedures for assisting individuals who have experienced UI ID fraud. To reduce confusion and anxiety for a victim of

UI ID fraud, states should provide updates throughout the process once a report of

UI ID fraud has been received. This may include, but is not limited to:

• Providing confirmation to the submitter that the fraud report was received;

• Clearly defining expectations and outlining next steps;

• Providing ongoing updates to the submitter and/or SSN owner (if known) throughout the investigation; and

• Notifying the submitter and/or SSN owner (if known) once the investigation is complete.

iii. Protecting victims. When a state determines that UI ID fraud has occurred the state must take actions to protect the rights of the UI ID fraud victim. As discussed in UIPL No. 20-21, Change 1, once the state issues a fraud determination, one option states can use to mitigate negative impacts on the UI ID fraud victim is to establish a pseudo claim record and transfer all claim information regarding the fraudulent activity to the pseudo claim. This removes the fraudulent activity from the victim's SSN and/or UI account, which should remove barriers the victim may encounter if they need to file for UI in the future.

This solution also applies to “claim hijacking” (also known as “claim or account takeover”). On hijacked claims, any weeks that were fraudulently redirected must be removed from the legitimate UI claim and the weeks must be immediately repaid to the rightful owner of the claim if eligibility for those weeks is determined. In the case of hijacked claims, the state should employ ID https://gcc02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.identitytheft.gov%2F&data=05%7C01%7Cgarrett.jennifer.l%40dol.gov%7C798ad9b6ff6f4e0e2a0708daf26c0339%7C75a6305472044e0c9126adab971d4aca%7C0%7C0%7C638088842980124889%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=wsXJpNXR6cVv1xFqVKjmiXcdeH93%2F3bKBlTkScdquj4%3D&reserved=0 http://www.dol.gov/fraud https://www.dol.gov/fraud verification as part of its investigation to verify the legitimate claimant’s ID prior to repaying the weeks.

States are also strongly encouraged to use the UI Integrity Center’s IDH BAV service to authenticate new bank account information provided on all claims prior to issuing payments, including verifying bank account information on claims that have been determined to be hijacked, prior to reissuing any payments. The IDH’s

BAV service validates the status of the bank account (e.g., account is open or closed) and provides a level of assurance that the individual identified as the UI claimant is the bank account owner and/or authorized user.

States that may not have the current administrative capability to move such activity to a pseudo claim may choose to temporarily mark the overpayment as

“uncollectible.” This ensures that UI ID fraud victims are not negatively impacted while the state develops a process to disassociate the fraudulent activity from the victim’s SSN. Below are other actions the state may take to mitigate the negative consequences for the UI ID fraud victim:

• Ensure that if a future claim is filed under the victim’s SSN, the claimant undergoes a secondary ID verification process (e.g., include an in-person reporting requirement or other expanded ID verification alternatives).

However, states should try to minimize the burden on the victim as much as possible when verifying identity.

• Ensure that the owner of the SSN is not held responsible for any overpayment and, whenever possible, is not issued a Form 1099G at the end of the year.

• Exclude the overpayment from TOP and suspend any Benefit Payment

Control collection activity for the actual owner of the SSN.

• Do not initiate any legal actions against the actual owner of the SSN.

f. Additional Important Resources, Strategies, Tools, and Services for States. As noted above, fraud prevention and detection activities, as well as overpayment recovery activities, are strongest when states employ a variety of tools, strategies, and resources.

ETA reminds states of the many other resources available to support states with ID verification, fraud prevention and detection, and overpayments recovery.

i. ETA’s Regional Offices. ETA’s Regional Offices are available to provide states with ongoing technical assistance regarding integrity strategies, tools, and services and to connect states with such resources supported and funded by the

Department. States are encouraged to work closely with ETA’s Regional Offices to address root causes of fraud and improper payments and in developing IAPs and any needed corrective action plans.

ii. Tiger Teams. The Department’s multidisciplinary technical assistance teams

(known as Tiger Teams) work with states to conduct consultative assessments to address state-specific, unique challenges and/or collect best practices to prevent and detect fraud, promote equitable access, reduce backlogs, and ensure timely payment of benefits. Tiger Teams work with states to identify immediate needs and issues focused on near-term improvements in customer experiences and improved operational processes, while also proposing grant funded recommendations to address fraud and support more equitable access for legitimate claimants. The Department engaged with 24 states for the Tiger Team initiative in Year 1 (July 2021 - June 2022) of the project and continues to finalize and deliver recommendations to states based on Tiger Team consultative assessments. Trends from Tiger Team recommendations are available at:

https://oui.doleta.gov/unemploy/pdf/TigerTeamCohortTrendsJune_2022.pdf.

ETA strongly encourages all states to engage in a Tiger Team consultative assessment. See UIPL Nos. 02-22 and UIPL 02-22 Change 2.

iii. UI Integrity Center. Established and funded by the Department and operated by the National Association of State Workforce Agencies (NASWA) Center for

Employment Security…