As much as $26 billion in unemployment benefits in the United States is either being taken by fraudsters or improperly made for one reason or another, a top federal government watchdog estimates.
Scott Dahl, the inspector general (IG) of the U.S. Department of Labor, recently offered the sobering statistic at a hearing before the House of Representative’s Subcommittee on Government Operations.
The estimate is based on a 10 percent fraud and abuse rate applied to the $260 billion expansion in jobless benefits under the federal, multitrillion-dollar economic rescue package, also known as the CARES Act, the Labor Department IG noted.
And that number may even be higher, based on a 10 percent fraud and abuse rate typical even “during the best of times,” Dahl told members of the House Committee, adding pointedly, “and we are in the worst of times.”
In order to divert unemployment payments into their hands, cybercriminals and other fraudsters are stealing the identities of a range of taxpayers, including workers battling on the frontlines in the struggle to contain COVID-19, Dahl said.
Dahl said his department is currently probing the fraudulent use of the identities of more than 36 different frontline healthcare workers to apply for unemployment benefits.
But that case is just a drop in the bucket in an ocean of potential fraud, with Dahl noting, in his written remarks, that his department is now investigating over 300 cases of potential unemployment insurance fraud.
Key issues plaguing both the U.S. Department of Labor and its counterparts on the state level across the country are “inadequate state staffing and outdated IT systems,” Dahl told members of the House Subcommittee on Government Operations.
Self-certification by self-employed and gig workers, who are eligible for jobless benefits for the first time under the CARES Act, is another area of vulnerability, Dahl said, noting an alert had been sent out to state employment officials across the country.
“The enormous expansion of UI benefits by more than 260 billion dollars under the CARES Act also substantially increases fraud risk, with criminals easily exploiting system vulnerabilities,” Dahl said
The U.S. Cares Act also included the Paycheck Protection Program (PPP) to help businesses, along with stimulus payments for Americans — $1,200 for individuals, $2,400 for couples and $500 per child. The payments came by way of direct deposits, paper checks and debit cards.
Agentic artificial intelligence (AI) promises to improve operational efficiencies and the customer experience offered by enterprises.
The advanced technology is finding applications in loan underwriting and fraud detection, and now it’s moving across borders.
TerraPay Co-Founder and Chief Operating Officer Ram Sundaram told PYMNTS as part of the “What’s Next in Payments” series focused on exploring AI’s use in banking and by FinTechs that automated decision making and streamlined processes will continue to transform global money movement, especially as faster payments gain ground in cross-border transactions. That’s the inexorable trend, but as Sundaram put it, there’s still room, and a necessity, to have some human interaction in the mix.
In terms of global fund flows, TerraPay’s single connection ties more than 3.7 billion mobile wallets together across 200 sending and 144 receiving countries, touching 7.5 billion bank accounts. As one might imagine, coordinating and enabling the transactions is complex.
“Obviously, in the best-case scenario, everything goes smoothly, but when things are not going smoothly, that’s when the customer queries come in,” Sundaram said.
It’s no easy task to find out straight away where a transaction is, as analysts and representatives at the company have to look at logs and query partner systems.
“A lot of that work is done manually,” said Sundaram, who added that the agents “know the corridors and the markets that they are working in, but it still takes some time.”
TerraPay is using AI models with machine learning to bolster customer support and automate tasks as financial institutions (TerraPay’s client base) send payments in real time, and those payments are processed into local markets’ beneficiary banks.
“We still don’t trust [AI models] to let them respond to the customer straight away, but we can do the analysis, and then that gets reviewed by an agent who decides if [information] is accurate or not and then sends it off,” Sundaram said.
The same principles are guiding AI models and company practices to improve technical and security operations, analyzing and categorizing anomalous transactions and automating integrations with partner firms.
“Compliance is an issue where there is a lot of review needed of the alerts, and we are using [AI models] to speed up those processes,” Sundaram said.
Asked by PYMNTS about how agentic AI can be harnessed, he said: “In financial services, you can’t take chances on technology like this, which has the freedom to go wrong. You have to be careful about making sure that it’s 100% reliable before we can let things run entirely by automation.”
Agentic AI also remains pricey. For example, OpenAI is charging $20,000 a month for its specialized agents. However, Sundaram said the industry will become commoditized quickly, which will lower prices, and some open-source offerings are capable.
“There’s a fire hose of news about breakthroughs and new ideas and new ways of doing things that are coming out on a daily basis,” he said.
Data underpins it all, and Sundaram told PYMNTS that no matter what the application, the information fed into the models must be clean. Most organizations have a range of data sitting in different intra-company silos, and those silos need to come down.
In addition, the data must be structured so that it is accessible and can be synthesized by the models. Many firms may have more than 1,000 software-as-a-service (SaaS) resources to which they are subscribed but are not accurately tracked or monitored.
“Every database is separated, each one sitting somewhere else,” he said.
The days of stitching together those separate SaaS offerings to run an enterprise are ending, he said, and we’re headed to a future when data is collected in one place.
AI models and agentic AI “are extensions of what we’ve always valued at TerraPay, which means building the most efficient infrastructure possible in order to make sure that transactions are processed safely, quickly and affordably,” Sundaram told PYMNTS. “We see AI and [AI models] as powerful tools that help us scale all this very quickly while making sure we build more and more efficiency into the system.”
