The update to the company’s Consumer Fraud Risk (CFR) solution, announced Tuesday (Sept. 24), uses artificial intelligence (AI) to provide British banks with more visibility to prevent fraudulent transactions.

The announcement comes just days ahead of new rules requiring U.K. financial institutions to reimburse victims of authorized push payment (APP) fraud, which Mastercard notes is typically triggered by a fictitious website, email, text message or phone call. Such scams cost British consumers $607 million in 2023.

“Fraudsters have long sought to deceive the consumer through scam websites and fictitious deals,” said Mastercard Executive Vice President, Security Solutions Johan Gerber.

“That’s why, at Mastercard, we are turbocharging our technology, providing banks additional lines of defense — helping them better identify and stop scams in their tracks.”

The company says its solution has since last year helped 11 British banks identify and prevent scams. The tool works by scanning multiple data points associated with a transaction and providing a real-time risk score to the sender’s bank.

“The new, additional AI enhancements to Consumer Fraud Risk provide the receiving banks the same score within seconds, making it possible for them to detect when a payment may be destined for an account used by fraudsters, known as a mule account,” Mastercard added, noting that it plans to expand the fraud risk prevention globally “within the year.”

Mastercard’s updated offering comes as financial institutions (FIs) are increasingly turning to AI to bolster their fraud prevention capabilities.

“The adoption of AI and machine learning (ML) technologies is transforming how transactions are monitored and secured,” PYMNTS wrote last month.

“A significant 94% of payments professionals view AI primarily as a tool for improving fraud detection. AI’s predictive analytics capabilities help identify potential fraud by analyzing user behavior patterns and transaction anomalies.”

Aside from fraud detection, AI is being employed for personalized customer service and operational efficiencies. And a survey last year by FICO survey found that a little more than three-quarters of customers expect FIs to use AI for better fraud prevention, spotlighting the increasing demand for advanced security measures.

“AI’s ability to provide real-time alerts about suspicious activities further underscores its critical role in the future of secure and efficient payments,” PYMNTS wrote.

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The analytics software company said Wednesday (Sept. 18) it has collaborated with the British Channel Islands-based telecom to develop a solution that allows for “direct, near real-time intervention” to protect customers against fraud.

“FICO and JT worked with leading UK banks to identify the most relevant telephony signals that indicate an active scam,” the company said in a news release.

The term “telephony” refers to the technology that lets people communicate across long distances via things like voice or fax.

FICO’s Customer Communications Service Scam Signal, the release notes, is available in Jersey, the U.K. and Spain, and is the first real-time application of telephony data being used with customer and payment data to prevent authorized push payment (APP) fraud, in which consumers are duped into sending authorized payments to scammers.

“This type of fraud is growing around the world; 2023 losses in the UK alone reached £460 million,” said Clare Messenger, head of mobile intelligence solutions at JT. “To protect customers from being caught by such scams, the new FICO and JT solution enables direct intervention with the customer to quickly determine if a payment should proceed.”

According to the release, FICO’s analysis uncovered strong correlations between a customer’s mobile phone behavior and the likelihood that a scam was occurring.

For instance, a victim might be “actively coached through security or manipulated by a fraudster into making a payment” during a phone conversation, the company said.

Scam Signal, the release added, uses advanced analysis of real-time network data coupled with customer and payment data, during live transactions, to detect and mitigate social engineering attempts aimed at tricking and defrauding consumers.

APP fraud’s prevalence in the U.K. has led regulators there to introduce new reimbursement rules for banks and payment companies. Those rules are set to go into effect next month, requiring financial institutions to repay victims up to 85,000 pounds.

In other fraud prevention news, PYMNTS earlier this week looked at the rising threat of invoice fraud, targeting companies’ finance departments.

Fraudsters “will call your back-office staff who are not trained in payments fraud prevention and try to communicate false information over the phone. And these staffers, they are great, smart, hardworking people, but they do not have the tools and that is why the fraudsters are attacking them,” Ernest Rolfson, founder and CEO of Finexio, told PYMNTS in July.

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The new tools, announced Tuesday (Sept. 10), are designed to offer real-time fraud detection and risk management services amid a surge in digital transactions and evolving cyber threats.

First up is Galileo Instant Verification Engine (GIVE), which is designed to provide real-time verification of external bank accounts and ownership. Able to be used on its own or as an integration with Galileo’s payment risk platform, GIVE lets businesses stop fraud by quickly verifying account existence, status, and ownership before transactions are processed.

“GIVE is further enhanced by its integration with the Galileo Payment Risk Platform, which uses a sophisticated Transaction Decision Rules Engine,” the company said.

“This engine applies customizable models, rules and profiles to each transaction, allowing for real-time, automated fraud prevention decisions tailored to the specific needs and risk appetite of each business.”

Galileo has also introduced Transaction Risk GScore, a machine-learning-based offering that assesses the risk of card transactions in real time, adding “a layer of fraud signals” to the payment risk platform while letting customers “determine the risk appetite based on the multiple model responses.”

Meanwhile, PYMNTS spoke recently with Max Spivakovsky, senior director of strategy and operations, global payments risk management and onboarding at Galileo, about the tightropes walked by banks as they try to balance delivering digital services and payments choices while also preventing fraud.

That balancing act requires financial institutions (FIs) to use both proactive and reactive approaches, as well as technological tools, as they defend themselves while providing a personalized, convenient customer experience, Spivakovsky said.

“The legacy solutions just don’t work anymore,” he told PYMNTS. “Leveraging a single tool used to be the ‘paramount’ strategy of fraud mitigation years ago, but now it’s just not applicable … the FIs must think about fighting fraud with a holistic perspective.”

The holistic perspective can pay dividends while safeguarding the FI from financial losses and reputational risk, he added.

“The client experience drives the engagement, and utilization of [banking] apps and programs,” Spivakovsky said.

He also noted that the financial services sector is shifting away from an era when banks took charge of everything and kept all data and processes on site, toward relying on FinTechs and other providers to provide real-time fraud prevention and identify fraud and scam patterns before they hurt banks and their customers.

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But while external cyberattacks dominate headlines, insider fraud — the deliberate exploitation of an organization’s systems by employees or individuals with internal access — presents an equally formidable challenge.

And as a settlement announced last week (Sept. 5) between CIRCOR International Inc. and the U.S. Securities and Exchange Commission (SEC) reveals, inside fraudsters tend to both target and operate within their organization’s finance and accounting departments.

Per the SEC complaint, CIRCOR’s finance director “concealed his misconduct by manipulating account reconciliations, falsifying certifications, fabricating bank confirmation documents, and misleading CIRCOR’s management and independent auditors.”

Employees in finance and accounting best understand their organization’s financial processes, internal controls and loopholes. This insight allows them to exploit weaknesses without raising suspicion. Fraudsters hiding in finance departments can manipulate accounting records, hide unauthorized transactions or create false entries, making it difficult for regular audits or oversight to detect discrepancies.

In some organizations, especially smaller firms, finance staff may have overlapping roles, such as handling both payments and reconciliations, reducing checks and balances that could detect fraudulent activity.

All this combines to make insider fraud notoriously difficult to detect, often requiring businesses to wade through vast volumes of data and navigate a myriad of complexities to catch early warning signs.

Read more: Why Business Email Compromise Scams Target Valuable B2B Relationships

Data and Automation Key to Effective Fraud Prevention

Organizations that invest in automation and data-driven solutions will be better equipped to protect their assets, reputation and long-term success.

That’s because identifying potential red flags and malicious activities through traditional manual review methods is a time-consuming, resource-intensive endeavor. The sheer volume of transactions, interactions and data points within modern organizations further complicates this task, making the use of automated systems and data-driven approaches indispensable.

One of the primary benefits of automation is its ability to continuously scan data for irregularities. Automated systems can be programmed to detect anomalies in real time, flagging unusual patterns such as unauthorized access to sensitive information, unusual financial transactions, or deviations from typical employee behavior. With machine learning (ML) and artificial intelligence (AI) technologies, these systems become smarter over time, refining their algorithms to improve detection accuracy.

PYMNTS Intelligence finds that over a quarter of surveyed firms (27%) use AI for high-risk, complex tasks, while nearly 90% have at least one high-impact use case for the innovative technology.

Automated fraud detection tools can also aggregate data from multiple sources, such as financial transactions, employee communications and operational logs, to form a holistic view of activities across the organization. By cross-referencing different data sets, these systems can identify potential risks that might be overlooked by manual analysis.

“One of the biggest differences between the consumer world … and the enterprise world is that different people are allowed different access to different information,” Eddie Zhou, head of AI at Glean, told PYMNTS. “Permissions are a first-class thing you have to think about with enterprises.”

For example, an employee making excessive changes to financial records or attempting to access confidential customer data outside of normal business hours could trigger an automatic alert. These real-time insights enable organizations to respond promptly, limiting the damage of any fraudulent activity.

Read more: Behind Company Walls: Protecting Against the Evolving Insider Fraud Threat

Protecting Against the Ongoing Insider Fraud Threat

In interviews for the “What’s Next in Payments” series, executives stressed to PYMNTS that a multilayered security strategy, also known as defense in depth, is crucial for reducing risks at various levels. This approach means implementing multiple defensive measures across the enterprise network.

One of those key defensive layers is increasingly the digitizing of legacy and paper-based payment workflows.

Research from PYMNTS Intelligence has shown that virtual cards and digital spend management solutions can help finance departments close the books faster while guarding against fraud.

“In today’s operating environment, being reactive leaves firms at a disadvantage. Fortunately, virtual cards are changing the game for businesses by letting them proactively — and easily — control their spend,” Dan Hanks, vice president of global product development at i2c, said in an interview with PYMNTS.

By leveraging real-time monitoring, predictive analytics and behavioral data — all things that data-rich payments environments provide — businesses can enhance their ability to detect and mitigate insider threats, particularly those within the finance function.

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The machine learning technique FraudGCN analyzes patterns in financial data and corporate relationships to identify and predict fraudulent activities. It uses graph theory and machine learning to examine the web of relationships between firms, their auditors and industry peers.

“It’s an unending, mathematical arms race between the authorities and the fraudsters,” Chenxu Wang, lead author of the paper and an associate professor with the School of Software Engineering and the Key Lab of Intelligent Networks and Network Security at Xi’an Jiaotong University, said in a news release.

The development comes as financial markets grapple with the impact of accounting fraud. A PYMNTS report reveals that 62% of financial institutions with over $5 billion in assets report increased financial crimes, exposing growing vulnerabilities in the U.S. banking sector. As methods for perpetrating fraud evolve, including criminals’ potential use of AI, there is ongoing interest in developing more effective detection methods.

Current Methods of Financial Fraud Detection

Traditional fraud detection methods often rely on audits, which can be labor intensive and may struggle to differentiate between genuine business success and manipulated figures. These hurdles means that many firms may go unchecked for extended periods.

Paul Wnek, founder, CEO and principal solutions architect at ExpandAP, told PYMMTS there are many common types of fraud in businesses: “Invoice fraud, such as fictitious invoices for goods or services that were never delivered or legitimate invoices that are altered to divert funds. Vendor fraud, such as setting up fake vendors to receive payments for nonexistent goods or services or kickbacks to award vendors or employees for approving contracts or invoices. Payment fraud, which can occur when fraudsters gain access to payment systems or manipulate approval processes to authorize payments fraudulently.”

These schemes can be challenging to detect using conventional methods.

“What is needed is an effective and accurate algorithm to automatically identify accounting fraud, and leave the days of random auditing behind,” said Mengqin Wang, another researcher involved in the FraudGCN project, according to the release.

FraudGCN attempts to address this by constructing multi-relational graphs representing company connections. This allows the system to analyze patterns across corporate networks.

When tested on data from Chinese listed companies, the researchers found that FraudGCN outperformed current approaches by a margin of 3.15% to 3.86%.

However, the practical implications of these improvements in fraud detection are still unclear.

The Role of AI in Fraud Detection and Perpetration

As AI’s role in fraud detection expands, experts note its potential for both detecting and aiding fraud. Joe Stephenson, director of digital intelligence at Intertel, discusses AI’s dual nature in this context.

“In the insurance industry, we are in the business of selling, and because of this, often overlook potential implications emerging technologies like artificial intelligence may have on claims,” Stephenson told PYMNTS. “While AI is great for underwriting, we are also seeing criminals leverage ChatGPT and AI to advance fraudulent activity, whether it be through the development of synthetic IDs or metadata.”

This introduces new challenges, as Stephenson explained: “Metadata isn’t traditional, and the use of social media makes it easy for any person to exaggerate claims or organize criminal groups.”

However, AI can also be leveraged to parse through large volumes of data.

“Advanced algorithms can scan and analyze social media activity, identifying patterns and anomalies that might go unnoticed by human investigators,” Stephenson said.

The “Financial Fraud Prevention Playbook” by PYMNTS examines how financial institutions can leverage advanced technologies like behavioral analytics and machine learning to combat digital-age fraud tactics, including AI-powered schemes, malicious bots and synthetic identities that evade traditional security measures.

Automation in Fraud Prevention

Alongside AI detection tools, the industry also implements automation in financial processes as a preventive measure.

“Automated accounting systems built with best practice security measures offer built-in fraud detection capabilities, such as anomaly detection and invoice matching algorithms,” Wnek said. “The best platforms are one-stop shops for all AP tasks, leading to a decrease in the number of systems between which data needs to pass through.”

This shift toward automation is an ongoing trend in the finance industry.

“Though traditionally change-averse, accounting teams have started to recognize the value of automation in improving the efficiency and accuracy of processes like accounts payable (AP) and accounts receivable (AR),” Wnek said. “AP automation cuts that line item completely, reducing costs anywhere from 40-95%.”

Additionally, by reducing manual interventions in financial processes, automation may decrease opportunities for certain types of fraud.

However, the adoption of these technologies has its challenges.

“The two biggest barriers to digitizing AP and AR adoption are cost and complexity,” Wnek said. “But these barriers are easily alleviated when businesses consider the return on their investment compared to outsourcing customer support and finance processing.”

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The U.K.-based group announced the effort Monday (Sept. 2), noting it had recruited several tech and finance giants to its cause, including Amazon Web Services, Mastercard, Lloyds Bank, Revolut and Santander.

Also joining the group are regulators such as the Financial Conduct Authority (FCA) and the Payment Systems Regulator (PSR), with the goal of finding new ways to protect businesses and consumers from fraud.

“Digital verification is considered a key step in mitigating economic crime,” CFIT said in a news release provided to PYMNTS. “An enhanced digital identity for businesses that can be shared and understood across institutions and sectors would help thwart fraudsters and create a more secure economy.”

The group aims to offer standardized, verified information about a business “that is interoperable with other financial systems for data cross-referencing, enhanced authenticity checks and additional fraud detection tools,” the release added. 

Meanwhile, Lloyds Bank, NatWest Bank and Monzo will work together on a proof of concept that tests the impact of a digital corporate ID, “including a reduced scope for accounts to be offered to potential criminals,” CFIT said. A report with recommendations on how British institutions could implement a digital verification solution is expected in March of next year.

In other fraud prevention news, PYMNTS spoke recently with Max Spivakovsky, senior director of strategy and operations, global payments risk management and onboarding at Galileo, about the tightrope banks walk as they provide digital services and payments choices to their end customers while protecting against scammers and cybercriminals.

He said this balancing act requires financial institutions (FIs) to take both proactive and reactive approaches, while also employing technological tools, as they defend themselves while creating a personalized, convenient customer experience.

“The legacy solutions just don’t work anymore,” he told PYMNTS. “Leveraging a single tool used to be the ‘paramount’ strategy of fraud mitigation years ago, but now it’s just not applicable. … The FIs must think about fighting fraud with a holistic perspective.”

The holistic approach can pay dividends while protecting banks from financial losses and harm to their reputation, he said.

“The client experience drives the engagement, and utilization of [banking] apps and programs,” Spivakovsky added.

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Garrett Laird, director of product management at Amount, a digital origination and decisioning SaaS platform powering consumer and small business deposit account opening and loan origination, told PYMNTS that many financial institutions (FIs) don’t reconsider their anti-fraud methods until it’s too late.

“You may not have realized it yet,” Laird said, “but they’re going to hit you.” And, he observed, “the fraudsters are jerks — and they like to hit you on holidays and on weekends, at two in the morning.”

The conversation was part of the “What’s Next in Payments” series focused on protecting the perimeter of various organizations from cyberattacks and hacks — keeping fraudsters out while letting good customers in and letting them transact with ease and speed.

Working with banks and credit unions, and helping them originate credit products digitally, said Laird, means that decisioning, pricing, fraud and verification are all key — and simultaneous — considerations that must be handled in real time. For a bank, when a new application shows up, and someone’s opening a new deposit account or applying for a loan or credit card, well, if a fraudster does manage to get through, the impact can be serious.

A single account, he said, can act as a “gap” or a “loophole that enables a broader group of criminals to take advantage — and fraudsters are notorious for looking for banks’ “soft spots.” Thus, a single application gives way to waves of hundreds of other applications all seeking to provide an entry point for a scam or breach.

“We’ve been direct lenders ourselves,” he said, in speaking about his platform’s functionalities, “and we have built technology that we ourselves have used, and we feel confident about giving to other financial institutions and helping them launch new products.”

Tech-Enabled Onboarding

A tech-enabled onboarding experience, said Laird, underpinned by artificial intelligence (AI) and machine learning, can not only beef up security but also foster a good customer reaction so that legitimate relationships prove sticky and long-lived.

“It all leads to better conversions when you keep your customers happy,” said Laird, rather than losing that same would-be customer to the FI that offers a relatively better user experience.

He noted there are several data sources that can be used to glean insights into emails, password, linked bank accounts and uploaded documents all in the service of identity verification.

“There’s a waterfall that we can put applicants through,” he said. “Suppose we’ve just discovered a fraud ring and they’re really good at forging documents and they’re beating some [of an FI’s] controls. “We can put an extra layer of friction in their way,” he said, “escalating to manual review queues so the fraud operations teams can put ‘eyes’ on how that fraud ring is evolving … and not getting in the front door in the first place.” AI, he said, helps with third-party fraud models to help detect fraudulent applications, representing another tool in the (rules-driven) anti-fraud toolbox.

“We’ve sought to be proactive about having the right data and processes in place to make decisions in an intelligent way,” he said, adding that “it’s not just about keeping out the ‘bad,’ it’s about letting the ‘good’ in and making things as painless as possible for them.”

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A recent PYMNTS Intelligence report, “Instant Impact: AI’s Role in Advancing Real-Time Payments,” in collaboration with The Clearing House, explores the evolving landscape of real-time payments and the critical role of AI in addressing associated challenges. It explores how AI technologies are integrated to streamline fraud detection, enhance customer experiences and accelerate the broader acceptance of real-time payment systems. 

Real-Time Payments Face Challenges

Real-time payments offer significant benefits, such as instant transaction completion and user authorization, but their adoption is impeded by perceived security risks. One concern is a heightened vulnerability to fraud, given the immediacy and irreversibility of these transactions.

According to a recent survey, 44% of organizations list increased fraud risk as a major obstacle, just behind system development issues. Manual anti-money laundering (AML) checks exacerbate this challenge, with 75% of financial institutions relying on outdated, labor-intensive processes. This reliance contributes to delays and perceived risks. There is growing recognition, however, that integrating AI could alleviate these issues, making real-time payments more secure and efficient.

AI Balances Speed and Security in Payments

Balancing rapid transaction processing with effective security is a significant challenge for payments providers, but AI is emerging as a key solution in this area. By automating identity verification and fraud detection, AI can reduce onboarding times, from more than 11 minutes to less than 8 minutes by 2028, translating to a 30% reduction. This efficiency not only improves customer satisfaction but enhances security by detecting fraudulent activities more accurately.

AI-powered algorithms analyze transaction patterns, identify anomalies and reduce false positives, leading to more accurate fraud detection and a smoother customer experience. PYMNTS Intelligence found that FIs are optimistic about AI’s role in managing these trade-offs effectively. 

FIs Adopt AI to Accelerate Fraud Detection

FIs are increasingly turning to AI to enhance their fraud detection capabilities. The adoption of AI and machine learning (ML) technologies is transforming how transactions are monitored and secured. A significant 94% of payments professionals view AI primarily as a tool for improving fraud detection. AI’s predictive analytics capabilities help identify potential fraud by analyzing user behavior patterns and transaction anomalies. 

Beyond fraud detection, AI is used for personalized customer service and operational efficiencies. A 2023 FICO survey found that 77% of customers expect FIs to leverage AI for better fraud prevention, underscoring the growing demand for advanced security measures. AI’s ability to provide real-time alerts about suspicious activities further underscores its critical role in the future of secure and efficient payments.

AI is transforming real-time payments by improving transaction speed and accuracy while addressing security and fraud concerns. This advancement paves the way for wider adoption of real-time payment systems. As AI technology evolves, it promises to further enhance both the efficiency and safety of financial transactions. 

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JPMorgan Chase disclosed the CFPB’s investigation of the peer-to-peer (P2P) payment app on Friday (Aug. 2) in a filing with the Securities and Exchange Commission (SEC), and other large banks are expected to make similar disclosures soon, the Wall Street Journal (WSJ) reported Wednesday (Aug. 7), citing unnamed sources

The CFPB’s probe is focusing on whether banks are doing enough to verify the identity and background of deposit-account customers and to shut down accounts controlled by scammers, according to the report.

In JPMorgan Chase’s filing, the bank said that it is responding to inquiries from the CFPB, regarding transfers of funds through Zelle.

“In connection with this, the CFPB Staff has informed the Firm that it is authorized to pursue a resolution of the inquiries or file an enforcement action,” the filing said. “The Firm is evaluating next steps, including litigation.”

Wells Fargo had previously disclosed that “government authorities” are asking about Zelle, according to the WSJ report.

Zelle is owned by a consortium of seven banks — including JPMorgan Chase, Wells Fargo and Bank of America — and is run by network operator Early Warning, per the report.

Early Warning told the WSJ that it has put countermeasures in place and that 99.5% of Zelle transactions are completed without reports of fraud.

On Monday (Aug. 5), Senator Richard Blumenthal, D-Conn., issued a press release and the text of a letter to CFPB Director Rohit Chopra in which Blumenthal called on the regulator to investigate the dispute resolution practices of Early Warning and the three banks that collectively represent 73% of all Zelle transactions: JPMorgan Chase, Bank of America and Wells Fargo.

“I further urge you to take appropriate action to ensure that these institutions fully and promptly address consumer reports of fraud, as required by law,” Blumenthal said in his letter to Chopra. “If your investigation finds that an institution has violated the Electronic Fund Transfer Act ‘knowingly and willfully,’ I encourage you to take the strongest appropriate action.”

Fifty-one percent of Americans use P2P apps like Zelle and Venmo for quick and easy money transfers, but concerns about fraud are casting a shadow over the growth of these services, according to the PYMNTS Intelligence and The Clearing House collaboration, “P2P Payment Potential: Promoting Convenience While Protecting Consumers.”

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The collaboration, announced Tuesday (July 23), is aimed at protecting financial services companies from check fraud.

“Check fraud is a growing and concerning area of financial crime — we know banks and financial institutions are experiencing a rise in reports and are in need of more advanced tools that can tackle the issue,” Barry Cohen, CEO of OrboGraph, said in a news release.

“Combining our expertise with Featurespace will enable us to deliver a more robust and comprehensive fraud detection solution, helping financial institutions to stay ahead of increasingly sophisticated check fraud schemes,” Cohen added.

According to the release, the partnership will involve Featurespace and OrboGraph integrating their fraud-detection services to better identify and prevent fraudulent check activities.

“By bringing together the two technology platforms, financial institutions will be empowered with a single solution that will enhance detection of fraudulent checks and reduce false positives, thereby improving operational efficiency and customer experience,” the release said.

The release pointed to data from the Financial Crimes Enforcement Network showing that check fraud is becoming more prevalent compared to other types of fraud, accounting for more than a third of all fraud at depository institutions last year.

And as reported here in March, The Federal Reserve Bank of Boston has estimated that there had been 680,000 reports on check fraud in 2022, almost double what they reported in 2021 — with losses in 2023 estimated to come to around $23 billion.

“The criminals also take advantage of ‘float,’ the days between when a check is accepted at a bank or business and when funds are withdrawn from the checking account. By the time the fraudulent check is detected by the account holder, the thieves are often long gone,” the Fed said in a blog post.

Among the solutions recommended by the Fed: “Whenever possible, switch to secure electronic payment methods.”

Meanwhile, PYMNTS spoke earlier this with Featurespace founder Dave Excell, who warned of the increasing prevalence of scams as scammers discover new tools.

“Unfortunately, the amount of scams and the prevalence of them has continued to increase, as there are new tools available to scammers … to victimize vulnerable populations,” he told Karen Webster as part of the “What’s Next In Payments” series.

Among the new threats is the rise of job-related scams, which have jumped 118% year over year, according to data from the Identity Theft Resource Center. These scams often prey on job hunters by pretending to be legitimate employment agencies or recruiters.

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