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Online EducationCompliance AllianceABA Banking Journal: ABA launches online Treasury check verification platform
The new tool provides a centralized point of access to the TCVS for ABA member banks at aba.com/TCVS. The system allows banks to verify the validity of all government-issued checks, including Social Security benefits, tax refunds, federal paychecks and government stimulus payments. According to the White House, Treasury checks, or checks issued by the federal government, are 16 times more likely to be subject to fraud. By using TCVS, ABA member banks can obtain check issue information and confirm a check’s legitimacy, significantly reducing the likelihood of fraud. ABA’s new platform will also allow ABA members to confirm payee name, which is a feature not available through the Treasury’s existing public-facing page. “We’re excited to offer this new tool in the banking industry’s ongoing fight against fraud, and we appreciate the Treasury Department’s support for this new platform,” ABA President and CEO Rob Nichols said. “Banks accessing the TCVS through ABA will be able to spot potentially fraudulent government checks in real-time, which will help protect taxpayers, banks and the federal government from millions in fraud losses.” By providing a centralized point of access on aba.com, ABA member banks will no longer have to build their own TCVS payee verification capability by integrating the TCVS Application Programming Interface with their own systems, a process that can take months to complete. “This new ABA platform is a game-changer for banks across the country looking to combat check fraud,” said Robert Voets, vice president, financial crimes investigations, Ion Bank. “Our customers bring us government checks every day, and thanks to this new tool, we will be able to quickly and easily verify critical information including dollar amount and payee. This is a major step forward in our fight against fraud.” This tool is the latest in a host of initiatives undertaken by ABA to help banks of all sizes respond to the growing threat of check fraud, including the ABA Fraud Contact Directory, its #PracticeSafeChecks and #BanksNeverAskThat consumer education campaigns, collaboration with the U.S. Postal Inspection Service on check washing and check theft scams, as well as business check fraud, ABA’s members-only Check Fraud Toolkit, and a Check Fraud Symposium in March 2025 featuring large, midsize and small ABA member banks, as well as other key stakeholders, including government representatives and vendors. Back to TopABA Banking Journal: Will fraud prevention ever be autonomous?Anti-fraud systems are learning to anticipate fraud rather than merely react to it. Better anticipatory abilities inch systems closer to full automation.
Just as self-driving cars integrate multiple sensors (cameras, lidar, radar) to build a comprehensive view of their physical environment, modern fraud prevention systems likewise must synthesize diverse signals – device intelligence, behavioral patterns, transaction data and digital footprints – to understand the full context of any given interaction and to enable defense in depth to protect against shifting fraud threats. As the volume and complexity of transactions and digital interactions surge, navigating these increasingly intricate ‘digital highways’ demands greater sophistication and calls for more streamlined fraud prevention methods. This begs the question: Will fraud prevention ever achieve full autonomy? Today’s human-led defenseLike autonomous vehicles navigating through unpredictable terrain, fraud prevention systems must be agile, able to adjust to new threats in real time and learn from each interaction to improve. With the integration of AI and ML, modern anti-fraud solutions quickly analyze vast datasets, recognize fraudulent activity patterns and predict potential risks before they materialize. Currently, most fraud prevention solutions deploy reactive rules-based detection systems with manual investigations and human-dependent processes that enforce operations at a limited scale. But as technology advances, the line between automated decision-making and human oversight will blur, creating a hybrid model where machine efficiency is enhanced by human intuition and expertise. Operations currently limited by human bias, manual reviews, basic rules scoring engines and high costs will give way to assisted intelligence, where machine learning will augment anti-fraud measures with guided investigations and highly customizable risk-scoring capabilities. Moving through new terrainWe’re at an inflection point. Traditional rules-based fraud prevention is analogous to having a human driver following a rigid set of if-then instructions: “If you see a red light, then stop.” This worked when the “roads” of the digital economy were more straightforward and less crowded. But the current fraud landscape is more like navigating rush hour in a major city during a storm – the conditions are complex and dynamic, and require split-second adaptability. The emergence of large language models and AI agents is accelerating the shift toward autonomy. On the fraudster’s side, these advancements fuel adversarial systems capable of adapting in real time, bypassing traditional defenses and coordinating sophisticated, multi-vector attacks. Fraudsters are increasingly leveraging AI to mimic legitimate behavior, manipulate systems and scale their operations with precision. Looking to a future state of full autonomyFully autonomous fraud prevention remains a lofty goal, hindered by significant challenges. While AI has transformed the landscape, it can still struggle to detect subtle, complex fraud schemes that require nuanced contextual understanding – a domain where human experts continue to excel. The trajectory, however, is clear: Fraud prevention is evolving beyond binary risk decisions into the realm of sophisticated risk orchestration. Modern platforms are becoming AI-powered traffic management systems that can simultaneously monitor millions of transactions, predict potential fraud attempts and dynamically adjust security measures in real-time. This shift from static, rules-based frameworks to dynamic, context-aware models that continuously evolve represents the future. These predictive systems will not only enhance scalability but also free human experts to tackle strategic challenges that demand nuanced judgment and creativity. Automation will amplify efficiency, but human oversight will ensure compliance, reduce bias and address the ethical complexities that AI alone cannot manage. Together, they form a hybrid model – a seamless partnership where technology augments human insight and humans guide the adaptation of technology. Tamas Kadar is CEO of SEON, a fraud-prevention firm. Back to TopABA: Executive Order 14306, President Trump’s Executive Order on CybersecurityJune 24, 2025 | John CarlsonOn June 6, 2025, President Trump released Executive Order 14306 which outlines the Administration’s policies on cybersecurity. Trump’s EO largely builds on two previous executive orders issued by the Biden and Obama Administrations by promoting secure software development, enhancing internet routing security, preparing for quantum computers, and continuing to rely on the National Institutes of Standards and Technology (NIST) to interface with industry. However, the EO makes several noteworthy changes, including removing a section on combating cybercrime and fraud, narrowing the focus on artificial intelligence, modifying the malicious cyber-enabled activities sanctions program, extending deadlines for US government actions, and removing some mandates. The EO calls out the threat of nation state adversaries, stating that "The People's Republic of China presents the most active and persistent cyber threat to United States Government, private sector, and critical infrastructure networks, but significant threats also emanate from Russia, Iran, North Korea, and others who undermine United States cybersecurity."
CISA News: Solar Company Sues Google for Giving Damaging Information in AI OverviewsWhen an AI "hallucination" becomes defamation.June 19, 2025 | Frank Landymore
"This lawsuit is not just about defending our company's reputation; it's about standing up for fairness, truth, and accountability in the age of artificial intelligence," Nicholas Kasprowicz, general counsel for the solar company, Wolf River Electric, said in a statement. First filed in a state court in March, the lawsuit was transferred to a federal court this week after Google filed for a removal, the Minnesota Star Tribune reported. It's generally uncharted legal territory. Can a company be held responsible when its AI spreads harmful misinformation? If so, it could represent a huge inflection point as AI companies have long tried to duck liability for the outputs spouted by their large language models. "This might be one of the first cases where we actually get to see how the courts are going to really dig down and apply the basic principles of defamation law to AI," Ari Cohn, lead counsel for tech policy at the Foundation for Individual Rights in Education (FIRE), told Politico. What Google's AI allegedly made up is clearly serious enough to put customers off, and appeared when searching "Wolf River Electric lawsuit" on the search engine, which is a plausible query for a potential customer looking into the background of someone they're about to do business with. Per the suit, as quoted by the Star Tribune, the AI feature confidently fibbed that Wolf River Electric was facing a lawsuit from Minnesota Attorney General Keith Ellison for "deceptive sales practices," like lying to customers about savings, and tricking homeowners into signing contracts with hidden fees. Ever the diligent researcher, the Google AI cited four links to back up its claims: two news articles (including at the Star Tribune), a statement from the state's AG, and Angie's List. None of these made any mention of a lawsuit against Wolf River. Per Politico, some of the links mentioned that other solar companies were being sued, but there was nothing about the plaintiffs. Errors like these are well documented: Google's AI is easily tricked into inventing and then elaborately explaining fake idioms, when it's not busy recommending putting glue on your pizza. Google denied the defamation allegations in a filing last week, and brushed off what happened as a harmless mishap. What's losing a few potential customers when they're building amazing AI that's going to save the world? "The vast majority of our AI Overviews are accurate and helpful but like with any new technology, mistakes can happen," Google said in a statement to Politico. "As soon as we found out about the problem, we acted quickly to fix it." When you're not a trillion-dollar monolith, however, lies can be pretty costly. Wolf River said that several of its customers cancelled their contracts — some worth as much as $150,000 — because of what they read in the Google AI Overviews. There's a silver lining, however: all that lost business may be some of the strongest evidence yet for proving AI-related defamation in court. "Wolf River Electric claims they've got the receipts," UCLA Law professor Eugene Volokh told Politico. "They've got what a lot of people who've been libeled have a hard time proving." Also in the solar company's favor is that it likely isn't well-known enough to count as a public figure, Politico noted, meaning that the bar for proving defamation is lower. Wolf Electric doesn't have to demonstrate there was "actual malice" involved, and instead merely needs to show that Google was negligent. It's far from an open and shut case, but it has the makings of a strong one. According to the Star Tribune, Wolf Electric is seeking significant damages of $110 million to $210 million. "No corporation, regardless of its size or market dominance, should be permitted to release powerful AI tools that generate and spread false information without proper oversight or consequences," Kasprowicz said. Back to Top |
The American Bankers Association today launched a new online platform that will enable member banks to easily verify government checks and their payee information through the U.S. Treasury Department’s existing Treasury Check Verification System at no cost.
As fraud prevention races toward unprecedented complexity thanks to advances in artificial intelligence and machine learning, it’s shaping up to mirror the evolution we’ve witnessed with autonomous vehicles – with its mixture of sensors, decisions and actions that exist on a spectrum from human-controlled to fully automated.
