AI-Powered Money Laundering: A Growing Threat to Financial Integrity
As the golden age of technological development continues to unfold and artificial intelligence (AI) continues to achieve mainstream utilization by businesses and individuals alike, the growth of AI-backed protocols has already contributed to significant improvements in workflow and operational efficiency across the financial realm. With AI now being used by financial institutions to better meet their anti-money laundering (AML) and counter terrorism financing (CFT) requirements, firms are achieving unprecedented levels of detection of financial crime threats, allowing them, along with the regulatory bodies that govern them, to mitigate potential threats before major damage is done. Finance-centric AI-powered solutions analyze vast amounts of data, detect suspicious patterns, and automate key processes like customer due diligence (CDD) and transaction monitoring. This leads to reduced false positives, improved accuracy, and faster response times, ultimately strengthening AML compliance and revolutionizing the sector as a whole, all while cutting costs for financial institutions in the process. Yet even with these advancements, money laundering risks continue to become more pervasive as financial criminals become more technologically adept themselves and seek to exploit new avenues for personal gain. Further, as sophisticated AI models become more easily accessible to the masses, their potential misuse as tools to facilitate financial crimes has remained a key area of concern for regulators and government agencies seeking to thwart further misconduct in this regard. Unfortunately, it appears that this trend may already be developing overseas.
Late last year, top government officials and regulatory authorities in the U.S. warned of the increasing risk that developing technologies can pose to the integrity of the global financial system. In December 2024, the U.S. Treasury Department’s Financial Crimes Enforcement Network (FinCEN) highlighted new and highly-successful fraud schemes being utilized by bad actors centered on “generative AI” acting against American interests with respect to Anti-Money Laundering and Counter Terrorism Financing National Priorities. Recent reports have now indicated that fraudsters and criminal organizations in Europe have begun to leverage artificial intelligence to open both bank accounts and digital wallets with prominent cryptocurrency exchanges, enabling more complex money laundering schemes. According to the Italian financial intelligence unit (UIF), fraudsters have adopted generative AI and deepfake technology to bypass know-your-customer (KYC) checks, creating synthetic identities or hijacking real ones to launder illicit funds. This development, detailed in a June 2025 UIF report, underscores the escalating risks posed by AI in financial crime and the urgent need for advanced countermeasures to allow both banks and crypto exchanges to avoid potential abuse.
Criminals can exploit AI through a number of varying methods: Automating transactions, simulating legitimate business activities, and even going as far as to create convincing online marketplace listings or cryptocurrency trades. By splitting their large illicit sums into smaller, dispersed transactions, fraudsters can generally reduce their visibility to law enforcement, allowing their efforts to continue. Generative AI, which is capable of producing realistic content such as fake IDs, invoices, and phishing emails, amplifies these money laundering threats exponentially given both its ease of employment and their ability to shroud detection for the financial criminals employing them, allowing these schemes to go on without a hitch. On a positive note, the recent UIF report detailed a decline in suspicious transaction reports (STRs) of perceived “minimal value” from 150,000 in 2023 to 145,000 in 2024, with a focus on “higher-quality flagging” across Italy over the last two years.1 However, the report also speaks on negative developments, including a significant rise in this AI-driven fraud dubbed “Frankenstein fraud,” which has largely offset the progress made with respect to targeted crime detection. Under the most common ploys seen within the southwestern European nation, criminals have combined real and fictional personal details, using AI-generated images, videos, and documents to open accounts at banks and cryptocurrency exchanges. These accounts later facilitate the conversion of crypto-assets to fiat currencies, often as part of the layering phase of money laundering, allowing those behind the schemes to make off with funds while avoiding detection by governing bodies and the affected financial institutions themselves until it is too late. According to ACAMS, in some cases, suspects used AI-generated images and videos to open accounts in the names of real individuals without their knowledge, while in others, they have created and used synthetic identities that had no corresponding entry in Italy’s national tax registry.1
The misuse of AI in financial crime demands a robust response. UIF urges financial institutions to fight “fire with fire” by deploying AI-powered detection systems of their own. These systems excel at identifying complex patterns and anomalies in real-time, spotting subtle signs of laundering that traditional methods can miss. When used by FI’s, generative AI can enhance risk assessments by dynamically profiling customers based on transaction history and patterns of behavior, prioritizing high-risk cases. It also automates due diligence, generating comprehensive reports on entities’ financial and legal status, and simulates laundering scenarios to expose system vulnerabilities. Further, the agency has highlighted several key red flags for financial institutions to be mindful of when analyzing transactions for potential suspicious activity. These include geo-locational anomalies, inconsistent IP addresses, and recurring patterns found in KYC data, with identification in this regard helping to pinpoint these coordinated and largely-automated efforts taken by tech-savvy criminal organizations to limit their overall scope across the region and worldwide.
The UIF’s findings in Italy should serve as a wake-up call for the global financial system. Unfortunately for financial institutions continuing the fight against illicit finance however, analysts believe that the negative use of AI to facilitate crime will not be fading any time soon. To counter AI-driven fraud, institutions must continue to strengthen their internal KYC procedures, coordinate their anti-money laundering (AML) and anti-fraud efforts, and continue to leverage the open-source intelligence that is now at their fingertips. Firms should also lean on upgraded processes for identity verification, including use of multifactor authentication (MFA), phishing-resistant programs and live verification checks in which a customer must confirm their identity through real time audio or video to deter the threat of generative AI by criminals. Further, the continued use of advanced transaction monitoring tools and maintaining current regulatory compliance standards in daily practice is also critical. By investing in AI-driven defenses, enhancing due diligence, and fostering collaboration with regulatory bodies and law enforcement, institutions can stay ahead of tech-savvy criminals. The battle against AI-powered money laundering is intensifying, but with the right tools and strategies, it is one that can be won.
Citations
Vedrenne, Gabriel. “Criminals Using AI to Open Bank Accounts, Digital Wallets in Italy.” ACAMS Money Laundering, 18 June 2025.