standards for AML compliance. Continuous communication and collaboration between regulators and operators are essential to align policies, procedures, regulations, best practices, and ultimately reputations.
One key initiative supporting this effort is the National Gambling Intelligence Sharing Group (NGISG), which aims to foster information sharing and investigative collaboration. Comprised of law enforcement agencies from the U.S. and Canada, NGISG facilitates the confidential exchange of intelligence related to cheating groups, emerging methods of fraud, and other criminal activity targeting the gaming sector. While primarily focused on law enforcement, NGISG allows limited information sharing with regulators and industry leaders, helping them adapt AML policies and procedures proactively. Tere is growing interest in expanding this model: non-law enforcement stakeholders, including casinos and regulatory agencies, have proposed creating a separate portal to facilitate broader information exchange. Te NGISG is evaluating this idea and gathering input from a select group of non-law enforcement representatives, with plans to develop guidelines and a test programme.
Gatherings also play a vital role in advancing AML discussions. Gaming Laboratories International (GLI) recently hosted its 25th annual Regulators Roundtable in Las Vegas, which brought together a diverse group of gaming professionals to examine industry trends, illegal gambling, and cybersecurity— each with direct implications for AML compliance. Similarly, the Dowling Advisory Group sponsors an annual BSA/AML Conference emphasising training and knowledge-sharing. Tis event draws experts from across the sector to discuss updates to AML laws, emerging money laundering threats, and practical strategies for developing and maintaining effective AML programmes.
What are some examples of effective AML best practices currently implemented in Nevada’s gambling sector?
While each gaming jurisdiction must tailor its AML policies to fit its unique needs, I believe Nevada has struck an effective balance between adopting industry best practices and enforcing robust regulations through the NGC and the NGCB.
A key regulatory tool utilised by the NGC and NGCB is the Book Wagering Report (BWR) regulation (NGC Reg. 22.061). Tis rule requires gaming entities offering book wagering to report any single wager or combination of wagers exceeding $10,000 within a 24-hour period, as well as any payout or
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series of payouts above that threshold. Tese reports must include the individual’s identifying information for submission to the NGCB. Much like the federal Currency Transaction Report (CTR), the BWR helps regulators detect suspicious activity or patterns that could indicate potential money laundering.
Beyond regulatory mandates, the NGCB leverages external tools to enhance its AML efforts. One such resource is Visual Casino, a software platform that disseminates information on suspicious or potentially criminal activity observed in casinos nationwide. Te database includes an individual’s name, photograph, and a brief activity description.
Additionally, NGCB embeds agents in joint federal task forces alongside the Drug Enforcement Administration, the U.S. Department of Homeland Security, the Internal Revenue Service, and the Federal Bureau of Investigation. Tese collaborations provide the NGCB access to broader intelligence networks and investigative capabilities, significantly strengthening its ability to identify and respond to money laundering threats.
Which emerging technologies show promise in strengthening AML efforts, and how can they be integrated responsibly?
Artificial intelligence (AI) could play a pivotal and growing role in advancing AML efforts within the gaming industry. Much like in other sectors, AI offers transformative potential by analysing large volumes of betting and financial data to identify suspicious activity—such as unusually large bets, rapid withdrawals, or behaviour that deviates from a customer’s typical pattern. AI may also enhance customer due diligence by verifying identities through facial recognition, document validation, and behavioural biometrics, while continuously assessing risk based on transaction history, source of funds, and geographic location.
In the SAR area, AI can streamline the process by automatically generating reports, prioritising alerts based on risk levels, and significantly reducing false positives—allowing investigators to focus on credible threats. Natural language processing further strengthens compliance by scanning open- source data, including sanction lists, news coverage, and social media, to flag individuals potentially linked to criminal or politically exposed activity.
Additionally, AI supports real-time monitoring across
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