Why AI is an Essential Ingredient in a Successful AML Program

Why AI is an Essential Ingredient in a Successful AML Program


The World Bank estimates that the annual volume of global money laundering exceeds $3.5 trillion (a figure that equates to nearly 5% of global GDP). Given that less than 1% of money laundering activity is actually detected by the banks and financial authorities, the realm of regulatory compliance has grown exponentially in recent years in an effort to correct these limitations. New regulatory technology (RegTech) continues to be developed and modified to meet the demands of organizations large and small while also allowing them to better navigate pervasive risks to financial integrity, including destabilizing financial activities. In this same respect, the leadership of many of the world’s top financial powers are consistently working to improve their respective anti-money laundering (AML) and counter-terrorism financing (CFT) controls to protect covered financial institutions and their respective economies. The financial burden associated with such changes for providers however has continued to grow during the AML crusade initiated in the early 2000’s, as banks have had to adjust on the fly in order to stay compliant with complex and ever-changing regulations. The Covid-19 pandemic has further compounded these issues, as the abrupt change in the traditional work environment coupled with new financial crime threats emerging as part of the mass shift to remote operations have left banks reeling in their efforts to fill a growing void.

            Many compliance departments are already overwhelmed with their respective workloads as a result of emerging legislation. Unfortunately there appears to be no relief in sight however, as analysts have estimated that roughly 300 million new regulations are expected to be implemented throughout the world within the next decade.2 And non-compliance is simply not an option today, as large scale penalties for AML slip-ups or deficiencies can all but force many firms to shut their doors altogether. For context, enforcement actions against financial institutions (and their employees) totaled $5.4 billion in 2021 with the average fine coming in at approximately $34.4 million.1 With both costs and fear of repercussions mounting, many have begun to turn to the adoption of potent technologies, including artificial intelligence (AI), to stay ahead of the game and ensure comprehensive coverage in this regard.

            Though not nearly as fantastical as it is portrayed on the big screen, AI has many practical real-world applications that have begun to shape many major industries contributing to the global economy (healthcare, retail, manufacturing, etc.).  The integration of artificial intelligence (AI) into daily workflows across the financial sector has revolutionized the way banks manage their compliance responsibilities. When utilized as part of the modern compliance solution, AI has the ability to process huge volumes of pertinent financial data quickly and accurately. Today’s financial institutions must screen their customers against a variety of published sanctions lists and blacklists, as well as screening for criminal history, political ties, and more. On top of that, they need a system capable of scanning through this wealth of information without creating unnecessary alerts for false positives that will ultimately require manpower for final clearance. AI processes can sift through these possible matches nearly automatically, while making ‘smart’ decisions with near pinpoint accuracy, subsequently eliminating the vast majority of false-positive alerts without any manual input required.

                AI and machine learning capabilities replace many of the now obsolete and costly manual labor processes synonymous with the customer verification process. Global RADAR has invested heavily into AI-backed processes in recent years, culminating in the development of their own sophisticated AI used for screening and risk rating, eliminating countless hours of wasted manpower and allowing our partners to thrive in spite of growing demands and threats. Global RADAR’s newest AI is heavily backed by advanced analytics directly extracted from real-world financial data. The technology utilizes “fuzzy logic” based on phonetics in addition to exact match processes using the Metaphone 3 algorithm, each of which helps to eliminate false positives while identifying direct matches more accurately. Global RADAR’s advanced anti-money laundering screening initiatives cut false-positive alerts down significantly, easing the burden on compliance departments of some of the world’s most renowned financial service providers while allowing precious resources to be re-allocated to other areas of their daily operations.

The AI-powered platform has a wide range of features to eliminate both human error and unnecessary manual labor. These include:

  • Screening against OFAC sanctions, adverse media, and PEP lists
  • Search Corporate Registries for ownership details
  • Customizable negative news and adverse media searches
  • Exclude search terms to reduce false positives
  • Real time screening through manual data entry or batch processing
  • Automatic information extraction and screening from PDF files
  • False positive suppression
  • Automated Daily list updates
  • Real-time screening of transaction details for trade finance, lending, funds transfers and SWIFT messages
  • Integration with the email system for automatic notifications on new matches
  • Search history and comprehensive audit trail detailing all interactions
  • No deployment needed. Sign-up and search!
  • Fully responsive, available for mobiles and tablets or via API
  • Export, share, and print search results directly from mobile devices

With the technological revolution in full swing across the global financial sector, banks can no longer ignore the fact that machine learning capabilities are the way of the future in finance. All told, smarter systems mean less busy work, less pressure, and less stress for compliance departments and other components of the modern financial institution.


  1. Hodge, Neil. “Report: Financial Services Fines Drop 49 Percent in 2021.” Compliance Week, 10 Jan. 2022. 
  2. Schorr, Joe. “How AI Can Improve Regulatory Compliance: Logicgate Risk Cloud.” LogicGate, 18 Mar. 2021. 

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