Boston, July 23, 2020 – Financial institutions have invested significant effort and resources to meet their anti-money laundering obligations and have employed thousands to detect and prevent financial crime. But they are still fined by their regulators for falling short of expectations, still struggle with inefficiencies, and still fail to identify new criminal trends and networks. Can artificial intelligence help FIs turn up the heat for criminals at a manageable cost?

This report looks at AI for AML, explores the different techniques and approaches under the AI banner, considers how innovation is solving key issues, and examines some of the operational considerations and challenges that FIs need to overcome to fully benefit from AI. Aite Group conducted 23 interviews with executives from FIs and AML software vendors from around the world from March to May 2020 to inform this research.

This 40-page Impact Report contains nine figures and 11 tables. Clients of Aite Group’s Fraud & AML service can download this report, the corresponding charts, and the Executive Impact Deck.

This report mentions  Abrigo, ACI Worldwide, Acuant, Acxiom, Appway, Arachnys, AU10TIX, AuthenticID, Automation Anywhere, Automation Edge, Ayasdi, BAE Systems, Beam, Blue Prism, Brighterion, Caspian, CGI, ComplyAdvantage, CSI, Daon, DataVisor, Duality, Dragnet Solutions, Early Warning Services, Equifax, Experian, Facebanx, Facepoint, Featurespace, Feedzai, Fenergo, FICO, FinScan, Fiserv, GBG Group, Genpact, GIACT, Guardian Analytics, IBM, ID Insight, ID R&D, iDenfy, IdentityMind, IDology, INFORM GmbH, Intellicheck, iProov, Jumio, Kofax, LexisNexis Risk Solutions, MiTek, Narrative Science, NICE Actimize, OneSpan, Onfido, Oracle, Pegasystems, Pelican, PwC, QuantaVerse, Quantexa, Refinitiv, Samsung SDS, Sanctions Scanner, SAS, Silent Eight, Socure, Thales, ThetaRay, Transmit Security, TransUnion, Trulioo, UiPath, Verafin, Veratad, Veridas, and Wipro.