• Automating rules : While a TMS rule created by AML compliance team members or suggested by the industry can be the right one for the job , advanced technology can confirm or recommend rulemaking . Advanced systems complement TMS rulemaking by determining when a rule is ineffective or indicating when an algorithmic approach or a neural network should supplement rule-based TMS .
• Automated reporting : As it has been broadly demonstrated of late by ChatGPT and Google Bard , AI technologies can devise clear narratives based on the data examined . By auto-compiling summary descriptions , AI-enabled AML solutions can speed reporting when explaining why an alert was cleared . This capability also increases the consistency and accuracy of reporting across AML compliance teams .
• Achieving resilience and agility : Adopting advanced automation allows AML compliance teams to save time and gain powerful insights to reduce inefficient , manual tasks and make better operational decisions .
The primary goal for financial crime prevention professionals is to select one or more solutions that address the biggest opportunities for efficiency and effectiveness gains in current processes and systems . Each solution added to the mix comes with its own change management , training , vendor management and other efforts necessary for a successful implementation , so select as few as necessary to meet goals . Further , avoid solutions that overlap in their functionality and ensure the workflow you are creating for AML investigators is well understood . The fewer solutions needed to master and access daily , the more efficient they will be in their work .
Concerning training FIs ( including smaller FIs with limited budgets ) on new technology , the solution that is ultimately selected should not require much education ; it should be intuitive and fit into existing processes and risk priorities . For example , the AML RightSource Financial Crime Investigation Report ( FCIR ) can be read by investigators of almost any level of experience and immediately make them more efficient by presenting supporting documentation needed to analyze cases efficiently and to create suspicious activity reports when indicated .
Conclusion
Increasing risks and regulatory expectations and a tight labor market are challenging financial crime compliance leaders to improve the productivity of their teams . With AI-enabled AML technology , FIs can automate compliance operations , helping teams become more efficient and channel investigators ’ talents to the most complex alerts .
This combination of advanced technology and an efficient compliance team provides FIs with the awareness and the tools to continually combat risk more effectively and overcome AML compliance disruptions .
Phil McLaughlin , chief technology officer , AML RightSource , 1
“ Opportunities and Challenges of New Technologies for AML / CFT ,” Financial Action Task Force , July 2021 , https :// www . fatf-gafi . org / en / publications / Digitaltransformation / Opportunities-challenges-new-technologiesfor-aml-cft . html #
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