Global talent shortages reached a 16-year high in 2022 as 75% of employers reported difficulties finding talent. According to the U.S. Chamber of Commerce, “We have a lot of jobs, but not enough workers to fill them. If every unemployed person in the country found a job, we would still have 4 million open jobs.”
Against this backdrop, anti–money laundering (AML) teams within banks and financial institutions are overburdened, overstressed, and under-motivated. These stressors have been compounded tenfold, especially as overburdened teams now must deal with pressures from Executive Teams and Boards as sanctions governance has become a boardroom agenda item. As the large-scale employee turnover continues, the staff who remain are becoming even more overburdened, stressed, and dissatisfied.
According to WorkFusion CEO Adam Famularo in a recent Forbes article, “AI is currently solving this problem [talent shortage] by creating a digital workforce. Organizations can ‘hire’ AI to do highly skilled work, freeing their employees to do what humans do best—create and innovate.” For organizations in highly regulated industries, AI can provide reasoning around why it made a decision and provide detailed documentation ensuring stronger audit trails. In this way, AI has the promise to help us all do our jobs better.
No, AI will not replace workers
In a recent webinar entitled, Work.AI Brings Humans in the Loop, WorkFusion’s VP of Product Management, Vasil Remeniuk, and Maria Sheremet, Product Manager at WorkFusion, described why humans will always be needed when an organization uses AI-driven tools, highlighting three main reasons.
First, AI portals (I.e. ChatGPT, Google AI) are fantastic for delivering general knowledge. But when it comes to domain-specific knowledge, human experts will continuously add domain-specific knowledge that is required to address fast-changing circumstances. For example, subject matter experts who understand anti-money laundering (AML) compliance have been in high demand in the financial services industry since thousands of sanctions arose as a result of the Russia invasion of the Ukraine in early 2022. Without ongoing input of human domain-specific knowledge, AI would be unable to handle AML compliance processes on its own.
Second, human oversight is necessary to oversee the output generated by AI tools or machines that leverage AI. For example, Evelyn, one of WorkFusion’s flagship AI Digital Workers is the digital embodiment of a Sanctions & Adverse Media Screening Analyst. Evelyn is pre-trained as an expert in BSA/OFAC requirements and performs exceptional sanction watchlist screening, PEP and name sanctions screening, plus adverse media monitoring. “She” can automatically review and disposition alerts from various sanctions screening tools as well as search and analyze adverse news with great speed. Despite having both general knowledge and domain-specific expertise, Evelyn still requires humans to review her most critical findings – the identification of “true positive L1 alerts” which a financial institution needs to act upon to remain in compliance. Certainly, Evelyn is highly effective at automating the review and disposition of the overwhelming majority of alerts she receives from sanctions screening tools. But her ability to collaborate with a real person via HITL (human in the loop) is necessary to 100 percent accurate alert adjudication and dispositioning. In the end, as Vasil says in the webinar, “HITL remains a critical element of any successful AI structure to ensure AI remains accountable and effective.”
See how AI with HITL really works
To gain more clarity into how exactly HITL works in AML compliance operations, Maria demonstrated AML compliance as a workforce application in which AI Digital Workers and humans interact. In the brief webinar, Maria showed how humans and AI collaborate in a flexible and streamlined way to handle email-based customer interactions for KYC (know your customer) operations as well as massive volumes of alerts related to adverse media monitoring for KYC. After watching for just a few minutes, you will appreciate how powerful – yet simple – are the meaningful ways that AI Digital Workers and humans come together to deliver impressive results, at scale.
To help you delve even further into collaboration between AI Digital Workers and humans, WorkFusion presented another recent webinar entitled Putting AI to Work with Adverse Media Monitoring. In it, Art Mueller, WorkFusion VP of Financial Crimes, and Anna Thompson, Senior Product Manager at WorkFusion, provided detailed insights into AI Digital Worker Evelyn and her adverse media monitoring skills that protect an organization from risky client relationships by reviewing both ad hoc adverse media results as well as alerts from adverse media screening applications.
From an HITL perspective, the webinar names financial institutions that have used Evelyn for adverse media monitoring (AMM) and demonstrates how they leveraged AI with HITL (inherent within Evelyn) to increase team capacity and free up analysts to work on higher-value projects.