AI is transforming financial crime compliance
While 86% of compliance, operations, risk and IT professionals at banks and non-banking financial institutions (NBFIs) surveyed said they would increase spending on AI and ML over the next two years, a 93% of respondents said that instead of using automation to reduce staff, they would focus that extra capacity on strategies to manage risk and grow the business, according to WorkFusion.
“Leveraging AI-enabled automation technology to enhance efficiency and productivity can help alleviate capacity shortfalls in financial crime operations,” said Neil Katkov, PhD, Director – Risk at Celent. “And as technology drives improvements in productivity, compliance departments can better support strategies to manage risk and add value.”
Employee shortages in financial crime compliance
70% of banks and NBFIs face capacity challenges in their compliance operations—meaning that many departments that are “staffed adequately” face at least occasional capacity shortfalls.
38% of firms fill capacity gaps by calling on more senior personnel to pitch in. Smaller organizations are more likely to call on their compliance officers to help—44% of organizations with assets under $50 billion rely on senior personnel to close gaps.
63% of firms report that it takes four months or longer to fill experienced compliance analyst roles. Only 10% of firms can find experienced analysts in less than one month. Once hired, onboarding and training extends the time for fully replacing lost staff. Half of firms say it takes over four months to ramp-up new hires, with only 17% able to do so in a month.
53% say that employee retention issues put increased workloads on the remaining staff. About the same proportion of firms said that these staffing challenges led to longer cycle times for alert investigation, directly impacting compliance operations.
Efforts to lighten analyst workloads in compliance departments
Efforts by compliance departments to reduce analyst workloads include screening analytics, staff augmentation, specialized consultants, and technology levers.
If organizations had more capacity, 35% of respondents said they would improve risk monitoring by increasing the frequency of KYC reviews, 57% would use the additional capacity to pursue more revenue: 31% would work to shorten cycle times for account opening, and 26% would work to increase the firm’s risk appetite to take on new customers. Only 7% would look to layoff staff.
List management techniques—which include de-duplication, entity consolidation, and targeted application of lists to specific transaction flows or customer segments—have been used by 75% of firms and represent the top approach for banks, savings/credit unions, and fintechs alike.
Good person/bad person rules were the second most common approach taken by banks (48%); staff augmentation was second for savings/credit unions; and consultants were second for fintechs.
Throwing bodies at the problem is the least effective approach, with 75% of organizations getting 25% or lower uplift.
Organizations boost AI and ML investments
86% of organizations responded that they will increase their spending on AI and ML over the next two years, 45% of those said they will increase AI spending significantly.
Regulatory action would motivate 75% of organizations to adopt digital workers or similar advanced technology to improve compliance operations. Following regulation, staffing challenges were cited by 65% of respondents as a compelling reason for automation technology.
“AI isn’t coming for your jobs, is the huge takeaway from this report,” said Adam Famularo, CEO of WorkFusion. “AI is proving its value to the banking and NBFI industries by playing a vital role in how resource-strapped organizations can keep pace with financial criminals with automation tools like Digital Workers. Compliance officers, no matter the size of the organization, should not have to pitch in to manage L1 AML workloads when the automation exists to help increase team capacity and improve compliance.”