Upping AML Effectiveness at Mid-sized Banks in 2021

Up to $2 trillion - or 5 percent of the global GDP- is laundered every year, according to UN estimates, and data indicates that global crises like COVID-19 present a ripe environment for spikes in financial crime. The Association of Certified Anti-Money Laundering Specialists (ACAMS) warned in August of 2020 that money laundering activities were expected to return to pre-pandemic levels, “but in different forms that will exploit financial insecurity, unemployment and other anxieties.”

Historically, mid-sized banks have historically borne a disproportionate compliance burden compared to larger banks due to fixed compliance costs. Smaller financial institutions must comply with the same anti-money laundering (AML) regulations with fewer resources to fight financial crime – in terms of budget and headcount – than their larger counterparts. Money laundering also poses the risk of regulatory fines and reputational damage to mid-sized banks. Additionally, current economic pressures are forcing banks to optimize costs.

However, robust anti-money laundering systems are needed now more than ever as financial criminals increasingly turn their attention to smaller and mid-sized banks. Back in 2014, the unit chief of the financial crimes section of the Federal Bureau of Investigation’s criminal investigative division noted money laundering was shifting to smaller financial institutions. This observation has borne out as larger banks have upped their AML defenses in the wake of some high-profile money laundering scandals, leading even more criminals to shift their efforts to smaller banks.

Fortunately, mid-sized banks have an opportunity to strengthen their money laundering defenses while managing compliance costs by evolving away from traditional, costly and cumbersome anti-financial crime programs and toward advanced technologies. Here are a few of the technologies reshaping AML effectiveness at mid-sized banks:

• Cloud. While the financial services industry has historically been slow to migrate to the cloud, this shift has accelerated in recent years, especially in light of the pandemic. From an operational perspective, a cloud AML platform eliminates the need for additional hardware and middleware and reduces implementation costs.
  
  Additionally, with the cloud, there are no unpredictable costs of managing, patching and updating software and hardware. Instead, updates can be implemented across a bank’s network quickly, helping banks adapt to changing criminal behaviors and comply with new regulations. Cloud technology also supports disaster recovery and high availability across regions, which is especially important in today’s distributed work environment.
  
  

• Robust data modeling. Some of the most modern AML systems enable a common data foundation that can unite inputs from any transaction system and any data source, including third-party data feeds and fragmented data. This gives banks the ability to process and analyze large volumes of data from both internal and external sources. From there, banks can leverage the detection data pipeline for discovery and modeling of new criminal patterns. Additionally, cloud-based AML solutions give banks access to an ever-growing catalog of ready-to-use, industry-accepted anti-money laundering scenarios as well as industry-approved watchlists and sanctions lists.
  
  All this means investigators save time on data gathering and therefore have more time for investigation and analysis. Unified data also helps investigators make better decisions by providing a holistic view of customer activity across channels, which enables them to see relationships and patterns that they otherwise might have missed.
  
  

• AI and machine learning. While traditional rules-based AML scenarios may keep financial institutions technically compliant, they are unable to adapt to the constantly changing patterns of today’s criminals. Artificial intelligence and machine learning models can improve detection by rapidly adapting to evolving trends. These new models can be run in parallel with rules that can later be turned off when compliance professionals and their regulators are comfortable with their efficacy. AI can also be used to automate tasks so anti-money laundering professionals can file suspicious transaction or activity reports, either electronically or manually, with regulators in real-time.
  
  

Technological advances in crime detection and reporting capabilities are finally leveling the playing field between larger financial institutions and mid-sized banks. By embracing such technology innovations sooner rather than later, banks can improve compliance, be better prepared for changing regulations, reduce operational costs and, most importantly, thwart criminal behavior.

By John Edison, Vice President and Global Head of Financial Crime and Compliance Products, Oracle