One of the key functions of an anti-money laundering (AML) solution is to make it easy for financial institutions to detect and report suspicious activities to regulatory bodies. This is done by submitting a suspicious activity report (SAR) to the regulator that governs the operations of a particular financial institution.
The Challenge of Accommodating Increasing Workloads
Simply put, a suspicious activity report includes all of the information related to suspicious or illegal activities that may be taking place within the reporting financial institution. These reports form the standards by which one measures the effectiveness and efficiency of anti-money laundering regimes and regulatory bodies. Compiling and submitting a suspicious transaction report is a seemingly straightforward activity, but repeated a million times, filing SARs places a significant burden on the establishments that make up the global financial sector.
The process of fulfilling regulatory reporting requirements has changed much over the years, and the number of SARs submitted by financial institutions has ballooned as well. In 1996, SARs numbered to only 150,000; by 2017, this figure has risen to over 3,000,000. In the same year in Europe, the number of SARs that were filed by finance-related businesses has reached 1,500,000, which is double the number of reports filed in 2006.
The increasingly strict regulatory standards for SAR submissions plus the rising number of reports filed contribute to the increasing cost of compliance. At the same time, the number of reports that regulatory bodies receive every year can be seen as a possible sign of weakness in the current AML reporting process. This can be interpreted as a reflection of a weak detection system that flags every suspicious activity and generates way too many alerts, enough to overwhelm the investigators working on these cases and compromise the quality of the investigations being conducted.
Faced with these challenges, how then can financial institutions reduce the cost and resources they need to maintain the quality of their reports, keep their establishment free from illegal activities like money laundering, as well as remain compliant to the standards set by regulatory bodies? The answer may be found in these three innovations used in enterprise-level AML solutions:
Machine Learning for Detecting Suspicious Patterns
Traditional AML programs are typically made up of many components like transaction monitoring, case management, and analytics, to name a few. The segmented process has served as a bane and a boon to both financial institutions and malicious entities. While it has previously allowed legitimate establishments to refine the way they detect suspicious activities, financial criminals are also finding ways to catch up and use this segmented system to their advantage. They do this by hiding traces of their illegal activities in various platforms such as the cloud, social media, and big data, making detection a more challenging affair.
Machine learning, or a form of artificial intelligence with the ability to learn from existing data, comes into the picture as a step up from the traditional query-based detection system that financial institutions now use to single out suspicious activities.
Based on the money-laundering patterns that criminals currently rely on, the AI can teach itself to write expressions of complex detection rules. This means that the technology can continuously refine and update rules without requiring human intervention. In turn, this can keep the financial institution’s compliance team highly effective without necessarily bringing new and specialized personnel into the picture. Take note, though, that machine learning does not eliminate the need for verification of detection configuration; the technology simply expedites the detection process.
Robotics for Automating Investigations
Robotics refers to the process of using robots to automate work, something that can be done when handling investigations. The investigation can be automated from start to finish, or it can also be designed to seamlessly integrate the human and robotic components of the process. Using robotics, the investigation process can be made more efficient and less resource-intensive without making concessions with the quality of the report. At the same time, because the compliance team is aided by a robot and is no longer bogged down by mundane tasks, its members can focus on enhancing their skills and improving their decision-making processes.
Cloud Solutions for Controlling Costs
More than half of an average company’s compliance cost goes to technology, while a significant portion of the other half of the budget goes toward staffing. These expenses, in part, can be due to using AML solutions that don’t come with automatic updates. Solutions like this often require on-premise deployment with the help of a technician from the solutions provider, a method that is prone to delays and errors.
A service-based cloud solution offers a mode of updating and delivering software on a subscription basis. The companies subscribed to this service can then expect the solution they are using to be the latest version. Without worrying about whether or not they’re working with the updated version of their AML solution or if the solution is up-to-date with the newest standards set by regulatory bodies, the compliance team can focus on the quality of their report.
A future-proof AML solution can go a long way in streamlining the AML reporting process. With these three technologies at their fingertips, financial institutions can ease the burden that SAR filing and compliance efforts place on their establishment.
