As organizations deal with increased online volume, processes for onboarding new clients and monitoring existing clients and their transactions are emphasized to battle money laundering.
However, for a proper risk-based approach, onboarding strategies should measure risk in real time that a particular client poses and collect the necessary information for proper evaluation. In addition, in the online world, presenting the right user experience and ensuring that the right data collection and evaluation technology is applied to the right risk level are also important.
A recent report published by Europe's Moneyval AML committee finds that while crime rates have stayed relatively flat in some areas, criminals are taking advantage of new and existing vulnerabilities exposed and underscored by the COVID-19 pandemic.
The report also found the following money-laundering areas of concern: fraud and embezzlement; medicrime; corruption; cybercrime; and late demand for moving illicit funds.
Similarly, U.S. FinCEN’s Director Kenneth Blanco, in his remarks during an ACAMS AML conference, highlighted three key areas of concern due to COVID, where FinCEN has issued advisories related to medical fraud, imposter scams and money mules; and cybercrime and cyber-enabled crime.
Both Moneyval and FinCEN list several strategies and recommendations for organizations to deal with these emerging threats. These recommendations include both online and offline activities. We want to focus on a couple of areas where an automated AML system can support the proper application of a risk-based approach and the adoption of focused monitoring techniques that deal with a large portion of the emerging threats mentioned above.
The risk-based approach, recommended by the Financial Action Task Force (FATF), calls for applying adequate efforts that vary based on the risk that an individual, business or action poses to an organization’s ecosystem. As part of the approach, once an organization has performed the needed risk evaluation, it must translate its strategy into actual practices that can be implemented and enforced by the organization.
Automated AML systems offer the necessary tools to measure the risk an individual poses in real time, providing a coherent and cohesive use of technologies including document verification, biometrics, data validation, fraud analysis, and sanctions and PEP screening to properly identify, authenticate and screen an individual. Fundamentally, knowing with certainty the validity of an identity addresses the threat of imposter scams, elderly abuse, medical fraud, and reduces the likelihood of mule activity.
While knowing and proving the identity of a new client is important, and a good onboarding process thwarts important threats as noted above, all compliance officers and analysts know that onboarding is just the beginning. Continuous monitoring of activities, apart from being required by AML regulation, is fundamental to understand and raise alerts on behaviors associated with AML typologies.
All regulated organizations monitor transactions. Most traditional and large financial institutions rely on automated systems to alert them when clients exhibit suspicious activities. However, many automated alerting systems are homegrown, and others are antiquated. Both lack the capabilities to adapt quickly to new threats like the ones described by Moneyval and FinCEN. In addition, these systems tend to generate large numbers of false positives that tie up compliance teams and increase the chances to miss important events. These systems also don’t understand well (if at all) virtual currency operations, which FinCEN’s Kenneth Blanco said are becoming a fundamental vehicle for money movement across the financial ecosystem.
Smaller organizations, in general, rely on manual efforts using spreadsheets and the expertise of their compliance analysts. Manual transaction-monitoring doesn't scale to the acceleration of online activity, leading to many potential false negatives, and reduced efficiencies as teams demand quick growth and analysts take time to train properly.
Modern AML transaction monitoring systems are capable of assessing risk dynamically, applying proper models and reducing false positives. They can add new models quickly that cater to new threats and can scale horizontally to the demands of increased volume of transactions. In addition, a modern AML system deals natively with virtual currencies presenting an integrated and holistic picture to compliance teams. A modern AML transaction monitoring system should uncover changes in behaviors that alert on bribery and corruption, money mules, late money movement, and cross border and jurisdiction activities.
Modern automated AML systems can implement a risk-based approach facilitating proper onboarding and monitoring of clients’ transactions and behaviors, and they can adapt faster to protect against new and evolving threats like the ones emerging during this pandemic. By using automated AML, businesses are able to complete effective compliance processes faster and at a lower cost than can be achieved manually.
