The Clearing House recently called for an overhaul of anti-money laundering practices, but financial institutions would be better served by improving the efficiency of existing AML and "know your customer" functions.
Currently, while the SARS reports are being filed, institutions are not capturing how many actual AML events are being identified as confirmed laundering activities and using that information to refine the process.
In fact, nearly 75% of analysts’ time is spent on acquiring, cleansing and validating data, which only leaves a quarter of their time for true alert investigations. This creates a backlog, which leads to human errors and high levels of false positives that take away from true high-risk alerts.
At the highest level, the objective of alert monitoring is to execute the requirements for KYC during onboarding and across the lifecycle as risk levels change, while importing customer information from trusted data sources and linking transactions to specific accounts and appropriate entities to determine risk. Inefficiencies that impact the AML function begins with the customer onboarding data capture, as well as data quality and enrichment.
If the initial data, which is used to build customer and client profiles, is flawed, the entire process will be ineffective and produce a high degree of either false positives or incorrect risk tagging of transactions.
To evolve to the next generation, financial institutions should focus on the following seven areas: data quality, portability, flexibility/scalability, automated process and analytics, enhanced performance, creating a closed loop process, and maximizing on the investment in optimizing the current process, tools and technology.
This will optimize AML/KYC activities by creating more meaningful SARs reports, reducing the high level of false positives that lead to erroneous reporting, and allow for internal groups to devote more time to prioritize and investigate the true high-risk alerts.
This shifting focus will improve analytics, reduce false positives and facilitate tests around the introduction and removal of information sources using both structured and unstructured data to measure impact. In addition, the improved data quality and customer profiles will also satisfy KYC requirements per the U.S. Patriot Bank Secrecy Act. By analyzing the contributing characteristics that drive false positives, financial institutions will be able to improve triggers during the transaction monitoring process.
Without separate functions assigned to each line of business, there is an opportunity to leverage new data and partnerships to contribute to a tighter global financial services AML community, while also constantly evaluating and improving prevention of AML activities at multiple levels rather than overhauling the entire system.
