The importance of process automation in your anti-money laundering efforts

Bank Secrecy Act and Anti-Money Laundering (BSA/AML) are the top regulatory burden for Financial Institutions (FIs) today. They are looking for new technology to address this problem in a cost and time efficient manner. Robotic Process Automation (RPA) is just the solution.

RPA is no longer a novel concept. It is an inclusive term that refers to the application of technology, allowing a company to configure a “robot” to capture and interpret applications for processing a transaction, manipulating data, triggering responses and communicating with other digital systems. Larger FIs might believe outsourcing AML compliance to be an overwhelming exercise when in fact there are many advantages to it.

  • Increased productivity: Much like an iceberg, 90% of AML compliance lies beneath the surface. It boils down to the daily efforts of personnel who pore through sanctions lists, negative news results and public domain customer information to find anomalies. Smaller companies can get away with manual analysing and reporting, but having compliance agents go through millions of rows of data with a fine-tooth comb is a massive undertaking. RPA allows for 24/7 operations with fewer experts working on repetitive and time consuming tasks.
  • Changing regulatory requirements: It is time consuming and tedious to cope up with the ever changing regulatory environment while performing manual processes. Compliance agents, on an average, spend 15 per cent of their time tracking regulatory changes. With the amount of required documentation increasing, RPA helps ensure higher accuracy in lesser time while freeing up agents for more strategic work.
  • Data and risk assessments: Compliance agents spend a bulk of their time scouring data on customers from external sources to manually assess the risk rating of clients. These ratings also require frequent updating following regulatory changes and availability of new data. Automation of these process through the use of bots would mean that these ratings are more accurate and this can be achieved with lesser human time and effort.
  • Cost of non-compliance: The cost of compliance is high. But, the cost of non-compliance in today’s landscape is even higher. Manual processes increase the likelihood of errors or omitted information. Companies not only have to face the heavy fines if they fail the audit checks but also suffer brand damage, risk losing customers and investor confidence.
  • Accuracy: AML detection is all about financial formulae and algorithms. When it comes to these things, the most robust solutions are AI enhanced technical systems. These systems are able to self-learn and be taught to handle exceptions. Machine learning also recognises and analyses trends quickly, which in turn allows for instant detection of anomalies. These systems also perform behaviour modelling which increases the accuracy of risk assessments.
  • Audit trails: Should the regulator look back at a company’s processes years down the line, it is required, under KYC due diligence that an audit trail is maintained. RPA creates streamlined system that is simple and comprehensive by ensuring that all documents and processes are integrated and even includes information that might potentially be of use in an audit.

The final word

RPA is no longer a novel concept and it definitely isn’t a technology trend. It is the way forward to tackle AML programmes, keeping in mind the growing need for accuracy and maintenance of costs.

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