Navigating toward compliance
Financial firms face the threat of money laundering—and they also face the challenge of complying with Anti-Money Laundering (AML) regulations. Responding to a rising regulatory burden, banks are investing more into their AML programs. But adding money and headcount may not be the best solution.
A trio of Accenture papers explores AML compliance, presenting a continuum of solutions financial firms can consider. These include:
What journey will your financial firm take to revise its AML compliance program?
Steer clear of clunky compliance
For some firms, AML compliance is costly, involving time-consuming manual support for Know Your Customer (KYC), AML customer screening and transaction monitoring functions.
On average, financial firms spent $60 million per year on AML compliance, but for some larger firms the costs run as high as $500 million per year.1
Is it time to bring on the bots?
Robotic Process Automation (RPA) may not solve every issue, but—as outlined in Accenture’s report, the Evolving AML Journey: Operational Transformation of Anti-Money Laundering through Robotic Process Automation—used with the right processes, RPA can help reduce costs and boost effectiveness for financial AML compliance programs.
With these considerations in mind, we've identified some areas that might be ideal for RPA implementation, such as customer due diligence, client screening, transaction monitoring and offboarding. See how RPA might help evolve one or more of these processes for your bank.
Ready to disrupt?
If your bank is ready to strengthen its Anti-Money Laundering compliance efforts, the newest technology on the scene involves Artificial Intelligence (AI) and Machine Learning.
AI automates activities that require humans to make decisions and use intelligence. Within that scope, Machine Learning focuses on computers that can learn—without having to be programmed—when they are exposed to new data.
Take up of Machine Learning technologies has been slow within financial services, particularly in AML areas. As noted in our paper, Evolving AML Journey: Leveraging Machine Learning within Anti-Money Laundering Transaction Monitoring, firms don’t yet know how AI and Machine Learning can support an AML application. Machine Learning can seem like a “black box,” with its inner workings unclear to regulators and compliance officers.
But, done correctly, AI and Machine Learning can reduce costs and improve transaction monitoring for banks—bringing better efficiency overall.
For financial firms looking to take that next step toward greater AML efficiency and effectiveness, it’s time to investigate the gains that can come from Machine Learning.
Technology such as RPA and Machine Learning can boost efficiencies and lower AML compliance costs. But, they are still point solutions.
For some firms, the best next step is to build an AML model that can scale as needed and keep pace with changing technology. A comprehensive model can help financial institutions manage the complexity of regulatory compliance and still gain flexibility and efficiency.
Our paper, Evolving AML Journey: Balancing Internal, External and Virtual Workforces: An Evolving Anti-Money Laundering Operating Model for 2020, recommends reviewing key oversight and operational factors to identify AML model priorities.
Within a fully scoped AML model, RPA, AI and Machine Learning can play a strong role. In this scenario, institutions gain not just the efficiencies and cost savings from automating individual processes. They also become future-proofed, able to address tomorrow’s challenges—possibly while using tomorrow’s technology.
Evolve your AML compliance
Financial firms have a challenge on their hands:
AML compliance requirements are rigorous and evolving.
Hiring more resources can help ease the short-term pain, but might create a longer-term problem, particularly given the manual nature of many AML processes. A range of solutions can help firms save money and build efficiency into their AML programs. With the three options identified by Accenture in our reports, financial firms are able to choose an option that can save money and boost efficiency.
All that's left to determine is the best solution for your firm.
1 Thomson Reuters 2016 Know Your Customer Surveys Reveal Escalating Costs and Complexity, Thomson Reuters, May 9, 2016.