Compliance Pressures on Banks Increase Due to Record Number of Suspicious Activity Reports Related to Money Laundering

The pandemic has led to a rise in cyber crime

Bank compliance departments are also under pressure as a result of COVID-19. The pandemic has led to heightened security risks that cyber criminals are increasingly seeking to exploit. The result is a significant increase in fraud, cybercrime, money laundering, terrorist financing, and abuses of government stimulus packages and financial aid.

Flood of regulation poses challenges for banks

The last few years have also brought a flood of new laws and regulations for banks, including the EU’s action plan to combat money laundering. This year, Switzerland introduced CDB 20, a revised code of conduct for banks relating to due diligence.

There is no doubt that these developments make the work of compliance functions even more complicated and time-consuming. It is impossible for banks to cope with this situation using their existing procedures and staffing levels, but non-compliance with these regulations can result in heavy fines.

Digitalization is the key

Banks are required to show they have put in place effective procedures, such as compliance management systems. As they start to realize the seriousness of this situation, more and more financial institutions are turning to digital solutions. But they still have a lot of catching up to do when it comes to automated compliance and risk management systems.

Automated compliance and risk management systems

The answer lies in an intelligent combination of digitalization, analysis technology, automation, machine learning and artificial intelligence. New technologies help banks to analyze enormous amounts of data more efficiently, uncover suspicious patterns more easily, and recognize potential risks at an earlier stage. This slashes the time required to carry out complex analyses and checks, thus increasing efficiency and cutting costs.

Artificial intelligence and machine learning help financial institutions to analyze data based on automated, standardized, self-learning processes. They also flag up security risks or breaches of the law. A key issue here is the combination of prescriptive approaches – compliance criteria that are defined as business rules by bank experts – and predictive approaches (machine learning).

The benefits: more efficiency, lower costs

Along with analyzing huge volumes of data from different sources at high speed, these IT systems can also draw their own conclusions. This ensures compliance with legal requirements while increasing efficiency and cutting costs. More than ten of Actico’s projects have resulted in client savings of 30% to 50%.

The compliance departments of banks and insurance companies mainly use machine learning in sanction screening processes in order to detect money laundering and terrorist financing.