Sujata Dasgupta, Global Head – Financial Crime Compliance Advisory, Tata Consultancy Services
There’s not a financial institution across the globe that will be a stranger to money laundering, fraud, and other financial crimes. In the UK, institutions have witnessed a significant rise in financial crime since the pandemic, with analysis by money.co.uk of the fraud and cyber-crimes reported to Action Fraud finding that £2.4 billion was stolen in 2021, 174% more than the previous year. And these are just those crimes that are reported– in reality, the amount lost to criminals could run to tens or hundreds of billions of pounds per year.
With the frequency and severity of such crimes on the rise, they increasingly pose a significant challenge to banks and financial services firms. Many banks have been struggling to tackle longstanding financial crime compliance issues due to poor data quality, fragmented compliance platforms, high false alert volumes, and high operational costs.
But the biggest problem is that the financial crime compliance units of these financial institutions still rely mainly on heavy manual processes. Their key reason for their cautious approach in the utilisation of AI and automation has been uncertainty about technology. Do regulators approve machine-based decision-making, and is machine learning logic fair in identifying suspicious activities?
This uncertainty highlights a clear need for the proper utilisation of technology in financial crime compliance. Financial crime compliance functions are responsible for monitoring account transactions and customer behaviour for money laundering, terrorist financing, bribery, corruption, and fraud. The current systems and processes of the financial institutions mean that these tasks involve heavy manual routine measures that take up a significant portion of staff’s working time.
Regulatory technology, or RegTech, could make handling these routine tasks more efficient. This tech can utilise machine learning, advanced analytics, NLP, dynamic biometrics, network graphs and other forms of AI, which can take responsibility for routine tasks such as data collation and processing, as well as some other everyday responsibilities. This can free up significant portions of analysts’ time for more complex, cognitive work such as in-depth investigations into potential crimes, as well as other tasks that require data-driven judgement and decision-making.
Lack of access to information on criminal activities outside national boundaries has hindered efforts to combat banking fraud and compromised anti-money laundering and financial crime compliance actions taken by banks. While the need for collaborative action in fighting financial crime is evident, financial crime intelligence sharing has hit a roadblock given restrictions imposed by data privacy regulations. As usual, technology has come to the rescue – privacy-enhancing technologies (PET) offer a way to share data while protecting privacy. Using PETs can help financial institutions to understand suspicious patterns of behaviour through financial information sharing and analytics whilst preserving the privacy of individuals.
Internationally, governments are just now starting to utilise PETs. For example, in June 2022, the UK and US governments collaborated to develop PETs to tackle digital financial crime and enable data sharing better across borders to prevent money laundering attempts.
There has been some progress in using technology to fight financial crime on a national level also. In 2019 the Bank of England announced that it would be working to encourage the introduction of artificial intelligence-based RegTech among UK banks. It pledged to launch a review in consultation with financial institutions to increase the use of RegTech over the next decade, to reduce the burden on them and improve the quality and effectiveness of their data. UK’s Regulator, Financial Conduct Authority (FCA), has encouraged FIs to use advanced technology to prevent and detect fincrimes, providing sandboxes for RegTech solutions development and validation. FCA has been organising Tech Sprints every year to foster innovation in this space.
Some banks in the UK have already started adopting AI-powered solutions in fighting financial crime, while others are yet to explore advanced technology in this space. As financial crimes quickly grow more complex, adding more people to compliance functions alone may not help in disrupting them. A strong defence requires a combination of people, processes, and platforms. Processing huge volumes of data to uncover sophisticated criminal networks and illicit money trails in financial institutions must necessarily utilise AI.
In 2021, the European Commission announced guidelines on ethical AI, pursuant to which artificial intelligence solutions will be classified as a minimal, limited, high or unacceptable risk. Recently the UK Government also announced plans to publish a national strategy on responsible AI adoption. These types of guidelines based on regulation will support increased AI usage even in compliance functions.
In the UK, people have trust in banks and financial institutions. The only way for the financial sector to maintain and grow this trust is to keep up with the development of technology which can help fight financial crime. Financial institutions must step up and proactively seek technological and AI solutions to deal with increasingly sophisticated criminals and hackers. The time for action is now!
