By Andrew Doyle, CEO of AML compliance software, NorthRow
Whether it is predicting consumer shopping preferences, guiding military decisions, or providing unique insights into financial crime, new uses for artificial intelligence (AI) are making headlines almost every day.
While the debate is evolving daily, most of us are in agreement that AI is set to transform almost every industry, across every sector. And none more so than in compliance. With regulators now expecting to see digital solutions in place to counter the risk of financial fraud, we’ll certainly see a deeper integration of AI and machine learning into anti money laundering (AML) and compliance processes as we enter 2024. Here’s why:
It’s proactive, not reactive
Advances in technology have undoubtedly made it more difficult for businesses to keep up with the rapidly evolving tactics of online fraudsters, especially in the financial services sector. This means banks, fintechs and other financial services businesses need to forget about reactive fraud prevention approaches and embrace proactive, pre-emptive efforts that can be afforded by AI.
The adoption of AI technology can be used to improve and accelerate the automation and streamlining of what were slow and manually intensive fraud prevention and AML and Know Your Customer (KYC) verification processes, and enable much quicker identification of violations to reduce the risk of non compliance.
It spots issues, faster
AI technology can also analyse and interpret large volumes of data, helping organisations identify patterns, anomalies, and potential compliance issues more quickly and accurately than ever. It gives compliance teams real-time insights into data and information, enabling them to make more informed decisions, faster.
With algorithms able to detect suspicious fraud patterns at lightning speed, predictive AI has the ability to help financial services businesses identify bad actors more speedily and even stop fraud from happening in the first place.
It’s more efficient
Not only will AI translate complex regulatory text, it can also automate the creation of various documents, including contracts, reports, and legal documents all required for regulatory compliance. It also helps reduce the risk of human error and will improve accuracy in compliance-related tasks, such as data analysis, reporting and monitoring.
While AI is undoubtedly a transformative technology and has the power to enhance the compliance function across all regulated businesses, it also brings with it a certain set of challenges which need to be considered.
Data privacy and security
AI systems may store large amounts of sensitive data, making them attractive targets for hackers. Businesses need to ensure that data privacy and security measures are in place to protect this data, while ensuring their AI systems are securely designed, implemented and managed to minimise the risk of any data breaches.
Ethical use
There is a need to ensure that AI is used ethically and responsibly. Compliance with ethical guidelines and regulations is crucial, especially when it is used in customer interactions and to aid decision-making.
Auditing and training
Financial services businesses need to have mechanisms in place for auditing and validating AI-generated content and decisions to ensure they comply with the latest regulations. This means the use of AI requires ongoing training for teams across the business to ensure everyone understands how and why it is being deployed.
There’s no denying that the emergence of AI is transforming the landscape of AML compliance, helping regulated businesses better detect and prevent incidents of financial crime, while helping them navigate and adhere to the latest regulations.
However, it is really important to establish a balance between AI adoption and human expertise to ensure that data privacy, ethical deployment and adequate auditing and training programs are in place first. Only then can AI become truly transformative.
