Practical uses of AI & ML in the fight against financial crime


As the fight to prevent and tackle financial crime hots up, the need for new and expansive technologies becomes just as important.

In a recent presentation, Napier chief AI officer Luca Primerano highlighted some of the practical uses of AI and ML in the fight against financial crime.

A key issue in the industry can be found when banks are reviewing clients. Primerano explained, “Banks and financial institutions need to review their customers on an ongoing basis to make sure that what the customer said they would do corresponds to what they actually did in terms of transactions, activities, and events, throughout the lifecycle of that customer within that financial institution and financial organisation.

“If you think about the problem from an analyst point of view, from somebody who’s running these reviews on an ongoing basis, what often happens is the data that holds the information representing the customer transactions and activities, is split between different silos. So, it’s very difficult to connect all of this information together and present it in such a way that an analyst can make the better decision and can therefore focus on those activities that are inconsistent with the historical data and historical activity.”

Primerano outlined that in many examples, the big issue is how to manage all of this data, and how can it be presented to the user so they can make a decision in the fastest and most efficent way.

He added, “Wouldn’t it be great if I could train a set of machine learning agents based on the historical trading of historical activities of customers, and as the machine learns the patterns that represents the activities of a customer, it can also learn what good looks like and what bad looks like, because that’s represented by anomalies in data, anomalies in behaviour, and therefore present this information back to an analyst for them to make a decision on where are the key data points they need to investigate and where a deep dive is required.

“So the idea is, therefore, you train your machine learning agents, they understand the behaviour of the customer, and they can therefore understand the anomalies, the unusual correlation in data.”

To listen to the whole presentation, enrol in the Professional RegTech Certificate.

About the Professional RegTech Certificate

The Professional RegTech Certificate course offers a comprehensive and practical exploration of Regulatory Technology (RegTech) for professionals working in the financial industry. With a focus on real-world applications, the course covers key topics such as the fundamentals of RegTech, adoption strategies for financial institutions, the regulators’ perspectives, data reporting, KYC and onboarding, anti-money laundering, cybersecurity, advanced technologies such as AI and ML, and specific legislations.

The course stands out from others by providing a holistic view of the RegTech landscape, combining real-world case studies with insights from leading-edge RegTech innovators and senior leaders from financial institutions.

You can enrol here.

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