The Case for AI in Communications Surveillance

Surveillance is high on the agenda for most financial services’ compliance teams. Despite extensive work done in this space, many firms still find their surveillance processes insufficient compared to the expectations of regulators. Last year, the?UK’s Financial Conduct Authority (FCA)?issued a statement that it remains concerned that requirements for market abuse surveillance are not being fully met, despite the Market Abuse Regulation (MAR) having been introduced as far back as 2016.

The reason that market participants are not fully meeting all requirements may not be for want of trying, however. Surveillance – and communications surveillance, in particular – is a complex and data-heavy activity.

Consequently, many compliance teams are now looking at how artificial intelligence (AI) – or one or more of its subcategories of advanced analytics – could be applied to the puzzle, either alongside or in place of more traditional solutions.

In this article, GreySpark takes a deep dive into the use case of AI in surveillance systems, and how AI subsets such as Machine Learning (ML) can be optimised in surveillance systems.

There’s plenty more where that came from. Head over to our website at www.greyspark.com to discover more.

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GreySpark Partners is a global business and technology consultancy, specialising in mission-critical areas of the capital markets.

For decades, we have been a lynchpin to the world's most critical financial firms, tapping into our deep expertise and helping them to adapt to changing regulatory and technological environments.

GreySpark has offices in London, New York, and Hong Kong.