Financial services businesses are missing out on transformative insights because only three per cent are using machine learning (ML) to analyse their unstructured data, according to research.

A Censuswide survey of 150 senior IT decision makers at UK financial services firms for Cloud Technology Solutions found that while artificial intelligence (AI) and automated functions such as Machine Learning are being used to process and analyse structured data, the value of unstructured data remains untapped.

Unstructured data includes audio, video and email files and accounts for around 80 per cent of the data that financial services firms hold.

A total of 75 per cent of those surveyed said ML is being used to analyse structured data, such as names, addresses and credit card numbers, however 62 per cent admitted they were not using the technology on a “holistic” basis across their business.

The adoption of machine learning also appeared to be piecemeal, with more than half (57 per cent) saying it was being used by their IT department and just under a third (32 per cent) rolling it out across their risk unit.

The top application for machine learning in the sector is compliance, with nearly three quarters (73 per cent) using it to flag regulatory and governance issues.

Ryan Stewart, financial services lead at Cloud Technology Solutions, a Manchester-based Google Premier Partner, said: “Data-led insight is increasingly vital across financial services. We’ve seen a lot of digital disruption in the industry and this has put significant pressure on the largest firms to rethink their operations and improve services to retain market share.

He added: “Increasingly, firms are recognising that the ability to collate, store and analyse big data is essential – and that ML is key to unlocking business insights from this data that can help them outsmart the competition.”

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