AI driving future of financial data, survey finds

New research has found that the use of machine learning is now widespread across financial services and is critical to the industry’s success in the future.

The research from financial markets data provider Refinitiv found that 90 per cent of financial firms are using machine learning, either in multiple areas as a core part of their business (46 per cent) or in pockets (44 per cent), while the 10 per cent of firms that have not yet deployed machine learning are experimenting with it.

According to the research, the main applications for using machine learning were in risk use cases (82 per cent), followed by performance analytics and reporting (74 per cent) and alpha generation (63 per cent).

The primary drivers to AI/machine learning adoption from financial firms were extracting better quality information (60 per cent), increased productivity and speed (48 per cent), and cost reduction (46 per cent).


However, respondents acknowledged that poor quality data impeded their ability to fully leverage machine learning and artificial intelligence technology, with 43 per cent citing this as the biggest barrier to adoption, followed by a lack of data availability (38 per cent).

“Machine learning and artificial intelligence are often described as emerging technologies, but the fact is they are already being widely applied across financial services,” said Refinitiv global head of applied innovation, Tim Baker.

“Whether it is an increasingly complex regulatory environment, the need to find new sources of alpha, or winning the fight against financial crime, the industry is turning to data and technology, and data scientists are increasingly important as the alchemists charged with turning big data into insight.”

The research was based on in-depth interviews with nearly 450 financial professionals across Asia (170), Europe (161) and North America (116).

The findings follow comments from IRESS chief executive Andrew Walsh that the most noticeable challenge was advisers being able to access data records in order to respond to institutions such as ASIC and the Hayne royal commission.

He said a large part of that issue stemmed from the requirement for advice firms to access records and acquire information in physical form, which had therefore limited their ability to have real-time oversight of their compliance. 

“We've seen responses [from firms] where people started to consolidate systems they've got from some of the institutional clients, however they've got multiple systems and those systems don't often talk to each other,” Mr Walsh said.

AI driving future of financial data, survey finds
Tim Baker
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Adrian Flores

Adrian Flores

Adrian Flores is a deputy editor at Momentum Media, focusing mainly on banking, wealth management and financial services. He has also written for Public Accountant, Accountants Daily and The CEO Magazine.

You can contact him on [email protected].

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