The adoption of AI/ML is primarily driven by extracting better quality information (60 per cent) and enhanced productivity and speed (48 per cent)
The use of machine learning (ML) is pervasive across the financial sector and is crucial to its success in future. Nearly 90 per cent financial firms are already using ML as a core part of their business, according to a latest survey by Refinitiv – a global provider of financial markets data and infrastructure.
About 90 per cent of financial firms are using ML, either in numerous areas as a core part of their business (46 per cent) or in pockets (44 per cent). Out of that 10 per cent of the firms that have not yet deployed ML, are experimenting with it, the survey reveals.
Poor-quality data – a hindrance
Globally, c-level executives and data scientists surveyed by Refinitiv acknowledged that poor-quality data hinders their ability to completely utilise ML and artificial intelligence (AI) technologies. Around 43 per cent respondents cited this as the biggest hurdle in adoption, while 38 per cent cited lack of data availability as a major barrier.
As per the survey, 75 per cent of firms are making considerable investments in ML technology. On the other hand, 62 per cent of respondents said they are planning to hire more data scientists in the future as asset and banks managers seek to give themselves a data and technology edge over their competitors.
Major ML applications
According to 82 per cent of respondents, the major application for using ML was in risk use cases. However, 74 per cent respondents think performance analytics and reporting is the main application of ML, followed by alpha generation (63 per cent).
The adoption of AI/ML is primarily driven by extracting better quality information (60 per cent), enhanced productivity and speed (48 per cent), and cost reduction (46 per cent).
Commenting on the survey findings, Tim Baker, Global Head – Applied Innovation at Refinitiv, said, “Machine learning and artificial intelligence are often described as emerging technologies, but the fact is they are already being widely applied across financial services.”
“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,” he added.