Smarter Humans, Smarter Machines was the core theme of our closed-door #RefinitivSocial100 UK roundtable held in September 2019, with 10 of the UK and Europe's most influential thinkers and thought-leaders on social media in the world of FinTech. Hosted by Refinitiv CEO David Craig and Ben Shepherd, Chief Strategy Officer, and moderated by Amanda West, SVP Innovation Refinitiv Labs, we held a near 2 hour-long discussion on the future of artificial intelligence and the challenge of poor data quality in financial institutions. The main question that everybody was seeking to answer was: Is poor data quality hindering the deployment of machine learning (ML) by financial services companies? "Banks have been saying for a very long time that the data they have is messy and needs to be cleaned. "When we imply that the data might be wrong, we are of course implying that the ultimate decision you make, the automated, autonomous decision made by the AI, having gone through machine learning, could be wrong". FinTech and digital payments advisor, Neira Jones (@neirajones) agreed that using bad data in ML somewhat defeats the object. "Years ago, when we had huge data warehouses… you would have time to clean up your data.

The rise of AI and machine learning in financial services is already driving major benefits across compliance and the customer experience. To realize the full potential, Sean Durkin, Head of Data Science at Barclays, tells us in our latest Expert Talk about the importance of being able to appreciate the "art of the possible". Best practice tells us that screening remains our best defense against corruption. However, Refinitiv's 2018 research into the true cost of financial crime highlights just how tough it is for often over-burdened compliance teams to pinpoint potential risk in the age of big data and global third-party networks. Such challenges can lead to gaps in compliance, which inadvertently allow financial crime to flourish.