A fintech talent war is pitching corporations against startups in pursuit of the AI skills required for the digital transformation of financial services. Our #RefinitivSocial100 thought leaders discuss hiring, retaining and educating data science talent. Advances in artificial intelligence (AI) have made hiring and retaining the best fintech talent one of the most pressing challenges facing the financial services sector today. This race to attract the right skills is exacerbated because corporates and startups search for the same profile within a limited pool of fintech talent. It's also apparent that the education system is not geared to producing thousands of students with the required AI skills.

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.