Jaywing grows consulting team with Dr Steve Finlay, credit risk and machine learning expert
Risk and Data Consultancy, Jaywing, has appointed credit risk and machine learning expert, Doctor Steve Finlay, as lead consultant to strengthen the company’s analytics offering and innovate its product suite.
With over 25 years’ experience of providing analytical solutions to the financial services industry, Steve’s expertise will help organisations navigate regulatory requirements, optimise acquisition and collections strategies, and develop and validate scorecards and models used to underpin credit decisions. He will play a key role in continuously assessing and innovating Jaywing’s proprietary products, which are designed to improve the way organisations detect fraud, make lending decisions, set provisions and collect debt.
Previously, Steve worked at Computershare Loan Services as Head of Analytics, The Co-Operative Bank as Senior Manager for Risk Models, HMRC as a predictive analytics consultant and earned a PhD in Management Science from Lancaster University. He has written several academic and business books. The new edition of his latest book, “Artificial Intelligence and Machine Learning for Business: A No-Nonsense Guide to Data Driven Technologies” was published last year.
Steve Finlay, Lead Consultant at Jaywing, says “I was drawn to Jaywing as it was at the forefront of many things that are now considered commonplace, such as the use of AI-based decision making to optimise business processes. It is an adventurous, ideas company whose roots in science made them an obvious match for me.”
Nevan McBride, Risk Practice Director at Jaywing, comments “We’re thrilled that Steve has joined our data science team. As one of the UK’s leading experts in data science, Steve will not only help our clients extract the most value from their data but will also ensure Jaywing’s proprietary products, including our award-winning explainable AI solution, Archetype, offers organisations the cutting-edge technology they need to de-risk key business decisions.”