AI in fintech: 7 trends for 2017 – Seldon -- Open Source Machine Learning

AI in Production – AI is only used by banks in production in a few key use cases such as high frequency trading, fraud detection and credit scoring. In 2016 many machine learning R&D projects started across other business functions. In 2017 banks will move from testing machine learning models to putting models into production to make a real impact on business KPIs. Open-Source AI Platforms – Leading on from the last point, banks will have to consider if the best strategy for operationalising models is to use a major cloud vendor, proprietary tech, open-source tech or in-house build. I think the winning combination is an open-source core machine learning platform supported by in-house R&D higher up the stack, and cloud provider focused mostly on the lower level compute tasks.