In asset management, we already have a significant and growing portion of assets being managed using data-driven “quantitative” investment strategies. This should be the starting point for discussing machine learning (ML) in investment research.
To successfully manage large amounts of peer-to-peer investments, our team has prepared an algorithm which saves a lot of time and manual work by investing in loans automatically. ML helps to develop strategies more efficient and profitable.
MS 16 together with Sneakypeer is constantly improving knowledge for Risk Team to ensure that they are working with the latest technologies to process large amount of data for data-driven investments.