Aapryl has predictive capabilities and helps manager research teams separate manager skill from factors. The platform consolidates multiple sources of data into a one-stop platform to make it easier to analyze. We provide tools to streamline processes, monitor risk, and increase your comfort with recommendations.
Aapryl’s portfolio replication techniques allow you to identify key factor exposures and to separate the effects of factors from skill. Compared to other quantitative assessments, it provides the Aapryl Score which goes further in providing a predictive indicator. A machine learning engine (using neural network algorithm) is utilized to answers the question, “compared to the average manager in a category how likely is a manager to finish in the top quartile over the next 3 years?”