[DSC 5.0] Recommender Systems for Personalized Financial Advice - Aleksandra Chirkina

In this video we present a recommender system for personalized financial advice, which we designed for a large Swiss private bank. The final recommendations produced by the system were delivered to the end clients through a mobile banking platform. The recommender system is based on collaborative filtering technique and can work with changing asset features, operate with implicit ratings and react to explicit feedback that clients can give using the mobile app. Moreover, we developed and implemented an approach to provide an explanation for each recommendation in the form “As you bought A, you might like B”
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Aleksandra Chirkina is a Data Scientist at InCube Group, working on designing and implementing machine learning solutions in the financial industry.
This talk was presented during the Data Science Conference / 5.0 as a part of the Applicative ML track.

[@DeanRKern]

nice work! :)