ML-based clients prioritization and ranking algorithm

Abstract

Kristal.AI is an AI-powered DigitalWealth Management Platform. It is one of the leading firms in the Fin-tech industry, which provide its customers a platform for wealth investments, It has a very well experienced committee for handling customers queries and also has an AI-driven advisory algorithm that recommends portfolios to the customers according to their profile. As the company has stepped into the AI-driven world, it wants to implement one AI-driven algorithm for it’s clients prioritization and Ranking, so that Relation Management team of the company can focus more on more potential users of the company’s platform rather than just hovering around users who may not be worth of time, as there are also users who just do the sign up for the sake of curiosity but do not want to enroll themselves as the authenticated clients of the company. To tackle this problem there is a need of one AI-based automated algorithm which filters the more potential users from the data and ranks them according to their likelihood of becoming the company’s authenticated Registered KYC approved client. I with the Data Science team of the company has tackled this problem by creating one Machine Learning based client prioritization and ranking algorithm that takes raw company’s data as input on a daily basis and generates a list of clients with their corresponding ranks in which they are to be followed, and for this, weeks of Exploratory Data Analysis had been done to select the crucial features and One Regression Model(Gaussian Process Regression) was created and optimized to give the desired output. This model gave an accuracy of about 82% and a precision of about 84% over the test set.