Machine Learning Engineer
Solutions for continuous user authentication- based on gait data and other mobile sensors.Failed experiments around graph database- to analyse fraud rings and estimate similarity patterns across them.Estimation of Risk Analysis of candidates based on digital presence/ PF passbook/ other publicly available databases for credit lending solutions.Developed Behavioural Analytics systems to detect fraudster based on the interactions with the loan applying app.Setting up pipelines and running simulations for analytic reports of video-kyc calls to understand future potential blockages.Algorithms to detect tampering/ reusing the same NID card for various onboarding apps which saves the company nearly $2000 for each fraudster caught.