Follow Us On

Fraud prevention: using classification models, neural networks, density-based behavioral clustering and ML ops for real-time detection of payment and return fraud

October 13, 20219:00 - 9:30AI Retail - AI Expo 2021

Moderator

Tom Peroulas

Tom Peroulas

Board Member, Sarcoma Foundation of America
  • October 13, 2021
  • 9:00 AM - 9:30 AM

Speaker

Ravindra Yadav

Ravindra Yadav

Director of Data Science, Meesho

Abstract

Due to the dramatic increase of fraud which results in loss of billions of dollars worldwide each year, several modern techniques in detecting fraud are continually developed and applied to many business fields. Fraud detection involves monitoring the behavior of populations of users in order to estimate, detect, or avoid undesirable behavior. Undesirable behavior is a broad term including delinquency, fraud, intrusion, and account defaulting. In this session, We will talk about different types of Fraud related to e-commerce and techniques used to detect such frauds. We will also go through the process of using these fraud detection mechanisms in production scenarios. This includes deploying your model for real-time fraud detection and batched/retrospective fraud detection.