Abhinav Jain
Case Study

Abhinav Jain

VP, Global Fraud Decision Science
Abhinav Jain graduated from IIM Ahmedabad in 2009. He joined American Express and has since held positions of increasing responsibilities in fraud risk management across analytics, data science and AI modeling in the span of 12 years. Abhinav has a proven track record of implementing innovative solutions including a patent on leveraging sequential modeling to
predict fraud.
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Monday, 19 September, 2022 / 12:30 PM - 01:00 PM IST
Case Study: Leveraging AI and Data to Mitigate Account Login Fraud

There has been a rise in account take over fraud. With advent of Chip-Pin and Online OTPs, fraudsters are looking at more unconventional ways of committing credit card fraud. Fraudster’s login into customer’s online account to change key demographic info, order replacement cards, get access to OTPs or disable spend/fraud alerts. This activity is then followed by fraudulent transactions on the customer’s card. We developed an end-to-end modelling solution which at an account login level can predict if the login is indeed from a genuine customer. Logins with high-risk score would be asked for incremental authentication while low risk logins
would get a seamless online experience. In this session, we will talk about the following:
1. Leveraging digital data and card spend data to create innovative data elements which
capture bad logins while ensuring minimal impact to good customers
2. Developing a stable ML model in a volatile fraud environment by relying on model metrics
which align with business needs
3. Importance of collaboration with business and technology teams to ensure efficient
implementation

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