Presented at #H2OWorld 2017 in Mountain View, CA.
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Abstract:
Venkatesh will explore how driverless AI is helping to keep fraudsters at bay. Share results from experiments conducted on large scale payment transaction data.
Venkatesh's Bio:
Venkatesh is a senior data scientist at PayPal where he is working on building state-of-the-art tools for payment fraud detection. He has over 20+ years experience in designing, developing and leading teams to build scalable server-side software. In addition to being an expert in big-data technologies, Venkatesh holds a Ph.D. degree in Computer Science with specialization in Machine Learning and Natural Language Processing (NLP) and had worked on various problems in the areas of Anti-Spam, Phishing Detection, and Face Recognition.
4. Fraud Prevention @ PayPal
Robust feature engineering, machine
learning and statistical models
Highly scalable and multi-layered
infrastructure software
Superior team of data scientists,
researchers, financial and intelligence
analysts
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5. Collusion Fraud – An Example Scenario
Buyer purchases an item using PayPal
Seller ships item to buyer
Buyer finds box empty & asks PayPal for
refund
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PayPal can refund buyer (eligible transactions under Buyer Protection)
6. Collusion Fraud – An Example Scenario
PayPal incur loss
Seller gives proof
Buyer and seller split the money..
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Collusion Fraud
PayPal asks seller for
proof
Repays seller (Seller Protection)