From Data to Dollars – Using Advanced Data Technologies to Minimize Fraud Loss.
In the world where digital payment is increasingly becoming commonplace, it is important to keep a check on fraud loss. Fraud pressure on popular payments companies is on an upsurge and if left unattended, it can potentially eliminate the business. One way to keep a tap on the fraudulent activities is to leverage the humongous amount of data that flows in with every transaction or user activity on the platform. Using the right data technologies to process the data can help in adjudicating whether a given transaction is fraudulent. In this presentation, I will talk about various ways in which an ecosystem can be constructed with the popular large scale data processing technologies like Hadoop and Teradata to mitigate the fraud loss.
The flow of the talk is as follows:
1. Introduction - What is Fraud Loss and Fraud Pressure?
2. Fraud Models – Mathematical armor for fraud prevention. (Illustration with a fraud model training)
3. Building an Ecosystem of Data Technologies
3.1 Ways to pre-process data to create unique data artifacts that can be used in near-real time.
3.2 How to link popular Data Technologies using a service to create an ecosystem to enable easy data access.
3.3 Journey of a data variable across all stages - raw data collection, data processing, model score computation and finally decision.
Starakjeet Nayak is a Product Manager at PayPal, working in the Risk Platform team for nearly four years. He has worked for designing and implementing many risk services at PayPal. He has extensively used Hadoop to analyze data to identify transactional fraud at PayPal. Prior to PayPal, Starakjeet has worked for Oracle and he has graduated in Computer Science from Birla Institute of Technology and Science, Pilani.
Outside of work, he likes outdoor activities like hiking, cycling and running. He enjoys public speaking and he has been the event anchor for big events at PayPal like Recharge 2017.