Fraud is expensive for businesses worldwide. Fraudsters are now using more sophisticated and dynamic methods for credit card, money laundering and other types of fraud. One way to combat this is to track and link suspicious customers that come to your online website, gateway or marketplace using device tracking. You can then automatically decide whether to allow those customers' transactions or deny them, based on different risk factors.

Join this webinar to learn how The Workshop built a device tracking and fraud detection application using Neo4j. They'll discuss what device tracking is, how they used it to develop a fraud detection application, and why they chose the Neo4j graph database to do the job.

ALEKSANDAR YABALKAROV
Product Manager, The Workshop

In the last 10+ years Aleks has worked in the online payments, fraud prevention and online entertainment industries. He gained valuable experience in the areas of Product Management, Business Analysis, Software Development, People Management and Customer Service. Aleks is interested in ways to prevent fraud in the online world – from conventional ecommerce through the entertainment sector, to IoT.


MIGUEL YEPES
Agile Development Lead, The Workshop

Miguel is a software engineer from the University of Cordoba. He joined "The Workshop" about 5 years ago and has worked on several e-commerce projects, including one related to fraud. This last project uses Neo4j to run real-time fraud checks for high volumes of transactions in a context where performance is very important.

Kelsey Bieri
Data Governance Analyst, ICC

Kelsey Bieri is a Data Governance Analyst at ICC in the Master Data Management and Data Governance Practice. She has contributed to numerous data governance and data lineage projects in the Banking industry, helping organizations build a better understanding of their data universe. Kelsey holds a degree in Management Information Systems from the College of Business at Ohio University.

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