Abstract
Fraud Banks and insurance companies lose billions of dollars each year to fraud, and investigating fraud often involves identifying suspicious patterns among mountains of uninteresting transactional data. Increasingly sophisticated fraudsters have developed a variety of ways to elude discovery, both by working together, and by leveraging various other means of constructing false identities.

Graph databases such as Neo4j offer new methods of uncovering fraud rings and other sophisticated scams with a high-level of accuracy, and are capable of stopping advanced fraud scenarios in real-time. This provides an enhanced degree of insight, compared to fraud detection algorithms that use basic statistical analysis and pattern recognition.

Neo4j is allowing users to develop the next generation of fraud detection systems based on connected intelligence.

Speaker: David Montag

David Montag works as Field Engineering Manager at Neo Technology, the company behind the graph database Neo4j. In essence, he works to ensure the success of Neo's customers. David was part of founding Neo's Silicon Valley offices, where he worked for three years before returning to his native Stockholm to help Neo grow in the Nordics and Europe.

Neo Technology

Neo Technology was founded in Sweden. At Neo, researchers have pioneered graph databases since 2000 and have been instrumental in bringing the power of the graph to more than 40 Global 2000 corporations. Customers include Walmart, eBay, Cisco, HP, Accenture, Medium, FiftyThree, and CrunchBase. Serving customers in production for over a decade, Neo4j is the world’s leading graph database with the largest ecosystem of partners and tens of thousands of successful deployments.

Price: Free

Language: English

Contact: Benedikte Schaltz

 

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