Using graph-based features to get a quantum leap in fraud detection

Despite spending $1 billion on fraud detection software each year, fraudulent activity still costs banks over $50 billion annually in a rising trend that doesn't appear likely to change!

Sophisticated financial criminals are constantly changing their tactics. AI-based detection systems, dependent on large training sets of historical data, may be good at catching the low-value frauds but may struggle to pick up on the newest highest-risk approaches.

In that case, you need a system that gives your seasoned fraud professionals an easy and quick way to pull together a 360-degree view of the people, accounts, transactions, and communications of suspicious actors, so you can react before they take too much.

This talk will explore how graph databases can help improve your AI-based detection systems and give you tools for intelligent investigation, transforming your ability to respond to fraud and sending a strong message to organized criminals to leave your bank alone.