Fighting fraud and other types of financial crime like money laundering presents a constant challenge for companies. Unfortunately, fraudsters are also becoming more sophisticated, which means fraudulent activities are only expected to increase in frequency, speed, and effectiveness. So how can you save your company from the next attack?
Legacy systems based on relational and other types of databases have shown themselves to be inadequate in detecting high-value fraud targets. Not seeing the real suspicious patterns, they often provide false positives, sending fraud analysts on fruitless investigations. And since it can take weeks to comb through data from multiple sources, fraudsters go undetected – until it’s too late. This inadequacy results in billions of dollars of economic loss every year.
That’s not the case with knowledge graphs, which have been proven invaluable for fraud detection and prevention. To discover how you can use knowledge graphs to fight high-value fraud, join us for this 30-minute on-demand webinar for a live demonstration of a knowledge graph-based fraud detection system using Neo4j's graph database and analytics tools. You'll also learn:
- What a knowledge graph is
- How to use knowledge graphs to detect suspicious patterns rapidly
- How knowledge graphs enhance fraud risk assessment, demonstrated with real-world examples
If you want to capture high-value fraudsters faster and more efficiently, be sure to attend this session.
Originally from the United States but now living in the United Kingdom, Joe has over 20 years of varied experience in the IT industry across a number of domains and specialties. Most recently, Joe has focused on technical pre-sales and solution architecture in the data and analytics space. When not geeking out over data and technology, he enjoys camping, tending to his garden and allotment, reading, and playing board games and RPGs. He also bakes a mean cheesecake.