Fraud is a serious crime and can cost your organization a lot of money. But it’s not just the sum of its monetary impact: fraud can also lead to lost market position, damaged reputation, low employee morale and lawsuits.
Fraud can take many forms, but there are two common characteristics: pressure and opportunity. Pressure is the force that drives a fraudster to commit an illegal act, like stealing money or falsifying an expense report. Opportunity refers to the criminal’s perceived ability to commit a fraud scheme, such as a phishing scam, lottery or sweepstakes scam, investment fraud, identity theft, chargeback fraud, tax fraud or employment fraud.
Criminals are constantly experimenting with new ways to circumvent existing fraud detection systems and are creating and using more complex schemes. For instance, they can use a synthetic identity to trick the system by combining real and fake elements. They can also collaborate with multiple accomplices to scale their attacks and evade detection.
To fight fraud, you need to understand the patterns of these new threats. Graph algorithms, which analyze the way data points, called nodes, are connected, can help you discover hidden connections in your data and identify suspicious activity. For example, if one of your clients is indirectly connected to a politically exposed person, a pathfinding algorithm can reveal this. Similarly, a centrality algorithm can show you who is the most likely ringleader in a group of fraudsters. Then you can improve your fraud detection and prevention strategies accordingly.
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