Fraud detection company is an essential part of a company’s loss prevention strategy and, in some cases, can be considered a component of anti-money laundering (AML) compliance processes. It requires a mix of technological tools, subject-matter experts (especially analysts), policies and procedures, and data analysis to function effectively.

While fraud detection isn’t a comprehensive solution to all business risks, it can significantly reduce the number and size of losses and help ensure regulatory compliance. However, it’s important to note that fraudsters continuously hone their attacks, so it’s critical that businesses regularly examine and update their fraud detection systems.

Supervised and unsupervised methods of fraud detection rely on the characterization of abnormal events to identify fraud risk factors. For example, some document fraud detection software may use machine learning to identify how particular documents like bank statements or pay stubs typically look and then scans new ones to determine if there are any anomalies in the font or format that indicate potential fraud.

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Other solutions use a combination of data analytics and predictive modeling to identify the likelihood that a given event is fraudulent. These systems can then alert the appropriate person to take manual action to prevent the fraud from taking place, whether that’s canceling a transaction, refunding money, blocking access to an account, or even pursuing legal action. A good fraud detection system can also provide peace of mind for customers, encouraging loyalty and creating a positive brand reputation.