Enterprises lose billions of dollars a year due to fraud. Bogus payments, money laundering, loyalty program fraud and cyber security incidents, just to name a few. Enterprises have explored a wide variety of ways to combat fraud, including hiring additional staff which has proven ineffective. It’s time-consuming, and nearly impossible to investigate every claim. The perpetrators of fraud are highly sophisticated, and their techniques evolve quickly, often making solutions obsolete just as soon as they’re implemented.
Comarch Fraud Protection software significantly increases the efficiency of suspicious event detection compared to rule-based methods. The solution is based on machine learning, which is a state-of-the-art approach where Artificial Intelligence (AI) is used for creating models that, based on historical data, can determine the occurrence of suspicious events with high accuracy.
For many years, the use of rule-based information systems has been a sufficient, though not too effective, approach to detecting various types of fraud. However, fraudsters eventually began to use more advanced methods that beat rule systems. To effectively prevent and detect fraud, it is no longer enough to apply a set of rules. Artificial intelligence comes to the rescue. Using historical data and machine learning, you can search for unusual events, detect anomalies incomparably more efficiently. What's more, over time and with changing patterns of digital crime, the Comarch Fraud Protection system can learn new user behaviors on an ongoing basis. In this way, enterprises can try to foresee the intentions of fraudsters.
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