A fraud detection solution is used to identify high risk online transactions. It helps organizations maintain their customers’ trust by blocking fraudulent activities.

The first thing to know is that there are three main types of fraud detection solution. They include static rules, machine learning, and AI-driven solutions. Each has its own advantages.

Static rules are the simplest type of fraud rule. Typically, these rules use simple if/then logic. For example, if a user’s IP address is blacklisted, he will not be allowed to use your site.

Machine learning is a more sophisticated approach that relies on neural networks. It works best with large amounts of transactional data. Unlike static rules, it can detect complex behavioral patterns early on.

AI-driven solutions utilize neural networks to detect and block fraudulent transactions. Neural networks are able to distinguish between legitimate and illegitimate transactions, allowing businesses to avoid costly losses.

RapidMiner enables businesses to quickly find fraudulent behaviors before they happen. With real-time data processing, there’s no need to manually review each transaction. Identifying fraud before it happens can save businesses millions of dollars in fraudulent costs.

Ocrolus Detect uses artificial intelligence to analyze document content and detect tampering. This can help lenders make faster lending decisions.