A fraud detection API is a prerequisite for any online business that wants to mitigate risk and detect bad actors in real time. These API tools allow businesses to screen users, payments and other important action points for fraud at every step of the user journey from account creation through checkout and payment. They can help businesses identify and block fraudulent payments, fake accounts, chargebacks, bad users, bots, account takeover (ATO) and more.
The most advanced fraud prevention systems combine a variety of different algorithms to spot patterns and flag anomalies. Some of the most popular are machine learning, pattern recognition, and behavioural analysis. They use data from a number of sources including previous fraudulent activity, user behaviour and risk scores. By collecting a large quantity of labelled data and giving it rapid feedback to the system the algorithms can learn over time and become more accurate.
However, despite this sophisticated approach to detecting fraud, criminals are constantly finding ways around rules-based models. This means that rules-based fraud detection systems need to continuously update and expand their library of known fraudster behaviour. This makes them slow and imposes a heavy maintenance burden on human fraud analysts.
As a result, many online businesses are turning to fraud detection API as a way to avoid the cost and inconvenience of manual document reviews, identity checks and other antiquated methods of preventing fraud. APIs provide a faster, more accurate and more flexible method for screening data than existing methods. They can be programmed to look for fraud in a specific way by using custom fields or data feeds.
For example, a fraud detection API could be programmed to flag any transaction that has a small amount immediately followed by a large amount. This would be possible by partitioning a data stream with a keyBy operator and adding a process() call to each of the partitions. This function could then be called by the fraud detector on the keyed context. The fraud detector could then output an alert if the transaction was flagged.
This kind of customised fraud detection is possible because the fraud APIs offered by SEON are designed with flexibility in mind. SEON’s APIs are fully documented and provide a codebase that can be used to quickly configure the fraud detection functionality for a specific business need. This way a developer does not have to learn all the full ins and outs of a full fraud engine but can simply implement the functions they need to work with their own data and API interfaces. This also helps developers reduce the amount of time they spend on maintaining the fraud detection API and frees them up to focus on other parts of their project.