Fraud Detection

The solution identifies over fifty of the most prevalent payment fraud scenarios faced by banks and other financial institutions through the millions of transactions they process every day.

The product detects and flags fraud typologies including Account Take Over, Authorized Push Payment Fraud, Synthetic Identity, and Relationship Fraud. Fraud Detection advanced capabilities can also identify unknown risks, such as fraud typologies that do not match current rule based scenarios.

When businesses receives an alert to suspicious activity, it comes with a full explanation, streamlining the transactions resolution. For example, a transaction could have been flagged because it followed a failed password attempt or because it was at a time of day that was not in keeping with the customers location.

The solution uses AI and machine learning algorithms to monitor monetary and non monetary events and look for patterns that indicate possible risks. This includes identity clustering, using behavioural and personal characteristics to identify accounts that are, for example, controlled by a single individual. It also combines financial and non financial events with natural language processing and machine learning, meaning factors such as location and time can be used to identify suspicious transactions in real time.