Fraud prevention platform for effective enterprise risk management
Neural Technologies’ Fraud Management solution provides enterprises with a powerful fraud prevention platform to reduce revenue loss. It protects businesses from a wide range of fraud types, delivering a vital enterprise risk management solution to tackle revenue leakage through fraudulent activities.
The Optimus Fraud Management product leverages sophisticated neural network technology that analyzes and identifies fraudulent behavior in near-real-time. The highly-customizable nature of the platform, combined with adaptive fraud management approach, make it applicable to use cases across multiple industries and verticals. Use cases include focus areas in telecommunications such as PABX fraud, bypass fraud, and Simbox fraud.
Customizable fraud detection
Optimus Fraud Management provides a customizable fraud prevention solution for end-to-end fraud management. It enables operators to profile and monitor all prospective customers during on-boarding, identifying risk factors and likely fraudsters prior to providing services. Existing customers can be continuously monitored in their day-to-day activities, with the Optimus Platform identifying and highlighting suspicious or anomalous behavior in near-real-time.
The AI/ML-driven platform can also be configured to monitor internal activity, providing an important solution for internal enterprise fraud detection.
Link analysis technology provides a key component for fraud prevention, particularly in on-boarding of new customers and questions of subscription fraud or bad debt. This complex analysis identifies risk factors across linked datasets for known fraud cases, and is able to uncover emerging fraud rings by identifying shared risk factors within a network.
Data mining tools provided by Optimus Insight can enable advanced case management and investigation, providing key business intelligence on emerging or existing fraud threats. It enables enterprises to manage and monitor their enterprise risk management, allowing ad-hoc queries for transactional data as and when is required.