inspkt Data Analysis
The system collects traffic data from the data sources predefined in the system, applies data profiling and analysis, timely detects and reports fraudulent cases, generates alerts, and executes actions on the operators’ network elements accordingly to stop the identified fraud attacks and prevent future attacks from the same sources.
The detection mechanism can work in real-time if the operators will to deploy our network monitoring probes, inspkt probes, as data sources that feed the system or in near real-time if the data is collected from the operators’ network elements.
It’s in our product roadmap to deploy machine learning as part of the system to strengthen and support the fraud detection algorithms and strategies.
- Addresses telecom fraud in real-time
- Provides faster, sharper, earlier and smarter telecom fraud detection mechanism
- Deploys a dynamic rule-based engine to create an unlimited number of rules to handle any type of telecom fraud including:
- Wangiri attack (one-ring scam)
- By-pass fraud
- Call spoofing
- Roaming fraud
- Subscription fraud
- SIM cloning
- Any type of IRSF fraud
- Operator’s internal fraud
- Actively alerts concerned teams about detected fraudulent attempts through various mediums (SMS, emails, system notification, etc.)
- Applies automated blocking commands on the network elements
- Updates the blacklist with the newly detected fraud sources to prevent future attacks from the same sources
- Provides a dynamic reporting engine with built-in and ad-hoc reports and live dashboards
- Can be easily customized and configured to detect any new fraud threats jeopardizing the operator’s business, improving the response time to these threats
- Proactively protects subscribers, achieving customer satisfaction and therefore customer retention
- Incorporates a bridging module for smooth integration with third-party systems