Panamax’s fraud management solution is a comprehensive fraud detection and mitigation solution, including advanced analytics. It utilizes both Artificial Intelligence and Business Intelligence to protect the networks. It merges usage records, information from the signaling networks, subscriber, and dealer profiles, and looks through interconnect, roaming, prepaid and post-paid scenarios to identify unusual usage, trends, behaviours, anomalies, and patterns.
the critical success factor defined were:
· Identify and prioritize the cells with call drop issues based on rules provided by the operator.
· Based on rules specified, provide relevant indicative information to network engineers that might have caused the issue in the particular cell.
· Provide a 360-degree view of network KPIs to the network engineer.
· Build a knowledge management database that can capture the actions taken to resolve the problem and
· Update the CRs as good and bad, based on effectiveness in resolving the network issue
As a huge data was getting created, the database used was Hadoop -Big Insights.
Data transformation scripts were in spark.
And the neural network was the ML technique used to find out the system parameters when historically alarms (the indication of network failure) in the system got generated.This information was fed as a threshold and once in the real scenario the parameters start approaching the threshold, the internal alert for those cell sites get generated for the Network engineer to focus on as preventive analytics.
More info: computer systems engineer