Telecom Operator leverages Big Data for Real-time Fraud Detection

About Client

The client is a leader in IP networking technology, with a strong track record in developing and deploying next-generation carrier-grade Session Border Controllers (SBC), pushing the envelope in an all IP paradigm. The client has a global presence with its SBC boxes used globally by leading Telecom Operators.


  • Network operators (the client’s customers) were losing a large amount of money because of fraud. The client did not have sufficient infrastructure to support running complex clustering algorithms to identify and detect fraud.


To build a system that allows storage of large amounts of call data on a single SBC box and be linearly scaled to accommodate data for more than a year. The system should leverage data to generate fraud patterns, and identify any fraudulent activity. For this, the system needs to provide real-time reports and dashboards for monitoring fraud and other key quality measures. However, additional challenges include

  • Large volume and data velocity (over 10,000 calls per second)
  • Complex application data (flat files, Google protocol buffers, nested data structure)
  • Limited Resource on SBC Box, scalable with node addition

Our Solution

  • A big data platform was needed to fulfill the ambitious requirements of the client
  • Apache Spark with Parquet columnar storage was selected for compression
  • Elephant Bird and Java were used for Google Protobuf Processing
  • KVM Virtualization of SBC Server to run multiple nodes with redundancy
  • Real-time scaling with addition of physical nodes
  • Unsupervised clustering & supervised classification for pattern recognition
  • Statistical parameters such as average length of call, average number of calls per month and average delays in bill payment
  • Real time fraud detection and alerting


  • The client is now able to retain and report data for 1 year on the same box instead of 1 month’s data.
  • The client was able to monetize the big data platform by adding advanced reporting features.
  • Fraud management was introduced in the product for identifying pre-defined fraud patterns in real time and report to the operator.

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