HexaCorp partnered with an energy services provider to address a critical issue of electric meter tampering, which led to significant revenue losses. Leveraging advanced technologies like SAP HANA, FileNet, and machine learning, HexaCorp developed and deployed a robust solution to detect and prevent tampering in real-time.

• The client faced widespread electric meter tampering, where users manipulated meters to record lower energy consumption than actual usage.
• Such activity not only caused substantial revenue losses but also undermined the integrity of their billing process.
• The company required a scalable, data-driven solution to accurately detect tampering instances and ensure proper billing for all customers.

• Identified and integrated data sources relevant to meter tampering, including meter readings, customer information, and usage patterns, into SAP HANA and FileNet.
• Defined key performance indicators (KPIs) for energy usage patterns to identify anomalies indicative of tampering.
• Built a centralized data lake in SAP HANA and FileNet to store and manage meter readings, customer details, and other documents related to tampering cases.
• Trained a machine learning algorithm using TensorFlow with SAP HANA to establish baseline “normal” energy usage patterns.
• The algorithm was then deployed to detect real-time anomalies, flagging potential tampering incidents.
• Configured an alert system and case management workflow using FileNet to enable proactive action when anomalies were detected, ensuring quick resolution.