Growing patent portfolio underscores’s leadership in enterprise AI announced it was recently awarded its third patent‚ extending its leadership in enterprise AI. The company received a U.S. patent for a machine learning technique that helps energy providers identify non-technical energy loss‚ including theft‚ fraud‚ and billing errors.

Non-technical energy loss is a significant problem for energy companies‚ resulting in $96 billion in lost revenue per year according to a 2017 study published by Northeast Group‚ LLC.

Conventional approaches to detecting non-technical loss often require significant manual effort‚ leading to efficiencies and inaccuracies that produce unnecessary expenses for energy providers and their customers.

The patented machine learning method‚ used in the C3 Fraud Detection™ application‚ analyzes data associated with energy providers‚ customers‚ utility meters‚ and other aspects of energy distribution and management. The analysis determines properties or characteristics associated with non-technical loss.

By pinpointing likely instances of non-technical loss‚ providers can focus investigations and reduce costs. Energy company Enel is using C3 Fraud Detection to transform its approach to identifying and prioritizing non-technical loss‚ with a goal to double the recovery of unbilled energy while improving productivity.

Patent details are available in the United States Trademark and Patent Office database.