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Energy Fraud Detection

Predict and prevent fraud through real time monitoring and anomaly detection.


Energy companies have witnessed growing fraudulent behavior, with customers illegally attaching to distribution networks. Lack of control over such events can lead to losses and accounting troubles. Detecting fraud and reducing losses is a key goal for audit managers of energy companies, they need to quickly identify and stop improper behavior, but also identify new behavior, whose risk was previously unknown, and therefore not related to losses.

Energy Fraud Detection is the advanced analytics application that helps utilities identify risks of fraud or improper behavior resulting in losses. Through a mix of business rules, anomaly detection and predictive analytics, the application identifies risky behavior, giving a fraud risk score to any event.

Specific Services

Energy Fraud Detection leverages advanced analytics to support audit managers, area managers and sales points with insights on fraudulent behavior. The application contains a predefined set of business rules related to the Energy market, based on Accenture’s deep industry knowledge. Utilities now have the ability to add new rules according to their experience, and their business knowledge, to spot new unethical behavior. The ability to define risk matrices allows the user to choose which components to use, and what weight to give them in the evaluation of risk.

Key features

  • Use of all available information to fight fraud
  • Real-time checking and scoring
  • Alert, e-mail, and report management based on deterministic rules
  • Predictive models for customers or risk score

Why Accenture

The scalable Accenture Insights Platform includes resources applications, providing fast and easy access to an array of industry and functional applications that bolt onto the platform. Utilities, in turn, achieve quicker time to market and more rapid results.

Utilities also benefit from Accenture Analytics’ wide range of capabilities rooted in:

  • Industry knowledge. The validity of our advanced analytics outcomes is underpinned by our deep knowledge of the sector.

  • Business. Applications are designed for business users and focused on business results, minimizing the complexity often related to advanced analytics. Getting to accurate outcomes does not require users to have statistical, mathematical or IT knowledge.

  • Flexibility. Applications are based on a framework that can be easily integrated in an enterprise operational environment to enable business process action.