Harnessing the Power of Data to Identify Fraudulent Water Usage - Data Matters

For a country that holds 12 percent of the planet's water supply, Brazil faces significant water management issues. In addition to its commonly known sanitation problems, the country's infrastructure lends itself to distribution issues, including fraudulent use. Fraudulent water use can be particularly hard to track and identify, and often goes unaddressed for significant periods of time – especially in highly populated areas where physically checking people's homes and water meters isn't an option. Instead, companies need to find ways to swiftly identify and eliminate fraudulent water activity which impacts an already scarce supply and costs communities money. To address this challenge, a utilities company from Mato Grosso, Brazil recently worked with a group of data engineers at ScientificCloud. The goal was to develop a solution that could better locate fraudulent water usage by tracking data patterns based on home location and property attributes. As a Sao Paolo-based data science company that develops and deploys machine learning (ML) and artificial intelligence (AI)-powered applications, ScientificCloud understood these problems first hand.