Ento
Case Studies
AI-Driven Energy Optimization in Retail Banking: A Case Study of Arbejdernes Landsbank
Overview
AI-Driven Energy Optimization in Retail Banking: A Case Study of Arbejdernes LandsbankEnto |
Analytics & Modeling - Machine Learning Sensors - Utility Meters | |
Buildings Retail | |
Facility Management | |
Building Automation & Control Inventory Management | |
Hardware Design & Engineering Services System Integration | |
Operational Impact
The implementation of Ento's AI-based solution has led to significant operational improvements at Arbejdernes Landsbank. The system's ability to automatically identify and prioritize potential savings has streamlined the bank's energy management process, reducing the burden on the Facility Management team. The solution has also improved the indoor climate in the bank's buildings, which has had a positive impact on the bottom line. Furthermore, the system's ongoing automatic monitoring capability allows the bank to quickly identify and address unexpected changes in energy consumption, helping to avoid larger, unexpected increases in energy consumption. | |
Quantitative Benefit
The bank's energy consumption and climate footprint were reduced annually by more than 100 tonnes of CO2e. | |
This reduction corresponds to 16% of the bank's total consumption. | |
In some buildings, consumption has fallen by more than 50%. | |