This project investigates the application of machine learning to support the evaluation of electricity prices and tariffs in Switzerland. ElCom is Switzerland's independent regulatory authority in the electricity sector. ElCom is responsible for monitoring compliance with the Swiss Federal Electricity Act and the Swiss Federal Energy Act, taking all necessary related decisions, and pronouncing rulings where required. ElCom monitors electricity prices and rules on disputes relating to network access. Additionally, it observes electricity supply security and regulates issues relating to international electricity transmission and trading. ElCom is responsible for ruling on disputes concerning feed-in tariffs and between network operators and independent producers (approx. 650 organizations). The operators' electricity tariff is determined by factors such as types of power stations, grid size, and many more. While the organizations propose prices for each year, ELCOM has to assess the validity of each suggestion. In this project, we want to explore the application of machine learning to support ELCOM employees in their evaluation process. More specifically, we want to apply Anomaly Detection and cluster analysis to identify abnormal tariff suggestions.