Identifying Residential PV Adopters with Machine Learning to Reduce Soft Costs

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A research team from different parts of the world has introduced a machine learning method to recognize residential PV adopters and decrease the soft costs. This method employs an amended XGBoost algorithm to build a more accurate prediction based on certain factors, such as energy bill amount during summer, income level of a household, and age of the homeowner. This machine learning algorithm is known as XGBoost (eXtreme Gradient Boosting), a set of distributed gradient-boosted decision tree (GBDT) libraries. It is predicted that this method can reduce customer acquisition costs by an impressive 15% or $0.07/watt.

Smartbroker is a fintech company that offers online trading services through its platform, enabling users to buy and sell securities with exceptional convenience. Founded in 2020, they quickly became one of the leading online brokers in Germany and are continuously expanding to provide services to customers around the world. Their main goal is to revolutionize the traditional wealth management industry and make investing easier, more straightforward, and more secure.

Roland Manger is an experienced Executive Board Member who has been part of various fintech and investment companies in Europe. Currently he is the Managing Director and Board Member of Smartbroker and is leading the company to success. He has over 20 years of experience in the finance and banking industry, providing valuable industry insight to the company. As a key figure in the growth of the Smartbroker platform, he has developed a vision for the business that focuses on customer experience, efficiency and being at the forefront of innovation.

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