Background and Challenge
Real-estate business is booming. In the first quarter in 2021 alone the volume of transaction was about 10.2 billion EUR in Germany . On the other hand, climate protection is one of our biggest issues, and, worldwide, emissions of buildings are responsible for 38% of the carbon dioxide output. Hence, so called green buildings are becoming increasingly more important . In a first step, we therefore want to figure out the relevant energy-oriented refurbishment factors driving the price.
Furthermore, for each real estate being sold the right buyer has to be found. Unfortunately, this still need involves a number of manual tasks. Therefore it is an interesting and challenging algorithmic problem to tackle.
Despite the increased number on PropTech-Startups, digital solutions establish themselves just slowly. In cooperation with Valyria Technology GmbH (Valyria), we seek to push innovation capacity. In particular, we want to understand how energy efficiency and an increase in the value of a real estate involve each other. Furthermore, knowing the needs profile of the possible buyers on the one hand and having the property characteristics on the other hand, we then want to find suitable buyers for the properties.
Given millions of real-estate valuation data and scientific freedom, we aim to enhance the current valuation process and tie in at several points.
As the core goal of the project, we want to investigate and understand the influence of environmental, social and corporate governance (ESG) criteria. In particular with respect to the climate crisis and sustainability we want to figure out which factors are driving the price. Furthermore, we want to understand how ESG criteria change the forecast regarding the price development.
Secondly, only the offers that are most relevant to interested buyers and sellers should be suggested. To this end a conception of a matching algorithm is necessary which maps interested buyers to fitting objects. In a first step it is important to determine the relevant factors influencing the decision. Afterwards, the right matching has to be found.