A system for improving analysis of complexes in real estate asset management

Artificial Intelligence (AI) is increasingly used in many domains nowadays. Data used as input for such models are becoming a precious commodity. With the right tools, data can be transformed in valuable insights supporting decision making processes. In the current process of asset management, data for complexes is manually processed and analyzed by asset managers. The data that has to be analyzed is extensive and it is challenging to take into consideration all of the relevant information while determining a policy for a complex. A system that can improve the asset management process with machine learning methods can be developed. However, machine learning requires extensive knowledge in order to be able to create reliable and valid models and also a broad knowledge of the specific domain. Developing a system that has predefined data pre-processing methods for machine learning, and predicting new instances will enable the creation of models that can improve the asset management process by suggesting policies that should be applied. Also, an advising system that provides information and assistance regarding the various tasks of the process of creating a machine learning model will enable the involvement of the asset managers and their knowledge of the data.