This research provides fundamentals for generating a (semi-)automated standardized technical and legal assessment of buildings. Based on original digital building documents from (institutional) investors, the potential for digital processing and automated classification and information extraction through machine learning algorithms is demonstrated. Preferred sources for key information of technical and legal due diligence reports are presented. The research project concludes with challenges towards an automated information extraction in DD processes. The findings are helpful for improving DD processes and more generally, promoting the use of machine learning in real estate professional services, which are reliant on classified and prioritized documents.
The project is sponsored by the Property Research Trust.