20 / 06 / 22 - 2 minute read
However, the current market environment feels like a mix of actors with a clear mindset between “business as usual” and “it is now or never.” In other words, new technologies are not being equally adapted by the industry. This is indeed a strong assumption and a disruptive thought at the same time. Still, real estate today requires the ability to deal with digitalisation, machine learning (ML), tokenisation, and IoT, to name some. These concepts are certainly in vogue and represent the real estate industry's increasing need to add a new pillar to the foundation: real estate data intelligence.
The past decade has shed light on one of the industry's darkest problems: lack of data. The real estate industry is more the rule than the exception regarding a lack of transparency. Perhaps, therefore, data collection has been the focus of many think tanks. One might think that the increase in information would lead to greater transparency, more accurate pricing, and, finally, more efficient markets. But the opposite seems to be the case.
Marcelo Cajias heads the Data Intelligence section, which is part of the Investment Strategy and Research team at PATRIZIA. In his role he is responsible for the global portfolio of analytical solutions and dashboards that support strategic investment decisions by means of observed and unobserved machine learning forecast models for various asset classes. Marcelo studied business administration at the University of Regensburg in Germany, majoring in statistics, econometrics and real estate economics.
Anett Wins is the data scientist responsible for building and estimating statistical models to find hidden patterns and indicated trends. To answer predictive and prescriptive research questions, she applies advanced machine learning algorithms.