Optimize and manage your real estate investment decisions with alternative big data and artificial intelligence.
Real Estate Pilot was built to support asset managers to better analyse, manage and forecast their real estate portfolio. The solution uses over 20,000 factors from financial markets, macro-economic data, and alternative real estate data. The solution globally covers real estate investments and enables a user to get a cutting-edge tool to boost performance in returns and output (e.g., reporting obligations).
1. Increase analytical competences in a wide range of Commercial Real Estate markets
Real Estate pilot can automatically identify from 20,000 factors which are the most relevant for a location (e.g., City or Country) and a specific object's (e.g. hospitals, office) value changes. The AI inside of the Real Estate Pilot analysis billions of possibilities among these factors until the main positive and negative contributors per object are identified, explaining e.g., 95% of the value development. The following output can be requested per location and object:
Part of the 20,000 factors are location specific, such as GDP or # of offices closing. These can be determined with Real Estate Pilot. Since each location has a different composition of the main value drivers of the corresponding real estate investment, AI is needed to select per location the relevant factors since there are billions of possibilities.
2. Real Estate Pilot is further used to better understand the future value development of a single object or a multi-object real estate portfolio. A key part of the forecasting is the ability of the tool to understand the macro and the microenvironment of a specific portfolio. Thereby, classic macro models are combined with real estate micro models to get deeper insights into the expected real estate market development. Any result can be drilled down since an "explainable AI" was developed on top of the underlying AI that scan's the real estate market.
3. Real Estate Pilot is also a very powerful tool to better run most modern risk management on any portfolio since it decomposes a portfolio into the main drivers and can further understand on a monthly rhythm value change. This feature is often used as an early warning system for better sales or purchases, during price negotiations or in general for strategic decisions.
Technology: Artificial Intelligence/Machine Learning, Cloud Computation, Big Data including alternative data