Predictive Analytics
For a Tech Aggregator in Real Estate
CLIENT & PROBLEM STATEMENT
- The client based out of UK is a Tech Aggregator in Real Estate with interest in Investment Banking too.
- The underlying Client was evaluating buying a pool of Greece properties with help of our Client.
- The Client wanted to Construct a mathematical model to predict the Price and Rent of the Properties in Greece.
- The predictions were to be data driven using data from various public sources. Price and rentals were to be predicted for each property in the portfolio.
APPROACH
- We trained data collected from public sources.
- We cleaned data, corrected for outliers, blanks and erroneous values. We binned certain variables like floor, build year etc and got small number of bins.
- We evaluated several models, performed feature transformations, analyzed relationships and statistical properties.
SOLUTION & OUTPUT
- G-Square selected the best performing model (outside training sample), built models for confidence interval and applied on final data.
- We predicted price, rentals and confidence intervals for each property and overall portfolio.
- This information helped the client make informed decisions about purchasing the property pool, as they had a clear understanding of the potential returns on investment.
