Business Objective
Our client is a leading property management firm involved in buying and selling of Single-Family Homes to Retail and Institutional buyers.
The Client wanted to perform a comprehensive analysis and arrive at a solution to estimate cash flow for Rental Homes as a means to maximize their return on investment. They wanted the solution to also be able to estimate non-payment risk for each individual as well as estimate the maintenance cost associated with each property.
Challenges
- Reliance on a large number of public data sources
- Inconsistencies in spatial/location data
- Missing values and errors in historical maintenance data sets
Solution MethodologyÂ
- Cleaned and collated demographic, census, crime rate, neighborhood, cost of the materials, age of the building, maintenance records, and spatial/location data
- Maximized rental income by estimating vacancy as a function of rent using linear regression
- Estimated non-payment risk probability for a property by a linear and logistic regression hybrid model
- Estimated cost of maintenance using ARIMAX time series model
- Optimized and classified properties using the above 3 model outputs into high/moderate/low ROI buckets
Business Impact
- Using rental, maintenance history, macro-economic and demographic factors, accurately identify property investments across geographies as well as classify them into high, medium, and low ROI categories to help the client tap into opportunities that would enable quick and improved ROI
