In order to manage or exploit a risk successfully, you have to understand it properly. It is not just a question of identifying a risk and plotting it on a risk map, it is a matter of really understanding how it might affect/benefit your business, what might cause it to occur, and the other risks it might influence or be influenced by. This is especially relevant to new businesses and wherever there is significant change.
Rental homes owned and operated by institutions didn’t exist in the USA ten years ago. Buy-to-let was something a few individuals did with a handful of properties. Institutions got involved in rented apartments but not houses. In the last ten years, it has grown from nothing to a $45bn business. The driver has been a fundamental shift in finances and attitudes; home ownership has become either unattainable or undesirable for many middle-income Americans.
The business model is to buy and rent out single family homes but the houses are selected using artificial intelligence programmes followed up by data modelling. One exponent is Main Street Renewal that focuses this modelling on middle-income suburbs and seeking out “fixer-uppers” – run-down properties in neighbourhoods that have affordable rents and a strong, diversified middle-income base. To date, they have found these in sunbelt cities (e.g. Atlanta, Dallas) or in the Rust Belt (Indianapolis, St Louis). When going into a new area, the analysis is backed up by someone from the company going and living in the area for a month before they consider buying any properties. They fix up the properties they buy using local crews, and owing to the scale of the business, they can purchase fixtures such as dishwasher, stove, fridge, etc at heavily discounted prices.
The potential rental is calculated using machine learning with the purpose of proving that they can achieve their desired yield on that property in that location after fixing the property up. It is only on the basis of fully understanding this risk, that they will go ahead and purchase the property.
Data source: Fortune magazine