After a while working in the real estate field, you may feel like you already have many tricks up your sleeve, but technology is constantly evolving and allowing companies to add tools to their operations that can help make the job easier and more efficient. That’s where Machine Learning (ML) comes in. ML is a part of Artificial Intelligence (AI), where a computer can collect data, and learn from that information without explicitly programming it to do so.
Every time we talk about technological and innovative tools, accessibility is always a factor. It´s certainly not going to be viable for most companies to develop their own technology, so finding a partner or solution to hire, from a company that has already made this investment should be on top of those companies’ minds. There´s always new companies uprising with this technology that is aiming to give you the tools that you need, you just have to evaluate whether they are a fit for your company.
The learning possibilities are endless, and you can clearly use this to your advantage; with the market changing day by day, ML can keep you abreast of trends before they happen.
Here are some of the ways it can help you and your customers make your job easier.
Lenders and insurance companies must run risk assessments, as in all other sectors, there are several risk factors that influence the final decision.
ML can learn and improve risk assessment processes more quickly; with the necessary information, it can optimize the process to be able to define if the client does not represent a risk, even if it does not have an adequate credit score. Freddie Mac and Lemonade, both insurance companies, already use this system.
Although it may not be one of their priorities, ML may know when is the perfect time to contact your past and potential customers, and adjust to their needs: do they need to sell? do they want to buy a new house? what neighborhood do they want to live in? ML can send the perfect message for every situation you need.
Finding investment opportunities
Researchers in Madrid developed a software that could find properties listed at a lower price than its actual market price.
Investors have to be two steps ahead of the competition, to know where the next big boom will be and invest before the others, but they also need to be aware of the risk factors that may be involved. ML can gather and discern all this information to finally give you a justified idea of where it is optimal to invest.
For example, Attom Data has collected information for 155 million properties, where several factors have been evaluated, such as neighborhood, natural hazard, environmental, school sectors, crime risk, etc.
Improving Comparative Market Analysis
Determining the true new value of a property can be very difficult with all the cumulative factors surrounding it. On many occasions, they are based on the past price of the house, but what is not taken into account, are the improvements to the public transport or of the neighborhood that can make an increase in the value of the property. ML, you can learn all the factors surrounding the property, and make a much more accurate estimate of it. ML, you can learn all the factors surrounding the property, and make a much more accurate estimate of it. It can do a scan of the entire area and its changes over the years, and see how the infrastructure, points of interest, transportation, etc. have changed to see how much the value of the property could affect in order to reach its ideal price
ML and AI are already being used in the Real Estate industry, it’s just a matter of time that they become a must in every company, and it can only be a good thing as it’ll make your job easier; Inman ran a test where “a broker competed against a computer to see who would make the best suggestions to a client, three different tests, three different days and the machine won the three times.” But it doesn’t mean that the brokers’ job will be made obsolete, it means that now you can have a tool to make your life easier.