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Will technology make real estate investing less risky?

Technology is rapidly changing real estate transactions and investing. From mobile apps that can help you rent out your space to finding a new home by scrolling through your social media feed, technology is growing and, so are the real estate tech consulting services.
In fact, with the help of apps and other technology, it’s easier than ever for buyers, sellers, and even real estate agents to speed up the marketing and transaction process, and this trend shows no signs of slowing down. Real estate investors (or those who wish to be) are now benefiting from technological advancements as well.


Cap rates during the previous 6-12 months are commonly used by appraisers. Unfortunately, when the bids come in and the buyer is chosen, the exact value is generally decided some months before the closing. The best predictor of the market is the buyer’s choice. Investment firms who are actively bidding on and selling properties and have the technology to follow and analyze the sales may have a competitive advantage in the future by detecting market shifts up to 18 months ahead of the appraisal sector, which normally depends on older data.
The cap rate is also unreliable because it does not indicate whether the metrics are being applied to forward or trailing data, if there is an adjustment for any increase in real estate taxes after closing, or if there are any adjustments to capital requirements, reserve levels, and so on. Cap rates can readily swing by 100 basis points as a result of these factors. Technology, on the other hand, may take a comparable sale and rebuild the financial pro forma to fully comprehend the sale’s parameters.
Finally, appraisers are human, which means they don’t always have total objectivity. Appraisers were frequently chastised in the run-up to the 2008 financial crisis for being unduly swayed by their clients out of fear of economic retaliation. Using machine learning and big data, technology can provide a more objective valuation for real estate investors, which should be the goal of any appraisal.

Research With Large Institutes

These organizations are primarily employed as an internal check and balance to ensure that ambitious acquisitions officers don’t overestimate their numbers. Many big institutions’ rental growth rate assumptions are governed by research departments, which typically rely on a combination of output generated by three or four market prognosticators through quite complex financial modeling.
Regrettably, the models do not always adequately capture the small differences in submarkets that might create value. For example, analysts may predict that office rents in New York City will rise by 3%, and 2% during the following three years, respectively. That may not capture market-moving events on a local level.

Competitive Edge

As previously said, technology now exists to generate a complete financial pro forma for practically every apartment community in the US by merely entering a street address. Revenues can be extracted in near-real-time from various market data providers or straight from specific community websites using data scraping technology. The costs can be calculated using a combination of existing portfolio inputs and market data services. In addition, machine learning algorithms can swiftly identify the competitive set for a specific residential community
As technology in this sector advances, we should be able to track the performance of apartment complexes in real-time in comparison to a competitive set, similar to how the hotel industry uses STAR reports. Recognizing if an asset is underperforming or exceeding its competitive set in real-time will be a powerful asset management tool. Avail for real estate tech consulting services for more information.


One of the drawbacks of publicly-traded REITs is that they typically lose the benefit of real estate diversification and are more closely associated with equities than real estate assets. Analysts can better track the value of the underlying assets relative to the stock price using real-time valuation technology powered by Big Data and machine learning, which is now accessible for the multifamily sector. It can take minutes to appraise a large portfolio instead of days, and it can tell an analyst if a public REIT is a buy or a sell.

Data Balance & Underwriting

When we evaluate a possible real estate investment, we look at three things: the pro forma from our operating partner, our internal underwriting, and the output from our machine learning algorithms.
Most financial pro-forms are generated by junior analysts or colleagues who do not have the benefit of investing through cycles. An analyst or associate had never witnessed a market slump, and in 2011, an analyst or associate had never seen a market upturn. We know that changing a few critical variables in a model can swing the IRR hundreds of basis points in either direction. Technology can provide critical checks and balances to ensure that “Animal Spirits” do not have an undue influence on underwriting.

Indexing Technique

Modern technology may be used to scan a market and discover which residential communities are underperforming the market and may provide an opportunity to acquire and create wealth. We are confident that in the future, individuals who have access to this type of technology will be separated from those who do not.

Final Words

We don’t think technology will ever be able to entirely replace human decision-making in the real estate investment process. However, we anticipate that in the future, technology will play a larger role in the acquisition and asset management responsibilities.
Technology is ruling right now. In the pandemic too, due to technology and digitalization, everyone was connected. However, technology is going to change the real estate sector too in a positive way. For more such information, contact a reliable real estate tech consulting services provider.

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