We usually hear about artificial intelligence (AI) being used to improve self-driving cars, but AI and Machine Learning (ML) are well on their way to transforming the investment management industry. We have already seen it impact retail investing, highlighted with the rise of robo advisors looking to displace expensive financial advisors. Firms like Wealthfront and Betterment pioneered the wide adoption of AI as a means to build retail investor portfolios, and more recently, Schwab launched its own version to bring robo investing into the mainstream.

The benefits of AI aren’t limited to just stocks and bonds — we are increasingly finding these same tools and strategies being used in the alternative investment world, often with even greater impact. Forward-thinking fund managers are transforming the way they evaluate real estate, in particular.

The journey these technologies take to get to a point where they impact industries always starts with the same first step: the availability of raw data. From the data, we form standardized metrics, then customized analytics, and ultimately optimization processes that drive investment decisions.

Over the last 10 or so years, there has been an explosion in the availability of real estate data. Retail investors have unprecedented access to information through sites like Zillow and Redfin. Outside of typical owner-occupied mortgages, however, the industry still lacks standardized metrics. As a result, comparing various offerings to identify undervalued opportunities is a challenging and onerous process. With so much data but so little structure, we’re starting to see the real estate investment industry skip ahead and adopt AI much more quickly than we saw in traditional asset classes.

Investing well in real estate takes numerous factors into account. The fact is, it’s almost impossible for most traditional investors, whose best tool is usually Excel. The consequence is overpricing and thus overheating of what are seen as obvious opportunities (e.g. many of LA’s luxury neighborhoods) and ignoring lesser-understood offerings (e.g. secondary markets, which often command a large unwarranted risk premium). ML provides an incredible solution.

Tech’s Impact on Your Investment Strategy

Fund managers are now using predictive analytics produced by ML to surface investment opportunities. For many lenders, for whom downside protection is paramount, they’re focused on harnessing the power of AI to give them an early warning system for at-risk investments.

Instead of waiting to hear from a wave of borrowers requesting loan extensions because they can’t offload their fix-and-flips, firms can track neighborhoods and regions to see that days-on-market is expanding (i.e. homes are taking longer to sell). They can act preemptively to shift where they lend to markets that are still heating up. Funds able to predict loan defaults ahead of time are in a better position not only recover their principal by restructuring the loans, but also identify additional distressed investment opportunities from lenders unable to see around the corner in the same way.

Over the past three to five years, FinTech has opened up a number of previously inaccessible alternative asset classes. Markets like bridge loans, life insurance settlements and cross-border trade finance are slowly making their way into more investor portfolios (for regulatory reasons, these are typically limited to accredited investors). New markets often have enormous amounts of disorganized and unstructured data, which leads to tough underwriting and less liquidity. Consequently, you’ll also often find attractive returns in these relatively untapped asset classes. Using AI and ML, institutional investors can identify where (outsized) returns are in these previously murky investments, opening up entirely new asset classes to add to client portfolios.

Where Will AI Take Real Estate?

AI gets particularly interesting when we take real estate investments beyond single opportunities and into portfolio construction. You might be excited about a rental home you own in your hometown, but what if you wanted a portfolio of loans from around the country? Thoughtfully building such a portfolio by hand would take a tremendous amount of time for even an experienced investment professional.

AI can automate this process by monitoring the numerous factors that go into evaluating any single real estate opportunity and using that massive data set to build a diversified portfolio. Instead of simply being invested in many loans, portfolios will be assembled strategically across markets that do not all move together when we see changes in factors like oil prices, unemployment or economic growth. From there, AI can take the next step and continually rebalance portfolios to maintain diversification as the world changes.

Despite many of our fears and hesitations, AI is already reshaping the investment management and real estate industries. The majority of stock trades today are automated. Robo advisors have given us the ability to build sophisticated portfolios at a fraction of the cost we used to pay. Alternative investments are next, with real estate leading the way. The future is here, and it’s bringing more elegant solutions at a lower cost than any time in history.

Ray Sturm is the CEO of AlphaFlow, which helps investors manage personal portfolios of real estate.

house Despite many of our fears and hesitations, AI is already reshaping the investment management and real estate industries. Photo: Pixabay