Can AI make real estate a more liquid asset?

Can AI make real estate a more liquid asset?

7 September 2023


How automation can help asset managers have access to more immediate cash flow. Explore how Stonal’s AI-driven platform transforms data collection, processing, and decision-making, providing accurate insights and improving investment outcomes. 


Real estate is a tangible asset class, providing stability and long-term returns to investors. However, one of the primary challenges faced by real estate asset managers is managing liquidity in an inherently illiquid market. 

Illiquidity, when an asset cannot be sold quickly at the desired price, makes it difficult to meet investor redemption requests and seize time-sensitive opportunities. Fortunately, advancements in artificial intelligence (AI) offer promising solutions to address the liquidity problem in real estate asset management, providing increased efficiency, improved risk management, and enhanced decision-making capabilities.


So, what actually is the liquidity problem?

Real estate is an attractive investment opportunity because of its potential to deliver consistent income streams, while steadily appreciating over time. The difficulty is that properties are not easily converted into cash. This makes real estate a relatively illiquid asset class. 

The liquidity problem becomes particularly noticeable during periods of economic downturn or shifting market conditions when accessing capital becomes essential for survival and growth.

Traditional approaches to mitigating liquidity risks in real estate often involve maintaining substantial cash reserves or establishing lines of credit. However, these methods come at a cost and may limit the ability to capitalise on lucrative investment opportunities. AI in real estate offers a new avenue for liquidity control in asset management.


How do we use AI to tackle this?

Stonal offers an example of how AI in real estate can solve one of industry’s most persistent problems. The platform uses AI to change the way real estate data is collected, processed, and utilised. Acquiring real estate data from a clean source is central to fast and accurate decision-making, and therefore increases the liquidity of assets. 

Data quality impacts the accuracy of investment decisions, so by ensuring that the data fundamental to deals is high quality, real estate asset managers and owners are able to base their decisions on accurate information and secure optimal outcomes each time. Stonal’s AI employs advanced data collection via unique proprietary algorithms to verify the authenticity of the data before it even enters the platform. 

Real estate data has become fragmented: a result of manual, outdated practices that have allowed errors to slip through the cracks unnoticed. The streamlined data within Stonal’s clean data lake is reviewed against itself and accessible, meaning various parties across the organisation are able to see it. Without these steps of verification, asset managers start the decision-making process with bad footing.

Accuracy is king when it comes to investment decisions in real estate; and, inaccurate inputs can lead to flawed investment decisions. Utilising AI mitigates this risk by introducing standardised and accurate data as the algorithms analyse the data to identify trends, patterns, and potential risks. Real estate asset managers can therefore make data-driven decisions, without relying on guesswork. The culmination of the process is hastened as a result, combatting the liquidity issue that plagues the industry.  


What are the actual outcomes?

But, every journey must have a destination. By leveraging AI to face these issues, algorithms analyse historical sales data, market trends, and property-specific attributes to forecast property values. 

As such, asset managers are able to more efficiently gauge the potential return on investment, evaluate liquidity risks, and make more informed decisions on property acquisitions and disposition. Using predictive pricing models ends the guessing game that arises with poor-quality data sets, instead bringing confidence in evaluating property values and potential risks. 

This optimises your portfolio by adding more liquid assets, and in turn, drives profits. Stonal’s platform harnesses the power of AI-drive algorithms to analyse the risk-return profiles of individual properties, granting asset managers a cleaner, more granular understanding of their investments. 

AI in real estate is redefining the playbook for asset managers. By adopting Stonal’s platform, the long-standing liquidity challenges that have plagued the industry become less persistent. In an uncertain market, making decisions based on clean data is essential to ensuring your portfolio remains competitive.

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