Artificial Intelligence In Wealth Management

Artificial Intelligence In Wealth Management : Real Estate & Lending

Artificial Intelligence In Wealth Management : With the recent proliferation of artificial intelligence, many ask if AI can be widely used in real estate. Real estate has mostly been a traditional industry and is frequently late to adopt new technologies. In fact, according to Morgan Stanley, real estate is the second least digitized industry.

Past data and transactions are commonly stored on paper rather than digitally or in a shared server or database. This means that it would be difficult to feed an AI enough quality data for it to learn. However, if the real estate industry were to digitize more records and data and be more receptive to change, AI could be an extremely beneficial addition. 

AI could help manage companies’ office space more efficiently. The 2018 JIL Occupancy Benchmarking Report states that 30-40% of office space is mismanaged. IBM’s AI TRIGGA solves this issue by effectively utilizing office space through data recorded by Wifi and spatial sensors. Companies using TRIGGA have seen their office space better utilized, leading to more efficient offices and workspaces as well as higher employee happiness and satisfaction.

Another use of AI in real estate is helping buyers search for properties. Current search engines help by eliminating options buyers are not interested in, but potential buyers are still left with too many options to explore them adequately.

AI could help reduce this issue: Trulia, a San-Francisco based real estate company, has an AI that helps potential buyers find their ideal home by using past transaction data, the buyer’s preferences, and the characteristics of properties.

Another use of AI in real estate is to accurately evaluate the value of properties by predicting future market fluctuations. Israel-based Skyline’s AI predicts the actual cost of features by anticipating future trends. Other AIs can predict the value of properties based on qualities such as square footage, location, bedrooms, bathrooms, and amenities.

For example, San Francisco-based Zillow’s AI can pinpoint the value of a property with a 2% margin of error. Zillow’s AI can also predict which potential clients are serious about buying property by analyzing their activity on Zillow and their purchasing data and activity on other online marketplaces. California based startup Doxel’s AI can also predict and minimize construction costs to avoid budget overrun. 

Although AI could tangibly improve the real estate industry in several ways, it would be most beneficial in the mortgage lending industry. Currently, only a third of mortgage lenders use AI, with half of those using it having it on a trial basis, according to a survey conducted by Fannie Mae. However, the same study predicts that the majority of mortgage lenders will be using AI within a year.

One positive impact of using AI is the possibility of it reducing the closing time from 52 days to 20 by eliminating personal document handling and verification of application forms, among other bureaucratic tasks. Having incorporated AI in late 2018, Bank of America has been one of the first industry giants to implement it. Because of AI, Bank of America reduced its mortgage application form from 330 questions to 10 and reduced closing time to 20 days. In light of the expedition of the mortgage process, Bank of America saw an increase of 6% in mortgages from Q1 through Q3 of 2019. 

AI could also expand the field of applicants who are eligible for mortgage loans. Currently, the percentage of Americans who own property is less than it was twenty years ago. One contributing cause to the reduction of homeowners’ rate is that potential borrowers are getting turned down due to a lack of past credit data.

AI can help correct for the lack of credit history by giving lenders a full view of applicants as people through access to more in-depth customer information. While there are privacy concerns about an AI researching applicants, a study conducted by Harris Poll earlier this year found that 70% of Americans would be content to provide extra personal information if it led to a fairer credit evaluation, with minority groups especially agreeing.  

Seth Weissman Urban Standard Capital CEO

There have also been concerns about AI developing the best-fit algorithm that discriminates against certain groups of applicants. However, lawmakers and regulators in the real estate and technology industries are working to ensure that AIs will be nondiscriminatory. One approach to eliminating possible discrimination is making the applicant evaluate algorithms accessible by the public to increase transparency and reduce potential bias, somewhat similar to open source code. 

In an industry that is seemingly stuck in the past, AI could be a valuable asset if introduced and appropriately regulated. Among other benefits such as expediting and improving the property buying process as well as helping efficiently manage office space, AI could reduce the risk of mortgage lending and prevent another housing crisis, all while allowing more Americans to own property. 

Artificial Intelligence In Wealth Management

AI Investing with New York’s Leading AI Firm – Rebellion Research

Seth Weissman, Urban Standard Capital CEO on NYC Real Estate, Florida, Lending & Developing