By 2030, AI is predicted to add +$15 trillion to the global GDP thanks largely to solving data issues according to PwC. Lending money used to be a tricky business but time consumers and technology is changing. Banks and other industries are struggling to cope with the changing consumer demand, but a few are getting it right.
AI’s Projected Impact on Global GDP
Real Estate is one industry that has a big AI opportunity due to its late mover position. The early pitfalls have been identified and now fast progress can be made with a sensible strategy.
Lending money is an easy task but validating a client is tricky. “Risk is the biggest hurdle to get over” according to Reynaldo Reyes, Director of Sales, Sharp Loan. “Biases still exist, and algorithms aren’t going to solve the issues if they are built-in from the ground up…let alone when facial recognition and GPS really get integrated into systems.” Real Estate is starting to use technology to its full potential, according to Reyes. From virtual reality, smart contracts, virtual assistants to better UX on sites and voice bots; “We’re using AI chat bots and Virtual Assistants, it really helps answer consumer queries with little delay. This feature is more targeted toward millennials looking for property because trigger messages based on certain actions or keywords provide timely assistance which makes the mortgage experience less stressful. Technology is helping us get people to the right place, figuratively and literally.”
Susanne Eickermann-Riepe, Head of Real Estate, PwC Germany is bullish on AI’s further contributions to the Real Estate market as the industry is only part way through the potential AI offers; “There are four main areas: Automated intelligence: Firstly, automating manual, cognitive and routine versus non-routine tasks. Secondly, supporting intelligence; helping people to accomplish tasks faster and better. Thirdly, expanding intelligence: helping people to make better decisions and finally, autonomous intelligence. Automation of decision-making processes without human intervention.”
Real Estate is, like many industries, turning its attention to learning from the playbooks of Netflix, Uber, Facebook, and Amazon to determine their client’s likes and dislikes are. When it comes to Real Estate, big data could involve using CRM tools that show when a potential customer visits your listing or website and collect data based on their activity on the page. Jasjeet Thind, Vice President, AI and Analytics at Zillow agrees; “Today the real estate transaction is stressful and often duplicative. By leveraging AI we can create a more personalized, end-to-end experience for our customers, eliminate many of the pain points associated with buying and selling a home, and help our customers close on their home faster.” Such information can forecast when a prospect might be selling or buying an investment property, or even the sell or rental price of a home.
Several startups are focusing on the Real Estate industry when it comes to AI, but AI isn’t a save-all for Real Estate. Bad planning, execution and problem-identification can lead to solutions that cause more problems than they solve. Data availability, data quality and standardization are key areas to focus on along with legal requirements around the world for the Real Estate industry. AI is just part of Real Estates future, not just the next 12 months. An in-depth look at cryptocurrencies, blockchain, the sharing economy, co-living and drone tech is needed by governing bodies to asses the opportunities and impact these and future technologies will have on the home lending and PropTech market as a whole.