HOME BUYING GOES DIGITAL

For generations, buying a home has been the biggest purchase an average Canadian will ever make. 85 per cent of first-time buyers spend as much money as they can afford on their homes, and one-fifth pay more than they’ve planned, mostly due to fees they didn’t anticipate.

Housing is so critical that most people still trust industry experts to guide them through the buying process. Real estate agents, for example, have been consistently rated as incredibly useful throughout the process, and six in 10 buyers still feel face-to-face discussions throughout the purchase are very important.

That being said, the world is changing – and quickly. Uncertainty about buying a home has decreased – in 2015, 51 per cent of buyers felt concern about the process, but this has declined for the fourth consecutive year to a low of 37 per cent. Online research is now the most popular method of finding information about homes, with three quarters of buyers accessing property insights online. Most buyers also expect to gather mortgage information online from lenders’ websites. Then there is the appraisal process, which more than a third of first-time buyers didn’t even bother with.

The COVID19 outbreak is rapidly accelerating this process, with real estate companies quickly adopting digital strategies and alternative methods of doing business, according to McKinsey & Company. In Ontario, for example, agents have been forced to change. The Real Estate Council of Ontario (RECO) has reported that, while real estate services are still considered essential, the government prohibited open houses as of April 4, 2020. Firms now have to sell digitally if they hope to attract buyers. Moreover, the agents with the most foresight in the business may also not be migrating online as a temporary measure – many expect the industry to change permanently after things settle down. 

THE ORIGINS OF GNOWISE INTELLIGENT HOME VALUATION

Amir Madadi and Faraz Arbabi took note of this. Madadi, a real estate investor and experienced property-tech visionary, felt the industry was missing something when it came to the online experience. “It’s 2020,” he explained. “The world-wide web is now over a quarter of a century old. New tech giants have proven to us that digital purchases are preferred by a large group of people, and it’s not just books or videos. Financial products, vehicles, mortgages, and most importantly, homes, are now purchased on platforms such as Zensurance, Rocket Mortgage and Purple Bricks.”

Arbabi, a PhD graduate of Engineering at the University of Toronto, specializing in numerical and computational modelling, suggested something revolutionary when he met Madadi in 2015. He suggested the ultimate, customizable experience for homebuyers, a system that would consider every variable they could gather – including distance to schools, macroeconomics, capital markets, jobs, COVID-19 outbreak data and so on. While some automated home valuation models simply consider the historical trends of previous similar sales, Arbabi knew this wouldn’t be enough – markets are fickle, and can turn in the blink of an eye – but how and where people want to live is a different story. He gathered as much open data as possible, through every source he could access. 

And so, Gnowise was born. It was a complete, neighbourhood-focused home price forecasting and valuation tool, which offered adjustments prospective buyers could make based on their own preferences. Complete with risk simulations under various conditions, Gnowise has grown its user base substantially since launching in 2018. The firm isn’t planning to cut out the experts, either – which many AI/ML systems aim to do. Madadi, in his own words, claims that “human interaction is the largest driver of trust in the markets, whether real estate or financial. And without trust, the market collapses. People often forget that when building complex models and API access for developers.” For that reason, Gnowise also offers a “human-in-the-loop” approach, with certified appraisers verifying AI/ML valuations from their platform. 

MOVING TO THE CENGN CLOUD:

There’s only one catch: This type of back-end system, including the multi-layered neural network models built to provide such insights, are incredibly hard to scale. Retraining such models with new information as it comes in can be time consuming. Add 200 gigabytes of open data that Gnowise consumes and you have an engine which can be difficult to control. Hosting such a system on a commercial grade cloud requires resources beyond what a normal business might be able to afford. With the ever-growing complexity of the world economy during a pandemic, more and more data continues to flow into the platform. 

For this reason, the co-founders decided to partner with the Communitech Data Hub, through the Centre of Excellence in Next Generation Networks (CENGN). CENGN provided the Gnowise team with a world-class, commercial-traffic-free testbed with extensive access to Nvidia Tesla V100 cards focused on machine learning enhancement. Gnowise staff are working diligently to optimize their model training to limit cloud expenses before they continue scaling and preparing their back end to take on more customers. CENGN engineers have organized every aspect of their data pipelines – containers, databases, and all. Gnowise has continued to expand its engineering team in house, bolstered by Communitech and CENGN advisors, coaches, and technical experts.

Madadi believes this is a game-changing experience for his firm: “The real estate market – from homeowners and investors, to brokers, agents and banks – is changing rapidly. CENGN is helping us accelerate that change at scale for the benefit of all parties. With the help of these experts, we’re able to fill all technical gaps on our cloud systems, and ensure we are prepared for even the most intensive large-scale customer deployments.”

For more information on real estate, see the 2018 Mortgage Consumer Survey Results, Canada Mortgage and Housing Corporation’s (CMHC) new factsheet, or the Statistics Canada Survey of Household Spending, and COVID-19 notices: https://www.reco.on.ca/covid-19/.

Learn more about Gnowise Predictive Real Estate Analytics, and apply to join them in the CENGN program.

The post How Gnowise is using the CENGN cloud to derive real estate insights through COVID19 appeared first on Communitech News.

Communitech is a partner of Startup HERE Toronto.  This article originally appeared on their site.