Home ownership across Europe has collapsed in the last 20 years meaning that more and more people are looking for non-binding and flexible accommodation. Indeed, for 25- to 34-year-olds earning between £22,200 and £30,600 per year, home ownership fell to just 27 per cent in 2016 from 65 per cent two decades ago. Research from the Institute for Fiscal Studies published in The Guardian highlighted how house prices increasing above income growth has meant that the chances of the next generation on a middle income owning a home in the UK has more than halved in the past two decades.
With Brexit uncertainty the housing market is looking even more unstable. Additional pressure on the current rental market due to fewer potential home owners wanting to take the risk and buy has resulted in a slow response to increased demand, which has meant the average price of rents, particularly in the capital has continued to increase at an exceptional rate.
The increasingly supply-constrained market has meant that rent in London is hugely expensive, on average £3,700 more, this makes the average monthly renting cost the most expensive across Europe for the third consecutive year.
We know from our data that the cost-of-living is one of the biggest frustrations about living in London, along with being unable to find an affordable place to live close to the city centre. Choosing where and who you live with is one of the most important decisions in our life, yet in London it is not uncommon to rent a room without even physically seeing the space or meeting the person with whom you live.
In practice, there is rarely enough time to make endless visits to view rooms and in London especially they are snapped up too quickly to hang around. And because demand far outweighs supply, potential roommates can be more particular and now we’ve started to see an increasing trend for one, often two interviews for potential housemates before accepting new sharers. Our platform uses AI to help smooth the process and minimise time-wasting by eliminating mis-matched housemates and making flat and roommate hunting easy with some simple fact-finding ahead of even the first meeting. Even for those living on the other side of the world the algorithm on badi can find matches in the city you want to live in ahead of even your first visit, once that’s done the platform will also enable you to easily secure your room safely with badi’s online payments technology.
Pairing perfect flatmates
Essentially, we use intelligent algorithms to pair perfect flatmates according to factors like age, tastes and interests. We want to make city-living accessible to everyone by cutting out the middle-men, giving people more control when it comes to renting a room. As a PropTech startup, we are centred very much around AI, algorithms and data – it is these technologies that allow us to become the quickest and most innovative room-rental marketplace.
Our solution is the first in the PropTech space and we’ve already seen encouraging adoption across the rental market, addressing different challenges. For instance, ‘virtual property managers’ use bots to help renters to log issues, book in services and contractors, and help tenants fix small problems and repairs.
AI in general is increasingly starting to provide solutions in our day-to-day lives, from virtual assistants to driverless cars and online personal shoppers. It makes sense that the rental industry is jumping on board. We’ve seen it in the mortgage industry already, with the likes of Trussle and habito using algorithms to pick out bespoke mortgages.
London is a particularly tech-led and digitally-savvy city with a higher AI adoption rate than most places in Europe. London’s AI sector saw a 200 per cent venture capital funding increase between 2015 and 2017, it has also been rated Europe’s top hub for AI talent by various other investors. The city is also investing in the next generation of AI talent, with 13 universities in the UK capital offering AI-related degrees.
In all industries, the business case has to be made that AI helps to reduce cost and barriers whilst improving efficiency and delivering personalised experiences. AI allows us to use data in a more mature way and accurate fashion, providing better solutions for all industries, particularly the rental market. So for badi, AI allows us to match people based on their personalities. For instance, we know from our data that smoking and pets are the most annoying personality traits of a flatmate.
Enhancing user experience
AI can also eliminate initial bias, providing an arguably more accurate match than our own first impressions. There’s an overused phrase “I didn’t think I would like you when I first saw you” between people that on paper could become best friends, AI can pick up on that much faster and create connections for life.
Machine learning helps when enhancing user experience in the whole platform flow. For instance, when bringing demand and supply together, machine learning is able to speed up the process by optimising towards previous matches.
We’ve developed a recommendation engine for listers that learns about the matching process between landlords and tenants and suggests which are the most “effective” users to live with. This speeds up the entire renting process, meaning landlords do not have to wait for candidates to search and request their flat, because badi recommends them beforehand.
It’s certainly an exciting time to be sitting in the intersection of property and technology, with AI in particular allowing us to increasingly provide quicker and innovative solutions to the room-rental market. Since launching, the performance of our algorithms has improved over time reaching out an accuracy level of around 60 per cent. By using AI in our recommendation engine, we’ve managed to generate more than 15M seeker recommendations to listers.
In the rental market, trust is built by making consistently successful recommendations. AI has helped us do this more quickly and more often, further earning the trust of our users. We would encourage any brands in the real estate sector to think about how they can adopt these types of technologies in 2019 – we’re excited to see what’s next to come!
Guillem Pons, Chief Data Officer, badi
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