How proptech is disrupting the rental market and why AI is leading the way?

Elisabeth Kohlbach

The coronavirus pandemic has created unparalleled new challenges across the UK’s resi-rental sector. A pause on the market during the first national lockdown left many property owners unable to finalise transactions, attract new tenants or facilitate viewings.

In the months since, the shift to lockdown remote working across the UK has radically altered property preferences, while repurposed short-term holiday lets have also saturated the market.

However, this is still not the whole story – the pandemic is also a watershed moment of opportunity, reaffirming the value that proptech, and AI in particular, can add for investors in the private rental sector (PRS).

Identifying best in class investment

Successful investment is no longer a case of simply buying up properties in business hubs or student towns. Covid-19 has significantly changed what tenants want from the rental market, with the UK Government’s advice to “work from home if you can” and a shift en mass to remote working prompting many renters to rethink proximity to city centres and commuting hubs.

The direction of travel is clear – home working will be the new normal for many people for some time to come. And, therefore, with less need for tenants to be close to the urban core of major cities, many will look elsewhere for better value for money and properties that are more closely aligned with these new priorities.

So, it is no surprise that a two-speed rental market has already begun to emerge, with rents in the countryside rising by 5.5% year-on-year in the October, a rate that was more than three times the national average. Meanwhile, rents in the capital fell by 5.3% – an almost complete reversal of their 6.3% rise last year and a significant decline on the average rent rise of over 38% in the past decade.

Finding new ways to make highly targeted, well-calculated investments has therefore never been more important. Understanding the nuanced trends in tenant requirements is crucial, and AI technology is unlocking new ways to do this. For instance, at Skwire, we built a proprietary self-learning AI algorithm trained on over 11 years and more than 150 million datapoints of residential rental data, which allows us to pinpoint the very best properties at a hyper-localised level. Crucially, it is proven to pick winners, with Skwire’s first portfolio beating local market yield averages by as much as 175%.

Capitalising outside of BTR

Technology is also opening up overlooked opportunities for investors in existing housing stock, moving beyond a focus on the Build to Rent (BTR) sector, which alone risks failing to meet housing demand. Capacity is one major element of this: while estimates suggest there could be a further 560,000 new PRS households by 2023, there are just 110,000 estimated Build to Rent units in the pipeline according to research from Knight Frank.

This suggests that 75% of rental demand remains unmet by BTR schemes, which carry greater development risk and often fail to offer the attractive locations of existing property stock, as sites available for development remain limited.

AI technology, in particular, is beginning to unlock the potential of existing housing, identifying opportunities for investment at pace and scale, as well as improving the efficiency of the underwriting process. Algorithms can also be tailored on metrics that improve the speed at which properties are prepared for listing on the rental market, for example by identifying homes in need only of cosmetic upgrades and without the long lead times of BTR.

Alongside greater efficiency, this data-driven approach can power tailored investments in portfolios that are much better aligned with investors’ ethics and evolving priorities. As well as offering a new route into the broadly untapped potential of standing stock, existing property is also a far more sustainable option – better aligned with ESG principles and the chance for a green recovery from the coronavirus pandemic, with lower carbon costs than new build projects. It is a factor that, as we begin to emerge from this global pandemic, will keep rising on the agenda for investors.

Monetising relationships and enhancing yields

Proptech is not only disrupting methods for making investments in property, it is also radically changing strategies for extracting value from that portfolio. In fact, more than half of landlords do not offer professional property management, a fact that rings true to many people’s anecdotes of woefully inadequate renting experiences.

But with the pandemic creating a preference for flexibility in all areas of our lives, it is also cementing the appeal of renting as a lifestyle choice – and investors must keep pace with this change. Not only is renting preferable for many people, they are also more spoilt for choice. The pandemic has driven down city centre rents, while the market is increasingly saturated by short-term holiday lets repurposed as longer-term rental homes when tourism revenues waned.

Tenant services are becoming an increasingly crucial differentiator, and tech will play a central part in delivering this to a high standard. By improving responsiveness with tech-driven, automated systems, landlords can monetise the tenant experience, enhancing satisfaction, maximising retention and reducing the administrative burden for property managers.

Further proptech innovations, such air quality sensors and integrated energy systems, are also giving tenants more control than ever before over the outgoing costs and environmental impact of their rented home – a trend that will only grow in importance over the years ahead.

Change and opportunity

Covid-19 has brought unprecedented upheaval to the private rented sector, but it is also an opportunity for meaningful improvement in a market that has, for too long, failed to evolve. Investors should take note of how proptech is disrupting the sector, and the chance this provides to improve the landscape and fabric of PRS for both tenants and investors, or risk being left behind long after the impacts of the pandemic have passed.