Artificial Intelligence Is Transforming the ‘Broken’ Property Sector
The UK housing market faces a long road to recovery after taking hit after hit over the past few years. Heightened inflation, sky-rocketing mortgage lending rates, inefficient processes: housing is not short of a few challenges. However, there is a glimmer of hope. There is a way to make investment more attractive, quash long-standing renting issues, reduce climate impact, and provide a fairer and more accessible property sector.
The solution comes in the form of emerging technology.
The Industry Challenges
It’s a complex market out there.
There are a plethora of challenges to face every day, one of the most prominent being the current rental market, with its task of enhancing housing quality while simultaneously scaling back out-of-control rental costs.
Recent data reveals a disheartening reality: nearly two-thirds of landlords expect they’ll need to raise rents by a minimum of 10% over the next 12 months. This decision is largely dictated by market pressures and the surge in energy bills.
Generally, the property is under huge amounts of pressure to reduce energy expenses for both tenants and landlords. Even with Prime Minister Rishi Sunak scrapping the EPC regulations changes, many property owners have already invested in making the necessary improvements.
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And, how long will it be before we see yet another U-turn in this area?
To overcome these challenges, institutional capital is required, which in turn needs rapid deployment of advanced technology.
The Individual Challenges
When it comes to investing in the housing market, at the heart of the problem lies a web of complexity born out of inherently poor processes, which is often traceable to human error.
These challenges are broad, including but not limited to a lack of transparency and data, inconsistent property valuations, sourcing lucrative deals, and manual processes taking hours instead of seconds. Altogether, it’s resource-heavy and unnecessarily complex.
Technology would therefore become an “extractor of knowledge” that speeds up processes through AI elements that can help streamline administrative tasks or carry out risk assessments.
By leveraging these features, technology has the potential to enhance efficiency and significantly reduce costs, thereby lessening the financial burden passed on down the chain from investor to consumer.
It’s Time to Fix That Which Is Broken
Two core technologies are starting to shape industries across the world, and both hold huge promise for the UK’s housing market: machine learning and artificial intelligence.
Machine learning
The consequences of overlooking crucial data in the housing sector can directly impact renters’ budgets.
A critical aspect of property underwriting involves pinpointing suitable “comparable transactions” to assess the asset’s value. This requires trained investment experts to dedicate countless hours of their time. That’s bad enough, not to mention the fact that the process often features guesswork when experts aren’t available. Both options are undesirable: enormous time investment, or unreliable estimations.
Enter machine learning.
It can help technology-driven property companies refine algorithms to process larger volumes of comparable assets compared to traditional, manual methods. Landlords can then leverage these platforms to evaluate and compare their property portfolios quickly and accurately. This process suddenly reduces from several days to nearly immediate completion.
Additionally, landlords can identify distinctions within their portfolios and similarities with others, enhancing their understanding of housing quality and enabling more accurate pricing. Investors can also utilize these algorithms to identify and prioritize sustainability-focused retrofitting projects, which can yield higher returns than new construction investments. This dual-purpose approach simultaneously addresses long-standing industry pain points, including reducing energy costs for landlords and alleviating overall renter expenses.
Artificial intelligence
Investing in real estate involves the grueling task of sifting through huge numbers of documents to gather the information required for a precise asset evaluation. This manual process not only elevates the risk of errors or oversights but also lengthens the investment transaction process.
By harnessing the capabilities of AI language models, aided by predictive analytics, investors can automate the consumption of data to quickly gain insights into assets, thereby freeing up more of their time for value-added activities.
By automating property management for example, landlords gain greater visibility and control over their property portfolio, helping to save on costs and increasing tenant satisfaction. When paired with comprehensive housing information like room count, location, energy efficiency rating, and accessibility, investors will start to look beyond newly constructed projects. This way, investors can identify properties that, once retrofitted, have the potential to yield much higher returns.
AI also enhances risk assessments, identifying properties or locations with hazards that could potentially impact the long-term value or trigger greater financial risks. This further aids investors in their search for projects beyond the new homes market.
There is genuine hope for the UK housing market, with the potential for complete alignment between the needs of investors, landlords, and their tenants.
All that’s required is an injection of innovation.
As is becoming ever more apparent, technology like AI can truly become a catalyst for transforming the housing investment landscape.
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