If assets like homes are becoming fluid in data as much as fixed in bricks and mortar, who can be trusted to interpret what this means for mortgage lenders, valuers, insurers, and homeowners?
The algorithm and the asset
When AI simulations become the de facto source of truth, the model risks dictating reality. Who decides when a forecast is a scenario - and when it becomes policy?
This raises a single, important question for the UK housing market: if assets like homes are becoming fluid in data as much as fixed in bricks and mortar, who can be trusted to interpret what this means for mortgage lenders, valuers, insurers, and homeowners? The answer lies with those who can connect the dots between risk, regulation, and reality — and that is where Cotality comes in.
Cotality’s role throughout is clear: to interpret and to guide — to frame the stakes of the transition and show clients where they must be alert.
Key themes for UK professionals
Artificial intelligence is changing what it means to own, value, and protect a home in the UK. Algorithms are recalibrating markets faster than human confidence can follow. Each gain in efficiency exposes new questions about fairness, transparency, and trust about how property is priced, financed, and insured.
In a series of articles regarding AI in the UK housing sector, we explore this transformation and its potential impact on accountability, ownership, valuation, underwriting, and more.
Throughout the series, we will return to the same principle: housing may be powered by data, but it is lived by people – and therefore accountability must never be left behind.
Part 1: Who really owns the data?
A decade ago, homeownership was defined by the name on the Land Registry deed. It was clear who was liable for questions and changes to value, risk, payments, and conveyancing. Artificial intelligence is altering this rhythm, taking real estate from an asset class defined by days of conversations and contracts to a dynamic recalibration of inputs in seconds.
The speed at which AI can assess mortgage portfolios and analyse thousands of properties has transformed property into a new kind of financial instrument. What was once a physical asset made of sticks and bricks now exists as a digital model to be scrutinised at every angle by anyone, anywhere.
While AI promises efficiency, what happens if it miscalculates LTV (Loan-to-Value), inflates value, or overlooks structural/environmental risk (e.g., flood plains)? Who is accountable?
Blurred accountability and the UK consumer
The question of accountability is critical for UK firms operating under the FCA’s Consumer Duty. While automation offers benefits, the Duty requires firms to act in good faith and avoid foreseeable harm to retail customers. When algorithms make key decisions—such as a property’s acceptable valuation or a borrower’s affordability—the accountability cannot simply be outsourced to the code.
The knowledge gap is clear: traditional UK housing regulation assumes clear lines of liability: owner, mortgage lender, insurer, regulator.
AI-driven systems blur those lines. When valuations and borrower eligibility are made by algorithms trained on opaque datasets, legal recourse could become uncertain.
Accuracy without accountability gambles on future outcomes for lenders, valuers, brokers, and homeowners alike. Working with partners like Cotality illuminates the layers of data, governance, and analysis behind the models so you can have confidence in Automated Valuation Models (AVMs), property risk profiles.
Encoding responsibility and regulation
The UK regulatory landscape is still catching up. Oversight focuses responsibility on the firm and the individual carrying out the regulated activity. With the Bank of England and FCA monitoring the systemic risk of AI adoption, firms must demonstrate that their AI systems are governed, auditable, and non-discriminatory. When physical assets are transformed into digital tokens, they can slip between frameworks: too virtual for property law, too tangible for securities law.
Without a shared definition of AI-mediated property, authorities will struggle to decide who bears fiduciary duty when decisions are delegated to code.
Data quality is human responsibility
The standard safety warning “garbage in, garbage out” holds truer than ever. In the UK, data quality is paramount for AVMs to be trusted as a component in the lending process, often alongside a physical valuation. The Royal Institution of Chartered Surveyors guidance on automated valuations stresses that the user must understand and accept the limitations of the data.
There is no longer a distinct divide between human expertise and technological insights. They work in tandem. But to provide accurate answers, transparency and accountability must remain the guardrails guiding AI’s development and increasing presence in the property market.
That’s why Cotality positions people at the connection point between data validation and model transparency. So when the FCA asks, “who’s responsible?”, the answer isn’t “the algorithm.”
Trust is transparent
“AI shouldn’t replace the chain of accountability; it should strengthen it,” says Cotality Chief Data and Analytics Officer John Rogers. “Our goal is to make every decision auditable, from the dataset to the doorstep. That’s why we ensure our data is compliant for all relevant regulation.”
Property remains the largest store of household wealth—and risk—in the economy. As AI intermediates more of that value, market stability will depend less on the brilliance of the code than on the clarity of the rules governing it.
Lenders want risk mitigation; regulators want compliance and transparency; families want security. All three require trust that the system can be explained when it fails.
The future of property may well be fractional, algorithmic, and dynamic. But the responsibility for what happens when models meet real lives must have a clear centre.
