BLOGS

A private rented sector under new pressure

Tenant referencing used to be a formality: a credit check, an employer reference, a photocopied payslip. That model is breaking down. Recent industry analysis of over a million tenant references puts suspected fraud at roughly 41 applications per 1,000 — a rate that has climbed by close to 40% year-on-year — with total exposure to the private rented sector estimated at up to £4.1 billion annually. Average direct losses per fraudulent tenancy, covering arrears, legal and court costs, void periods and property damage, are estimated at around £9,600.

For a sector already adjusting to the Renters' Rights Act 2025 and the abolition of Section 21, the timing compounds the risk. Landlords can no longer fall back on a straightforward no-fault route to regain possession, meaning a fraudulent tenancy now typically runs its course through a formal grounds-based process. Reported possession timelines exceeding six months are not unusual, during which a landlord holding a mortgaged buy-to-let asset continues to service debt against a property generating little or no legitimate income.

Fake identities are getting harder to spot

What has changed is not just the volume of fraud but its sophistication. Rather than a single forged payslip, referencing platforms are now reporting entire synthetic tenant identities: fabricated employers, doctored ID documents, invented referees and AI-generated bank statements assembled to pass multi-point checks. Confirmed fraud data for 2025 shows fake employment references up 226.6% year-on-year, referee fraud up 146.4%, and identity manipulation up 140.4% — a shift from opportunistic forgery toward engineered deception.

The exposure is not evenly spread. High-value lettings show materially higher confirmed fraud rates than the market average — properties renting above roughly £10,000 a month have recorded confirmed fraud rates several times the typical rate across all rental stock. This matters for institutional landlords and build-to-rent operators active in prime central London and other high-value submarkets, where a single fraudulent tenancy carries outsized financial exposure relative to a mainstream three-bed suburban let.

REalyse data on achieved rents and days-on-market by postcode and property type gives landlords and agents a practical cross-check here: an applicant whose stated affordability sits well outside the local achieved-rent band for that bedroom count and property type, or who is pushing to move unusually fast relative to typical local marketing periods, is a pattern worth flagging alongside document-level checks.

Why the incentives favour fraud right now

Three forces are aligning to make fraudulent tenancies more attractive to bad actors and harder for landlords to filter out.

Rental growth widens the prize

Sustained asking and achieved rent growth across much of the UK over recent years has raised the value of securing a tenancy without ever intending to pay for it. Where local achieved rents sit meaningfully above national averages — as REalyse comparables consistently show across inner London, parts of the South East, and city-centre flats in Manchester, Bristol and Edinburgh — the potential monthly gain from occupying a property rent-free rises in step, making these submarkets a more attractive target.

Possession timelines extend the runway

With Section 21 abolished and grounds-based possession now the only route, the average time to regain a property from a non-paying tenant has lengthened. Every additional month of free occupation increases the fraudster's return and the landlord's loss, shifting the economics of tenant screening from a compliance task to a direct P&L consideration.

Verification tools have not kept pace

Many landlords and smaller agencies still rely on manual reference checks and document review by eye — exactly the layer that AI-generated documents are designed to defeat. Right to Rent enforcement has tightened and penalties have risen, but identity verification technology of the kind used by banks and mortgage lenders remains inconsistently applied at the point of tenancy application.

Toward stricter, data-led verification

The direction of travel is toward layered, source-based verification rather than a single "pass/fail" reference. This typically combines:

• Digital identity verification — passport or driving licence checks validated against government or biometric data sources, not photocopies

• Source-verified income and employment — checks against payroll or open banking data rather than applicant-supplied payslips

• Cross-referencing against market comparables — testing stated affordability and rent against REalyse-style local achieved rent and yield data for the specific postcode, property type and bedroom count

• Ownership and provenance checks — for portfolio landlords and lenders, verifying legitimate title through Land Registry data to guard against related property fraud

For institutional landlords, lenders and build-to-rent operators, this points to fraud screening becoming a standard part of asset-level risk management, sitting alongside rental yield analysis, void-period tracking and planning pipeline monitoring rather than being treated as a lettings-desk afterthought. Lenders underwriting buy-to-let and BTR debt have a direct interest too: rental income assumptions used in serviceability tests are only as reliable as the tenant behind them.

Outlook

Tenant fraud is unlikely to reverse on its own — the tools available to fraudsters are improving faster than manual referencing can adapt. But the sector's response is becoming more structured: tighter Right to Rent enforcement, growing local authority powers against rogue activity, and rising adoption of identity verification technology akin to that used in financial services. For professional landlords, agents and lenders, the practical takeaway is to treat tenant verification as seriously as asset valuation — cross-checking applicant claims against real market data, not just the documents an applicant chooses to provide.