W.A.L.T. reads what three credit agencies, three valuation models and the Land Registry can't agree on — and returns a fully reasoned, fully audited bridging decision in under five minutes.
Four structural failures define bridging underwriting today — and every one of them costs lenders deals, margin, or both.
Experian, Equifax and TransUnion each run different scoring models, sources and timelines. Underwriters guess which report to trust: good borrowers get declined, risky ones slip through. Nothing in the market reconciles the three into one reliable view.
✕The same property returns materially different values across AVM platforms — and two RICS surveyors will frequently disagree too. Loan-to-value gets calculated from a single data point while the underlying evidence contradicts itself.
✕One application means six-plus systems, manual report pulls, AML checks, valuations and title review — three to seven days per deal. Brokers control flow and route to whoever answers first. In bridging, speed is the primary driver of conversion.
✕Separate contracts for credit agencies, AVMs, AML software and registry searches — then senior underwriters spend salaried hours re-keying data between them. Cost grows linearly with volume because nothing in the workflow is automated.
✕A lender that takes five days to return terms on a deal a competitor underwrites in two has already lost.
Scroll through the five stages of a W.A.L.T. run. The dossier on the left fills in as the engine works — exactly as it does in production.
Biometric eIDV, sanctions and PEP screening run the moment a case opens. SmartSearch, APLYiD, Veriphy and World-Check return in seconds — with personally identifying data pseudonymised before any model ever sees it.
All three UK credit agencies are pulled in parallel, averaged, and checked against each other. Where they disagree — a missed CCJ, a stale default — the inconsistency is flagged rather than silently inherited.
Three-plus AVM models are cross-referenced into a consensus valuation, replacing the single-data-point LTV that bridging decisions usually hang on.
Land Registry transaction history and market depth are scanned to estimate sale velocity — the exit-risk dimension nearly every lender skips because no tool measured it. Until now.
GPT, Claude and Gemini each produce an independent risk assessment. W.A.L.T. synthesises the three, flags disagreements, and assembles the audited 8-page report a human signs off on.
W.A.L.T. underwrites live bridging applications today through Whitehall Lending, a specialist lender in Mayfair — the team that built it.
Each model writes its assessment without seeing the others. W.A.L.T. synthesises the three, surfaces every disagreement, and hands a consolidated view to the human decision-maker. This is not AI replacing underwriters — it is AI giving them better information, faster, with identity data pseudonymised before it ever leaves the building.
Financial-grade controls at every layer. Client data stays private, isolated, and fully under the lender's control.
Tiered SaaS pricing on monthly decision volume. Predictable revenue, strong unit economics, low marginal cost per client.
MVP complete. Product nearly finalised. The platform is underwriting live cases today through Whitehall Lending.
From the team behind Whitehall Lending, a specialist bridging finance provider operating from Mayfair, London.
Managing Director of Whitehall Lending. Deep expertise in bridging finance, property underwriting and credit risk.
Lead AI engineer with 6+ years in NLP and a track record building highly scalable, highly sensitive AI systems. MSc Computer Science.
AI researcher published in Frontiers in AI on deep transformer models. AI Summit London hackathon winner.
Leads day-to-day operations, seconded from Whitehall Lending — direct lending operations experience inside the build.
Administration and operations support, coordinating across the founding team from Whitehall Lending.
Seed funding unlocks two key hires: a senior AI/ML engineer and a compliance lead — the roles that take W.A.L.T. from one lender's desk to two hundred.
See a live decision in minutes — or request the investor data room.