AI underwriting for bridging & specialist lenderslive on real cases

Every source.
Every contradiction.
One verdict.

W.A.L.T. is the AI underwriting engine that cross-references credit bureau data, multiple AVMs and Land Registry liquidity analysis, then applies three independent AI models to assess both the borrower and the property. The result is a fully reasoned, fully audited property decision in minutes. Lower cost, greater accuracy and serious speed, built and tested on live cases in the UK property market.

18Live integrations
<2 MINPer decision
3Models cross-examined
01
The problem

Underwriting runs on evidence
that disagrees with itself.

Four structural failures define bridging underwriting today — and every one of them costs lenders deals, margin, or both.

P—01

Contradictory credit data

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.

P—02

Valuations that don't agree

The same property returns materially different values across AVM platforms — and two qualified surveyors will frequently disagree too. Loan-to-value gets calculated from a single data point while the underlying evidence contradicts itself.

P—03

Speed kills deals

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.

P—04

Costs that scale with volume

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.

— Customer feedback, Whitehall Lending underwriting desk
02
The engine

Watch a case file
underwrite itself.

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.

CASE WHL-2026-0417 · BRIDGING · £640,000 · 68% LTV Run live
SmartSearch — KYC / identitypending
World-Check — sanctions / PEPpending
Equifax · TransUnion · CreditSafepending
Rightmove · PropertyData · Realysepending
Land Registry — title & liquiditypending
GPT · Claude · Gemini — tribunalpending
Recommendation
Proceed to offer — risk 32/100, confidence 91%
8-page auditable report
elapsed 1m 48s
Approved
Stage 1 — Identity & AML

Verify who you're lending to

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.

Stage 2 — Credit consensus

Three credit agencies, one profile

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.

Stage 3 — Valuation consensus

What the asset is actually worth

Three-plus AVM models are cross-referenced into a consensus valuation, replacing the single-data-point LTV that bridging decisions usually hang on.

Stage 4 — Liquidity

How fast it would sell

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.

Stage 5 — The tribunal

Three AIs argue. You decide.

GPT, Claude and Gemini each produce an independent risk assessment. W.A.L.T. synthesises the three, flags every contradiction between sources, and delivers one verdict — the auditable 8-page report a human signs off on.

03
Traction

Not a prototype.
A working desk.

W.A.L.T. underwrites live bridging applications today through Whitehall Lending, a specialist lender in Mayfair — the team that built it.

18Live API integrations
3LLMs cross-validating
<2 minPer decision turnaround
ForensicRisk report, every deal
Integration register — tested on real cases12 of 18 shown
SmartSearchKYC / identity
APLYiDeIDV biometrics
World-CheckSanctions / PEP
CreditSafeCredit scoring
EquifaxCredit reference
TransUnionCredit reference
RightmoveAVM / EPC
PropertyDataMarket depth
RealyseMarket indices
Companies HouseDirector / corporate
OpenCorporatesGlobal company data
Land RegistryTitle / ownership
04
Multi-LLM tribunal

Three independent opinions.
Disagreement is the feature.

i OpenAI

GPT

  • Primary risk analysis
  • Credit assessment
  • Exit strategy evaluation
ii Anthropic

Claude

  • Independent cross-validation
  • Regulatory compliance review
  • Counterparty analysis
iii Google

Gemini

  • Market data synthesis
  • Valuation review
  • Anomaly detection

Each model writes its assessment without seeing the others. W.A.L.T. synthesises the three, surfaces every contradiction, and hands a consolidated verdict 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.

05
Modules

Three modules.
Start with one, scale to all.

Buy only the intelligence you need today. Each module runs on its own — or combine both into a single, fully reasoned underwriting decision.

01 Module 01

KYC & AML

  • Identity verification & biometric eIDV
  • PEP & sanctions screening
  • Source of funds & wealth analysis
  • Companies House, UBO & director checks
02 Module 02

Property valuation

  • Multi-AVM consensus valuation (3+ models)
  • Land Registry title, charges & ownership
  • Asset liquidity & exit-risk analysis
  • EPC & market-depth data
03 Full platform

Underwriting

  • Everything in KYC & AML + Property
  • Multi-LLM cross-validated risk analysis
  • 8-page audit-ready decision report
  • Configurable risk rules per desk

Underwriting combines both modules into one reasoned, auditable decision — the work of six systems in a single call. Start with verification or valuation alone, and upgrade to the full decision engine whenever you're ready.

06
Security by design

Built like the systems
it sits beside.

Enterprise-grade security in every layer. Client data stays private, isolated, and fully under the lender's control.

Infrastructure

Isolated by default

  • Private, fully isolated Azure-hosted LLM environments
  • No shared inference layer — dedicated instances per client
  • Zero data exposure to external or shared models
Cloud foundation

Trusted Azure base

  • Built end-to-end on Microsoft Azure
  • Infrastructure trusted by Tier-1 financial institutions
  • Proven experience designing extremely sensitive systems
Compliance

Audited ecosystem

  • Only audited, compliance-grade third-party integrations
  • Encrypted communication with every external service
  • Designed to align with ISO 27001 & SOC 2 — certification in progress
Data protection

Isolated and encrypted

  • Account-level data segregation
  • End-to-end encryption at rest and in transit
  • Identity & access management with Azure Entra ID
  • Hardened, access-controlled database architecture
Least privilegeaccess enforced
Continuousmonitoring & risk management
Financial-gradeenvironments by design
ISO 27001 · SOC 2in progress, already compliant
07
The economics

Six contracts, six logins,
one subscription.

Today every decision is stitched together across separate vendors, licences and per-search fees. W.A.L.T. replaces the entire stack with a single subscription.

The current cost of underwriting

Underwriter salaries

£35k–55k per head, plus NI, pension and overhead.

Credit agency subscriptions

Separate contracts with Experian, Equifax and TransUnion.

AVM provider licences

An individual subscription for every valuation platform.

AML/KYC software

Additional compliance-platform fees on top.

Land Registry access

Per-search fees across multiple portals.

Hours per deal

Each underwriter logging into 6+ systems per application.

With W.A.L.T. — one subscription

All major credit agencies

Pulled, averaged and analysed automatically.

Multiple AVM models

Cross-referenced for consensus valuations.

AML/KYC with AI facial checks

Sanctions, PEP and identity checks built in.

Land Registry & liquidity

Asset liquidity analysis as standard.

Companies House

Director checks and corporate-structure analysis.

Open Banking

Bank-statement analysis and income verification.

One contract, one login — the entire underwriting stack in a single reasoned decision.

08
Get started

Book a demo on
your own cases.

Tell us which modules you're interested in and we'll run a live decision on a real case from your desk — then send pricing matched to your volume.

Underwriting live cases today through Whitehall Lending — built by the team that processes real deals and manages real risk.

We'll only use your details to respond to your enquiry — see our Privacy Policy.

What to expect
A 30-minute callWe learn your deal flow and which modules fit your desk.01
A live decisionWe run W.A.L.T. on a real case from your own pipeline.02
A tailored quoteModule pricing matched to your monthly volume.03
Live in daysOne module or all three — no long procurement cycle.04
09
The team

Built by people who
underwrite for a living.

From the team behind Whitehall Lending, a specialist bridging finance provider operating from Mayfair, London.

AB

Anthony Bodenstein

Founder & CEO

Anthony founded Underwriting UK after two decades in specialist property lending. As a practising bridging lender he has originated, underwritten and managed short term secured loans across residential, commercial and development assets, giving W.A.L.T. its foundation in real world credit decisions rather than theory.

EL

Elias Limouni

Chief Technology Officer

With extensive experience in AI and enterprise technology, Elias has led Agentic AI strategy for global organisations including Carrefour, and founded several deep tech ventures. At Underwriting UK, he leads the company's technical strategy and engineering team while building W.A.L.T., combining enterprise-grade AI with practical software engineering to deliver trusted, real-world underwriting technology.

GS

Gayathri Singaram

Engineer & AI Specialist

AI researcher published in Frontiers in AI on deep transformer models. AI Summit London hackathon winner.

JH

Jack Hodgkin

Head of Business Development

Jack leads lender and broker relationships at Underwriting UK. He joined from Whitehall Lending, where he was Business Development Partner originating and managing bridging finance introducer relationships, and brings prior business development experience across UK financial services.

LC

Lisa Croft

Operations Support

Administration and operations support, coordinating across the founding team from Whitehall Lending.

The people who built it use it every day. W.A.L.T. is shaped by real cases on a real lending desk — not a roadmap drawn in a vacuum.

10
FAQ

AI underwriting,
answered plainly.

The questions lending desks ask before putting an AI underwriting engine next to real money.

Q—01

What is AI underwriting software?

AI underwriting software automates the evidence-gathering and risk analysis behind a lending decision — pulling credit agency data, property valuations, KYC & AML checks and title data, then using AI models to assess risk. W.A.L.T. goes further: it reconciles sources that disagree with each other and produces an auditable recommendation a human underwriter signs off on.

Q—02

How fast can W.A.L.T. underwrite a bridging loan?

Under 2 minutes per decision. One case triggers 18 live integrations in parallel — identity and sanctions screening, three credit agencies, three-plus valuation models, Land Registry and Companies House — and returns a fully reasoned 8-page report.

Q—03

Does AI underwriting replace human underwriters?

No. Three independent AI models — GPT, Claude and Gemini — each write an assessment without seeing the others, disagreements are surfaced, and a consolidated view goes to the human decision-maker. It is decision support: better information, faster, with the lender keeping full control and accountability.

Q—04

Are W.A.L.T.'s lending decisions auditable and compliant?

Yes. Every decision produces an 8-page report recording the evidence, each model's reasoning, and every flagged inconsistency. Identity data is pseudonymised before any model sees it, environments are isolated per client on Azure, and the platform is designed to align with ISO 27001 and SOC 2.

Q—05

What is a multi-AVM consensus valuation?

An automated valuation model (AVM) estimates a property's value from market data — and different AVMs frequently disagree. W.A.L.T. cross-references three-plus AVM models into a consensus valuation, so loan-to-value is calculated from the weight of evidence rather than a single data point.

Q—06

Which data sources does W.A.L.T. integrate — credit agencies, Land Registry, Companies House?

18 live integrations, including Equifax, TransUnion and CreditSafe for credit; Rightmove, PropertyData and Realyse for valuations; HM Land Registry for title and liquidity; Companies House and OpenCorporates for corporate structure; SmartSearch, APLYiD, Veriphy and World-Check for KYC, AML and sanctions; and Open Banking for income verification.

Q—07

Who is W.A.L.T. built for?

Bridging lenders, development and specialist property lenders, and private credit desks that need fast, defensible decisions. It is built and used daily by Whitehall Lending, a specialist bridging finance provider in Mayfair, London.

Q—08

Can I subscribe to a single module, like KYC & AML or property valuation?

Yes. Each module runs on its own monthly subscription, priced on your monthly case volume, and you can upgrade to the full decision engine at any time. Book a demo and we'll send a quote matched to your volume.

Intelligent underwriting.
Instant confidence.

See a live decision in minutes — or book a demo on your own cases.