FinLend
Lending decisioning, risk & document intelligence
Underwriting that runs on your own infrastructure. FinLend reads a borrower document pack, scores the risk with an explainable model, and puts an on-prem assistant on the file, so the decision and the reasons behind it both take minutes. Every score traces back to its inputs for adverse-action review.
- Reads loan filesany format · any layout
- Policy checksagainst your rules
- Risk scoringexplainable
- Gap detectionmissing & inconsistent
- Auto-filled fileready to decide
Problem vs solution
Underwriting capacity is capped by people reading documents.
How this normally goes
An analyst parses financials, retypes them, chases what is missing, then screens names in a separate tool. Speed that up with a model nobody can interrogate and you trade a throughput problem for a fair-lending problem.
What we deploy instead
Extraction, scoring and screening as one pipeline with a human at the decision point. The score is gradient boosting explained through SHAP, so every outcome traces to the factors that moved it.
Presales and Discovery
What our architects hand you before implementation starts.
Book an architecture sessionSystem Design
How the pipeline meets your loan origination system, and where the human review gates sit.
Model governance plan
What the score is built on, how it is monitored, and what your regulator will ask for.
Data residency map
What runs on-prem, what may leave, and what that means for your policy.
Infrastructure sizing
What the on-prem footprint costs at your application volume.
Under the hood
Document intelligence
Reads the borrower package in whatever layout it arrives, routing low-confidence fields to a reviewer instead of into the decision.
Explainable risk
Gradient boosting with SHAP attribution, so adverse-action review has an answer rather than a number.
On-prem sanctions matching
Names matched locally against OFAC SDN and Consolidated lists. Nothing leaves your network.
Twenty risk and compliance checks
Sanctions, PEP and adverse media, credit, KYB and KYC, bankruptcy, on every application.
On-prem AI over the file
Answers from the borrower documents, including what would have to change for the decision to change.
Team and audit control
Passwordless email-code sign-in with admin user management for the underwriting team.
A full borrower package read, scored and screened.
Reading, data entry and screening automated.
Every borrower and guarantor checked on every file.
Sanctions, PEP, credit, KYB, KYC and bankruptcy.
Level of customization
Yours to change
Policy rules, score thresholds, the document set, the review gates, and which signals are decisive.
What we keep stable
Explainability and the audit trail. A score you cannot trace is a score you cannot defend.
How it ships
On your infrastructure, including air-gapped, with the model artefacts and the pipeline under your control.
ROI and economics
What you do not build
Layout-independent extraction, a scoring pipeline with attribution, local list matching, and the review workflow that keeps a person accountable.
Where the calendar goes
Not the first parsed document, but the long tail of formats, the model governance, and proving the decision path to a regulator.
Capacity, not headcount
Throughput rises against the same team, and analyst hours move from transcription to credit judgement.
Where this fits
A good fit
Regulated lending at volume, documents you cannot send to a third-party API, and a decision that must be explainable after the fact.
Not a fit
Consumer lending with a thin, standardised application where a bureau score already decides. We will say so in Discovery.
Seen in the field
Client work where FinLend did the heavy lifting.
Document-AI underwriting pipeline for a regional US bank
Regional US bank
A regional US bank replaced manual document reading with an AI intake pipeline it now owns. Every loan application arrives extracted, checked, and flagged for gaps before an underwriter opens the file.
Part of Lending
Credit decisions your team can make in minutes and defend for years.
Underwrite faster,
without the manual read.
Bring us the bottleneck, whether it is decisioning, document processing or servicing, and we'll scope the system that clears it.