Autonomous underwriting engine
A governed, multi-agent platform that automates risk assessment, document review and decisioning — turning weeks of manual underwriting into minutes.
The brief
A global lender's underwriting ran on people and paper. Applications moved through queues of analysts who gathered documents, checked them by hand, assessed risk, and signed off — a process measured in weeks, with cost and consistency that scaled linearly with volume.
They needed to compress that to minutes without losing control. In a regulated business, 'faster' is worthless if it isn't governed: every decision had to be explainable, auditable, and reversible wherever the rules demanded human sign-off.
- Replace weeks of manual underwriting with a system that decides in minutes.
- Automate risk assessment, document review and decisioning end to end.
- Keep every decision governed, explainable and auditable for regulators.
- Hold a human approval gate on edge cases and high-value decisions.
- Integrate securely with existing core systems and data sources.
- Improve decision accuracy while cutting operational cost.
Our AI-native approach
We engineered a multi-agent platform where specialised agents own the discrete steps of underwriting — document intake and extraction, risk assessment, policy checks, and a decisioning agent that assembles the case. Each agent acts only through governed, permissioned tools, and the whole flow is traced end to end.
The system is decision-support with teeth: low-risk cases flow straight through, while edge cases and high-value decisions pause for human approval. AI provides the speed; governance provides the trust.
What we built
Document intake & extraction
Agents read and structure submitted documents automatically, with confidence on every field.
Risk assessment agent
Models score applicant risk against policy and historical data, with the driving factors made explicit.
Policy & compliance checks
Every case is validated against the lender's rules and regulatory constraints automatically.
Decisioning agent
Assembles the assessed case into a recommended decision with a full, reviewable rationale.
Human approval gates
Edge cases and high-value decisions pause for an underwriter's sign-off.
Audit & traceability
Every step, input and decision is logged for regulators and internal review.
How we built it
We treated the platform as regulated production software from day one: structured tool-calling over free text, typed and permissioned integrations, retries, and an evaluation harness that scored decision quality against historically adjudicated cases before anything touched live applications.
Delivery was incremental — we proved one product line end to end, validated accuracy and the approval gates against real outcomes, then expanded. A senior pod owned orchestration, the risk models and governance together, so capability and control scaled in lockstep.
How it works
Intake
Applications and documents enter and are structured.
Assess
Risk and policy agents score the case against rules and data.
Decide
The decisioning agent assembles a recommendation with rationale.
Gate
Edge and high-value cases pause for human approval.
Record
Every step is logged for audit and continuous learning.
The platform's strength is orchestration under governance: specialised agents reason over structured tools rather than free text, which is what makes automated decisions reliable enough to trust in a regulated setting. Explainability is built in — every recommendation carries the factors that drove it.
An evaluation harness benchmarks decisions against historically adjudicated cases, so accuracy is measured, not assumed, and regressions are caught before release.
The impact
Underwriting that took weeks now resolves in minutes for straight-through cases.
Operating cost fell sharply while volume capacity rose.
Every decision became explainable and auditable end to end.
Underwriters moved from manual review to high-value exception handling.
Technology stack
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