arrow_circle_right FINANCE INDUSTRY – AGENTIC UNDERWRITING
Accelerate underwriting with Agentic AI
Agentic underwriting turns a slow, document-heavy risk assessment process into an efficient, transparent decision-making process. It can be built on the systems you already run as a working Lighthouse in weeks!
arrow_circle_right Our clients
They’ve trusted us
arrow_circle_right WHY AGENTIC UNDERWRITING
Leveraging AI for comprehensive underwriting at scale
40–60%
straight-through processing on the automated segment of the book
5×
faster first response to broker or client on submissions
97–99%
accuracy on extracted submission and policy data
90%
reduction in manual labour on repetitive document analysis
1 owner
a decision-maker on every material or escalated case
arrow_circle_right WHAT MAKES IT DIFFERENT
Your work focuses on creating a concise set of reusable, governed capabilities
Traditional automation projects rebuild logic for every product, market, and channel. In contrast, agentic underwriting breaks the underwriting journey into the decisions it actually requires – intake, triage, risk understanding, appetite, pricing, structuring, decisioning, learning. Each decision is built as a capability with a stable contract, detailing what it needs, what it produces, how confident it is, and when it hands back to a person.
The same capability then reuses across a second product line or a second market, so the marginal cost of each rollout drops instead of resetting to zero.
Better customer experience
Deliver relevant proposals faster, reduce waiting times, and respond more consistently to broker or customer needs.
Faster time to quote
Shorten the time from submission to proposal, helping insurers respond while the opportunity is still active.
Higher conversion
Improve the likelihood of winning business by getting suitable, competitive solutions to customers sooner.
Greater processing capacity
Handle more submissions without proportionally increasing underwriting effort.
Resilience to seasonal peaks
Scale processing capacity during periods of concentrated demand and reduce bottlenecks caused by limited underwriting resources.
How it works
One orchestrator, not one model
A central orchestrator manages the case state and directs each submission to the correct capability or combination of capabilities for the specific task in question.
Composite intelligence per task
Each capability uses the most appropriate mechanism, an LLM, a deterministic rule, a pricing model, a lookup or a person, but never an LLM by default.
Escalation by calibrated confidence
A reasoning trace is produced at every step. Only a named underwriter is called in where confidence or authority thresholds require it.
Integrated once, not per project
A shared integration fabric connects capabilities to core systems, rating engines, CRM and broker channels, so those systems can change without the AI being rewritten.
arrow_circle_right WHAT’S INSIDE
Reusable capability groups for lighthouse effect
As new capabilities are introduced to the organisation, they can be applied to more AI deployments, building on the skills that were previously tested.
Submission & triage
- Broker submission ingestion
- Extraction & structuring
- Completeness & duplicate checks
- Opportunity prioritisation
Risk understanding
- Document synthesis
- Internal/ external enrichment
- Geospatial & exposure context
- Historical claims context
Decision support
- Appetite & referral rules
- Risk scoring
- Pricing & rating
- Escalation triggers
Quote & bind
- Offer structuring
- Clause retrieval & generation
- Authority & compliance checks
- Core-system update
Governance layer
- Authority thresholds by task
- PII checks at every handoff
- Reasoning trail per decision
- Golden-dataset evaluation
Integration fabric
- API/ tool gateway
- Enterprise adapters
- Event bus & workflow engine
- Data contracts
arrow_circle_right HOW WE USE AI
How AI supports the process
AI-assisted: Submission intelligence
An agent extracts, structures and enriches broker submissions, resolving them into one clean record regardless of the format or channel through which they entered the business. Routine, high-volume tasks are carried out using the most cost-effective model that meets the required quality standards.
Human-accountable: Risk & pricing judgement
Ambiguous risk interpretation, complex clause synthesis and any pricing or bind decision above threshold route to a named underwriter. Every recommendation carries its evidence trail before it reaches them – they check the work, they don’t redo it.
arrow_circle_right HOW WE DELIVER
Your underwriting lighthouse, built full-stack from day one
Each phase produces a functioning part of the journey, as well as a reusable pattern for the next phase. Nothing is discarded between the MVP 1 and the scale-up.
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~4 weeks
Joint discovery workshops score candidate opportunities on value, automation potential, adoption readiness, regulatory fit and data readiness. MVP 1/ MVP 2 scope agreed.
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8–10 weeks
First live workflow, full agentic stack from day one, KPI baseline established for what comes next.
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6–8 weeks
Environment, integration and governance already proven, the remaining journey is built faster, KPI improvement demonstrated against baseline.
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4+ weeks
Capability roadmap, repeatable rollout framework and governance handed to your own team, factory model, not a one-off project.
arrow_circle_right IS THIS FOR YOU?
We’d rather tell you now than four weeks into a Lighthouse
Agentic underwriting is probably not the right fit if:
Your submission volumes on the candidate line of business are too low for automation to pay back within a year.
You want a single black-box solution rather than an orchestration layer you can audit decision by decision.
There’s no underwriting or IT sponsor available for a two-in-a-box team during the Lighthouse phases.
arrow_circle_right Our work
See the success stories of our clients
arrow_circle_rightContact us
Let’s review your underwriting opportunities
FAQ
Agentic underwriting uses AI agents and governed decision-making capabilities to streamline the underwriting journey, from submission intake and risk assessment to pricing and quote preparation. It automates repetitive tasks, improves response times, and provides transparent, auditable recommendations while keeping human underwriters accountable for material decisions.
Agentic underwriting can accelerate broker and client responses, improve data accuracy, reduce manual document analysis, and increase the number of submissions processed. Target outcomes include 40–60% straight-through processing on the automated segment of the book, 5× faster first responses, 97–99% accuracy in extracted submission and policy data, and up to 90% less manual labour on repetitive document analysis.
The solution connects to existing core systems, pricing and rating engines, CRM platforms, and broker channels through a shared integration layer. Its reusable capabilities can be deployed across products and markets without rebuilding the entire solution for each new implementation.
Each capability operates within defined rules, confidence thresholds, and decision-making boundaries. The system maintains a reasoning and evidence trail for decisions, applies compliance and data protection checks, and escalates complex, uncertain, or high-authority cases to a named human underwriter. AI supports the process, while people retain accountability for material underwriting.
The implementation process begins with a discovery and planning phase of approximately 4 weeks, followed by an MVP1 launch of 8–10 weeks. The MVP2 phase usually takes an additional 6–8 weeks, with subsequent scaling and rollout taking a further 4 weeks. Each phase delivers a functioning part of the underwriting process and creates reusable capabilities for future deployments.