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Cogentiq Underwriting

Transform P&C underwriting and intelligence; beyond automation

Cogentiq Underwriting operates behind the scenes; delivering trusted data quality, risk indicators rules alone can't surface, and sharp insights on every single file

Transform P&C underwriting and intelligence; beyond automation

Cogentiq Underwriting operates behind the scenes; delivering trusted data quality, risk indicators rules alone can't surface, and sharp insights on every single file

Fractal named a 'Leader' in Agentic AI Service Providers PeMa 2025 by Analytics India Magazine
Fractal Named a “Leader” in The Forrester Wave™ : Customer Analytics Services, Q2, 2025

Underwriting teams aren’t short on judgment.
They’re buried in cleanup.

Submissions arrive with conflicting facts, stale data, missing evidence, and context scattered across documents and systems.
Before underwriters can assess risk, they must first untangle the submission itself.

Rework is becoming the default workflow

Underwriters spend too much time reconciling mismatched data, checking documents against systems, and validating details that should have been clear from the start.

Rework is becoming the default workflow

Underwriters spend too much time reconciling mismatched data, checking documents against systems, and validating details that should have been clear from the start.

Inconsistencies are hard to catch early

Contradictions across submissions, loss runs, statements of value, prior policies, and supporting evidence often surface only after they have already slowed the process.

Inconsistencies are hard to catch early

Contradictions across submissions, loss runs, statements of value, prior policies, and supporting evidence often surface only after they have already slowed the process.

Rules can’t resolve every judgment call

Rigid workflows struggle with borderline cases, exceptions, and context-heavy decisions, creating unnecessary referrals and inconsistent outcomes.

Rules can’t resolve every judgment call

Rigid workflows struggle with borderline cases, exceptions, and context-heavy decisions, creating unnecessary referrals and inconsistent outcomes.

The decision trail is fragmented

Notes, evidence, rationale, approvals, and exceptions are often spread across emails, files, portals, and core systems, making governance and audit review harder than it should be.

Quality issues show up when they cost more

Leakage, missing evidence, weak rationale, and overlooked risk signals are often caught late in the workflow, when fixing them means delays, rework, or downstream exposure.

Empowering underwriters with intelligence at every decision point

Cogentiq Underwriting sits inside your core systems to make every submission decision-grade, by running explainable conditional decisions, surfacing what rules alone miss, and continuously validating files with complete decision lineage. No rework and no second-guessing.

Data quality gaps > Manual reconciliation and rework

IT systems extract data, but underwriters still reconcile conflicts, chase brokers, and decide what to trust.

Getting to decision-grade data remains manual.

Data quality gaps > Manual reconciliation and rework

IT systems extract data, but underwriters still reconcile conflicts, chase brokers, and decide what to trust.

Getting to decision-grade data remains manual.

Rule engine blind spots > inconsistent decisions on borderline cases

Values just below a threshold pass silently; those just above hit a hard stop.

No context for grey areas, leading to excessive referrals or hidden risk.

Rule engine blind spots > inconsistent decisions on borderline cases

Values just below a threshold pass silently; those just above hit a hard stop.

No context for grey areas, leading to excessive referrals or hidden risk.

Fragmented decision context > no defensible audit trail

Decisions are scattered across notes, emails, and spreadsheets; hard to reconstruct who decided what and why.

No connected thread from intake through QA to catch recurring errors.

Post-bind QA lag > leakage discovered too late

QA reviews a fraction of cases after bind. Insights locked in spot checks.

No mechanism to feed findings back as real-time controls before decisions are made.

Post-bind QA lag > leakage discovered too late

QA reviews a fraction of cases after bind. Insights locked in spot checks.

No mechanism to feed findings back as real-time controls before decisions are made.

How it works, in your workflow

Four modules carry a submission from clean intake to continuous governance

Underwriting Assistant

Data triage

Owns

Submission intake and data processing

Challenges

Messy packs, duplicates, conflicting data
Manual cleanup slows everything down

How we help

Turn messy broker packs into a decision-ready submission
Surface what’s critical vs noise early
Generate targeted broker follow-ups, not generic emails

Senior underwriter

Rules Analyzer and Copilot

Owns

Risk Decision and Conditions

Challenges

Guidelines scattered across PDFs
Difficult to make consistent decisions on nuanced cases

How we help

Surface explainable triggers with evidence citations and risk intelligence beyond rules
Support Approve/ Approve-with-Conditions/Decline
Hold credits until evidence is verified; draft conditions with pre-built rationale

Underwriting manager

Quality Assurance Bot

Owns

Quality, Compliance, Leakage Control

Challenges

Decisions scattered across notes and emails
Problems discovered too late to prevent

How we help

Run automated pre-bind QA (not samples)
Get full decision lineage and condition compliance
Detect leakage and recurring issues early

Underwriting Assistant

Senior Underwriter

Underwriting Manager

Owns

Submission intake and data processing

Challenges

Messy packs, duplicates, conflicting data

Manual cleanup slows everything down

How we help?

Module: Data triage

Turn messy broker packs into a decision-ready submission

Surface what’s critical vs noise early

Generate targeted broker follow-ups, not generic emails

What improves when you control the decision

Outcomes

Day 1 impact

Sharp reduction in processing time

Executive impact

Significant combined ratio improvement

Operational scale impact

Improved QA coverage

Speed to market

Faster quote turnaround

Built for the real work on underwriting desks.

Intake

Store 360 & Segmentation

Submission reconciliation across contradictions, duplicates, and stale inspections.

Evidence-tied broker follow-ups with short, targeted asks.

Auto-resolution of non-material discrepancies to accelerate clean-file throughput.

Intake

Store 360 & Segmentation

Submission reconciliation across contradictions, duplicates, and stale inspections.

Evidence-tied broker follow-ups with short, targeted asks.

Auto-resolution of non-material discrepancies to accelerate clean-file throughput.

Intake

Submission reconciliation across contradictions, duplicates, and stale inspections.

Evidence-tied broker follow-ups with short, targeted asks.

Auto-resolution of non-material discrepancies to accelerate clean-file throughput.

Decisioning

Explainable rule triggers with guideline traceability.

Conditional approvals with structured subjectivities, tracked to completion.

Credit hold-until-proof leakage control.

Risk intelligence signals for financial health, boundary conditions, and regional exposure, assessed alongside rule outcomes.

Override capture with AI-assisted rationale drafting.

QA & Governance

Pre-bind validation on every case, with structured checks across completeness, guideline adherence, evidence quality, data freshness, and compliance.

Override and underwriter behavior analysis across batches, with AI-generated insights.

Pattern detection that feeds directly into control improvements.

Risk evaluation lists prioritized by severity and exposure for focused review.

Not passive data. Not just digitization. Expert-level underwriting decisions at scale.

Where the market stops, Cogentiq continues.

Data Platforms

Data platforms enrich data but can’t mark a submission decision-grade.

Cogentiq reconciles conflicts, scores severity, seeks information from agents, and makes the file trustworthy for underwriting decisions.

IDP & Workflow Tools

IDP and workflow tools extract and route but have no conditional approval logic or audit-ready lineage.

Cogentiq helps triage the data as essential for decisions, so every decision is defensible.

AI Triage & Research Tools

AI triage and research tools help decide what to look at but stop before curating on the risk context.

Cogentiq carries the submission from triage through rules, QA, and learning — no handoff gaps, no dead ends.

Core Systems

Core systems are backbone infrastructure.

Cogentiq sits above them, integrates in weeks, and delivers intelligence without rip-and-replace — your stack stays, the decisions get smarter.

Purpose-Built, In-House

The platform combines deep underwriting expertise, proprietary AI engineering, and enterprise-grade control to deliver differentiated outcomes that generic or bolt-on solutions cannot match.

Insights from leaders

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Rule engines are binary, risk is not

Transform underwriting quality assurance from reactive sampling to continuous AI-driven pre-bind validation. Prevent leakage, detect drift, and strengthen compliance.

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Decision-Grade Intake: How AI Fixes Underwriting Bottlenecks

Underwriting delays start at intake. Learn how AI-powered, decision-grade intake helps insurers accelerate quotes, improve risk quality, and scale underwriting.

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