InsuranceOperations

Claims cycle time and loss ratio visibility shouldn't require a month-end sprint to produce.

We connect your policy, claims, billing, and fraud systems so adjusters, actuaries, and operations leaders can see the full picture as it develops, not after the cycle closes.

35%
claims cycle reduction

Gain clarity on loss ratio trends, claims cycle time, and underwriting expense, with the infrastructure to act before results deteriorate.

The Challenge

The operational reality of insurance

01

Claims cycle times drift without anyone seeing which segments

Average cycle time is tracked but not by claims type, adjuster, or geographic segment. The overall number hides the pockets that are bleeding.

02

Loss ratios surface at quarter end

By the time the quarterly loss ratio report arrives, months of claims have been processed and the opportunity to intervene has passed.

03

Underwriting capacity is invisible across submission queues

Submission volume and adjuster capacity are not tracked against each other in real time. Bottlenecks build before anyone sees them.

04

Documents pile up faster than people can read them

Claims intake, prior authorization, and underwriting submissions arrive faster than human reviewers can process them. Backlogs grow and cycle times suffer.

Key Metrics

The KPIs we surface for insurance carriers and brokers

Loss ratio (loss and combined)
Claims cycle time
First notice of loss to close
Underwriting capacity and submission volume
Hit ratio and quote conversion
Fraud detection rate
Reserve adequacy
Customer retention
Producer performance
Expense ratio
Capabilities

How we help insurance operations

01

Claims analytics with cycle time root cause

Drill into claims cycle time by type, adjuster, segment, and geography. Surface where delays originate and why specific claim categories take longer than others.

02

Loss ratio modeling by segment

Rolling loss ratio models segmented by product, geography, underwriting cohort, and distribution channel. See emerging trends 30 to 60 days before quarter close.

03

AI document intelligence for claims and submissions

Automated extraction from claim forms, medical records, police reports, and underwriting submissions. Structure unstructured documents at scale.

04

Fraud signal detection

Statistical and ML models that flag unusual claim patterns, provider billing anomalies, and network fraud signals for adjuster review.

05

Underwriting capacity dashboards

Real-time view of submission volume, adjuster capacity, and queue depth across all lines of business. Prevent capacity crunches before they happen.

06

AI agents for claims triage and routing

AI triage agents that read new claim submissions, score severity and complexity, and route to the right adjuster queue automatically.

Integrations

Some of the systems we connect with

These are some of the platforms we connect. We integrate with almost any system. If you run it, we can likely work with it.

Guidewire
Duck Creek
Sapiens
Majesco
Salesforce Financial Services Cloud
Snowflake
Databricks
Guidewire
Duck Creek
Sapiens
Majesco
Salesforce Financial Services Cloud
Snowflake
Databricks
Use Cases

Where this applies

01

P&C carrier: claims cycle time root cause by adjuster

A P&C carrier had an average claims cycle time of 28 days but could not identify whether the delay was in triage, investigation, reserve setting, or payment processing.

Outcome

We built a claims funnel analytics dashboard that tracked time in each stage by claim type and adjuster. The carrier discovered 60% of cycle time was in investigation for a specific claim category. Targeted process changes reduced average cycle time to 19 days.

02

MGA: loss ratio trending 45 days early

A managing general agent could only assess loss ratios at quarter end. By then, the combined ratio for one product line had already exceeded acceptable bounds with no opportunity to respond.

Outcome

We built a rolling loss ratio model that updates weekly. The MGA now sees emerging loss trends 45 days before quarter close with enough time to take underwriting action.

03

Commercial carrier: AI claims triage for 400 daily intakes

A commercial lines carrier received 350 to 450 new claims daily. Initial triage required an adjuster to read each intake document and route manually, taking 15 to 25 minutes per claim.

Outcome

We deployed an AI triage agent that reads claim intake documents, scores severity and complexity, and routes to the correct adjuster queue. Average triage time dropped from 20 minutes to under 90 seconds.

Results

Outcomes you can expect

35%
Reduction in claims cycle time
12%
Improvement in loss ratio through earlier intervention
60%
Reduction in document processing time
Real-time
Underwriting capacity visibility
FAQ

Frequently asked questions

Get Started

See loss ratios and claims performance in real time.

Book a free call and we will show you what insurance analytics can deliver for your operations.