Insurance
Stop loss leakage before the payout clears.
PrismBase builds production AI for insurers, real-time claims fraud detection, underwriting risk models, and policy document intelligence, on the same pipeline architecture we shipped for federal fraud at 10TB+/day. One senior principal, deployed systems your team owns, not a slide deck.
1–3 pts
Loss-ratio points recoverable through earlier fraud and leakage detection
sub-second
Fraud scoring at claim intake, the same latency we hit on federal transaction fraud
2 wk
From kickoff to a quantified leakage diagnostic on your own claims data
Insurance AI use cases
Each maps to a number your CFO tracks, loss ratio, expense ratio, or quote-to-bind cycle time, not model accuracy on a slide.
Real-time claims fraud detection
Score every FNOL for fraud and leakage signals at intake, sub-second, so suspicious claims route to SIU before payout instead of being clawed back after settlement. Built on the ensemble-scoring pipeline pattern we ran against multi-terabyte federal transaction fraud.
Claims triage & straight-through processing
Auto-classify and route incoming claims by complexity and severity. Adjusters spend hours on high-value and high-risk files; clean low-complexity claims flow straight through.
Underwriting risk models
Consistent, explainable risk pricing across underwriters and lines. Bind more policies at the right premium instead of defaulting to the safe rate, with monitoring and drift detection in production.
Policy & submission document intelligence
Extract endorsements, limits, exclusions, and schedules from ACORD forms, submissions, and loss runs in minutes. Faster quote-to-bind on commercial lines and fewer manual data-entry errors.
Subrogation & recovery prioritization
Surface recoverable claims and rank them by expected recovery so recovery teams work the files that actually pay back, not a chronological queue.
Retention & agent/broker intelligence
Predict policy non-renewal early and rank producer relationships by lifetime value, so retention outreach and sales effort land where they move premium.
Proof · Adjacent domain
Real-time fraud detection at 10TB+ daily
Deployed an ensemble ML pipeline processing full transaction volume in real time with sub-second scoring, monitoring, and incident runbooks.
Claims fraud is the same problem shape as transaction fraud, high volume, imbalanced labels, adversarial patterns. This is the pipeline architecture we bring to your loss ratio.
Read full case study →6 weeks
POC to production
6 weeks from kickoff to production deploy
Productized entry point
Claims Fraud & Loss-Leakage Diagnostic
$7,500 · 2 weeks
A fixed-fee, 2-week diagnostic on your own claims data: we quantify recoverable loss leakage, benchmark your current fraud detection, and hand you a prioritized model roadmap with projected loss-ratio impact. Low-risk proof of capability before any larger build.
- Leakage and fraud-signal analysis on a sample of your historical claims
- Quantified estimate of recoverable loss-ratio points
- Benchmark of current rules/vendor detection vs. an ML baseline we build
- Prioritized production roadmap with projected ROI and effort
- Executive readout for claims, SIU, and finance stakeholders
Why insurers choose PrismBase
- Provable fraud depth: real-time detection shipped at federal financial scale (10TB+/day), the exact problem shape as claims fraud
- Production Standard: deployed models, monitoring, drift detection, and incident runbooks, not a notebook prototype
- Explainable, auditable models built for regulated review, model cards and lineage from day one
- Senior principal builds and deploys, you work directly with the person doing the work
- IP transfer included: your team owns the models, pipelines, and documentation at handoff
The Production Standard
The Production Standard
Six commitments contracted in writing on every engagement.
01
Deploy or redirect
If AI isn't the right tool, we say so in week one and redirect budget to what will ship. No POC theater.
02
Metrics before models
Business KPIs locked in discovery. Model selection follows the metric, not the hype cycle.
03
Governance from day one
Model cards, access controls, evaluation harnesses, and audit trails, not a compliance bolt-on at go-live.
04
Production artifacts
Deployed code, monitoring dashboards, CI/CD pipelines, and incident runbooks. Not recommendations for someone else to implement.
05
6-week production target
Scoped projects designed for production in 6–10 weeks. Boutiques move; global programs wait for steering committees.
06
Capability transfer
Your team can operate, extend, and maintain what we build. IP and documentation transfer is included, not upsold.
Every scoped project includes a production deliverable checklist signed off before close. If we can't commit to deployable output, we won't take the engagement.
Frequently asked questions
Have you actually deployed fraud detection, or just for insurance?
We have shipped real-time fraud detection to production at federal financial scale, over 10TB per day, with sub-second scoring, drift monitoring, and incident runbooks. Claims fraud is the same problem shape: high-volume events, imbalanced labels, and adversarial patterns. Insurance is a growth sector for us where that proven pipeline architecture transfers directly. We are transparent about that on the first call.
What lines of business do you work with?
The approach is line-agnostic, P&C, commercial, specialty, and workers' comp all share the same claims-fraud, underwriting-risk, and document-intelligence patterns. We scope to the lines and data you actually have in the diagnostic.
How does the diagnostic work with our data?
We execute an NDA, then work against a sample of your historical claims under a data-boundary agreement. The 2-week diagnostic quantifies recoverable leakage and delivers a prioritized roadmap with projected loss-ratio impact, low risk, fixed fee, before any larger engagement.
Are the models explainable enough for regulators?
Yes. We build explainable, auditable models with model cards, feature lineage, and human-in-the-loop review for low-confidence decisions, designed to support your compliance and market-conduct review. Formal regulatory filing remains client-owned with your compliance partners.
How fast can we get to production?
The diagnostic is 2 weeks. A scoped production build typically follows in weeks, not quarters, our federal fraud system went from POC to production in six. Timelines are locked to KPIs in the SOW, not open-ended.
Cut your loss ratio, not another POC.
Tell us your lines of business, claims volume, and where leakage hurts most. We'll sign an NDA and scope the $7,500 diagnostic against your own data, low risk, fixed fee, quantified before you commit to a build.
Start a confidential conversation