Insurance & Payers
Governed AI for payers, claims, underwriting, and member services.
Kriv AI builds compliance-first AI for health plans, P&C insurers, and specialty carriers. Every deployment is documented, auditable, and aligned to NAIC, HIPAA, and state insurance regulations before it goes live.
For health plans, P&C insurers & specialty carriers
Claim intake
→ PHI stays in your perimeter
Governed model scores it
→ Decision + reason logged
Fairness & policy gate
→ NAIC-aligned controls
Human review where required
→ Physician / SIU in the loop
Pay, deny, or route
→ Auditable end-to-end trail
$79B+
US healthcare fraud, waste & abuse annually
NAIC
Model Bulletin on AI, compliance is now required
Prior auth
Biggest operational bottleneck for payers
3 wks
Typical Kriv AI time to governed delivery
The governance gap
Insurance AI without governance is a regulatory event waiting to happen.
The same risks, at every payer we talk to. Kriv AI builds the governance infrastructure first, then the capability.
The NAIC Model Bulletin is in force
State regulators are asking how AI is used in underwriting and claims decisions, and expecting documented answers. Most payers can't produce them.
AI is already in production without governance
Models are scoring claims and routing members today, without the audit trails, fairness documentation, or named accountability structures regulators now require.
PHI flows through every workflow
Claims, prior authorization, and member services all touch protected health information, so every AI deployment is a HIPAA and state-regulation exposure if it isn't designed for it.
Fraud crosses into financial-crime territory
For P&C and specialty lines, fraud patterns can trip FinCEN reporting thresholds. Detection built without that in mind becomes a liability, not an asset.
Explainability arrives too late to matter
Underwriting and reserving models reach production before anyone can explain a decision to an auditor, the board, or a regulator. By then it's expensive to fix.
Use cases
Where governed AI changes payer economics.
01
Claims fraud detection
ML scoring on claims submission patterns, provider behavior, and billing anomalies. Reduces manual review burden, surfaces high-risk claims before payment, and builds an auditable fraud trail.
02
Prior authorization automation
LLM-assisted prior auth review that extracts clinical criteria, cross-references medical policy, and produces a documented recommendation, keeping a physician in the loop where required.
03
Underwriting risk scoring
Data pipeline integration from structured and unstructured sources into a governed underwriting model. Explainability built in from day one.
04
Member services AI
Intelligent routing and resolution for member inquiries. Reduces escalation volume while maintaining the audit trail regulators expect for AI-assisted member interactions.
05
Reserving analytics
Actuarial-grade pipeline automation: data ingestion, loss triangle modeling, and scenario analysis, delivered as a governed workflow with documented assumptions and version control.
06
Regulatory reporting automation
Extract, transform, and validate for state and federal reporting requirements. NAIC filings, CMS submissions, and state-specific mandates with data lineage built in.
Your operations
Pick the operation, see what we feed it and how we keep it governed.
Four places payers put AI to work first. Every one ships with the audit trail and the human gates regulators expect.
Claims & fraud operations
ML scoring surfaces high-risk claims before payment and routes the rest straight through, with every decision logged into an auditable fraud trail your SIU and compliance teams can defend.
What it works on
- Claims submission patterns
- Provider behavior signals
- Billing anomalies
- Historical adjudication data
What you get
Governed AI for payers. Built to pass the audit.
$80B+
US healthcare fraud, waste & abuse the industry loses each year.
3 wks
Typical time from kickoff to a governed delivery.
NAIC
Model Bulletin on AI, treated as a design constraint.
- Documented, auditable AI for claims, underwriting, and member services.
- Fairness controls and decision logs your regulators can review.
- PHI that stays inside your security perimeter, BAA available.
- Explainability designed in.
- A governance framework you can show the board and state examiners.
Compliance framework
Built for the regulations already in force.
We design to the rules you already answer to, so the deployment is defensible the day it goes live.
Security, privacy & complianceNAIC Model Bulletin on AI
The NAIC Model Bulletin requires insurers to document how AI is used in underwriting and claims decisions, maintain audit trails, and demonstrate fairness controls. Every Kriv AI deployment is built with this as a design constraint.
HIPAA & state health regulations
Health payers handle PHI across claims, authorization, and member services. Our architectures are HIPAA-eligible by default, BAA available, audit logging standard, no PHI leaving your security perimeter.
FinCEN & anti-fraud obligations
P&C and specialty insurers face FinCEN reporting requirements when fraud patterns cross financial crime thresholds. Our fraud detection builds for this from day one.
Who we work with
Practitioners who own the risk and the results.
Our engagements are scoped with the people who will be accountable for outcomes, not just the project sponsor.
VP of Claims
Responsible for claims processing cost, cycle time, and accuracy. Wants fraud detection and prior auth automation that won't create new compliance exposure.
Chief Actuary / VP Underwriting
Accountable for the models behind pricing and reserving. Needs explainable AI, regulators, internal audit, and the board all ask questions.
CDO / VP of Data & Analytics
Building the data platform that enables AI. Needs governance infrastructure, data lineage, and a deployment model that IT and legal will actually approve.
CIO / VP Technology
Owns the integration surface, core admin systems, EHRs, clearinghouses. Evaluating AI vendors against security, compliance, and implementation risk.
Straight answers
Payer & health-plan questions
Is your AI HIPAA-aligned for handling PHI?
Yes. Our architectures are HIPAA-eligible by default, a BAA is available, audit logging is standard, and PHI never leaves your security perimeter. We assume regulated constraints from the first design conversation.
How do you address the NAIC Model Bulletin on AI?
We treat it as a design constraint. Every deployment documents how AI is used in underwriting and claims decisions, maintains audit trails, and demonstrates the fairness controls the bulletin expects, so you can produce documented answers when a state regulator asks.
Can you automate prior authorization without removing the physician?
Yes. Our prior auth review extracts clinical criteria, cross-references medical policy, and produces a documented recommendation, but keeps a physician in the loop wherever regulation or risk requires it. The goal is faster, defensible decisions.
Will your underwriting models be explainable to regulators?
Explainability is built in from day one rather than retrofitted. When regulators, internal audit, or the board ask how a pricing or reserving decision was made, the documentation and decision logs already exist.
Do you work with P&C and specialty carriers, or only health plans?
Both. We work with health plans, P&C insurers, and specialty carriers. For P&C and specialty lines we also build fraud detection that accounts for FinCEN reporting thresholds when fraud patterns cross into financial-crime territory.
How quickly can you deliver something governed?
Typical time to a governed delivery is around three weeks. We start with a focused assessment or a single high-value workflow, build the governance infrastructure first, then the capability, and expand from there if there's a fit.
Do you require direct access to our core admin systems?
Not necessarily. We're comfortable working through APIs, clearinghouse feeds, curated views, or data products defined by your teams, and we scope the integration surface with the people who own it, core admin systems, EHRs, and clearinghouses.
Start here
Governed AI for payers, built to pass the audit.
Claims fraud, prior auth, underwriting, member services, bring the workflow you're under pressure to automate to a 30-minute working session, and we'll map a governed path your compliance team and your state examiners can both stand behind.
+1-732-433-5564 · info@kriv.ai · East Brunswick, NJ
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