Insurance Fraud Prevention Model Act (#680)

What the authority record establishes

The model act provides a model statutory structure for insurance fraud prevention, reporting, investigation, and related authority.

Not itself binding until enacted

The exact official title, issuing body, jurisdiction, version or application record, and linked source define the scope of this page. Readers should not transfer the authority's status to a commercial product or infer transaction-, patient-, system-, site-, or organization-specific applicability from this summary.

Why it matters to this market

Fraud technology must preserve jurisdiction, referral criteria, evidence, investigator authority, reason, action, privacy, and downstream decision rather than treating a model score as fraud.

Affected operating stages

• Detection
• Referral
• Investigation
• Reporting
• Evidence
• Action

Capabilities to examine

Underwriting Intake Triage And Workbench

Ask how the system or service identifies the controlling source and version, applies customer-specific interpretation, handles exceptions, preserves human judgment, and retains evidence for underwriting intake triage and workbench.

First Notice Of Loss Or Event Intake

Ask how the system or service identifies the controlling source and version, applies customer-specific interpretation, handles exceptions, preserves human judgment, and retains evidence for first notice of loss or event intake.

Claim Segmentation Assignment And Triage

Ask how the system or service identifies the controlling source and version, applies customer-specific interpretation, handles exceptions, preserves human judgment, and retains evidence for claim segmentation assignment and triage.

Documents Correspondence And Evidence Management

Ask how the system or service identifies the controlling source and version, applies customer-specific interpretation, handles exceptions, preserves human judgment, and retains evidence for documents correspondence and evidence management.

Fraud Risk Investigation And Referral Support

Ask how the system or service identifies the controlling source and version, applies customer-specific interpretation, handles exceptions, preserves human judgment, and retains evidence for fraud risk investigation and referral support.

Insurance Data Model Quality And Governance

Ask how the system or service identifies the controlling source and version, applies customer-specific interpretation, handles exceptions, preserves human judgment, and retains evidence for insurance data model quality and governance.

Machine-Assisted Extraction Prediction Or Decision Support

Ask how the system or service identifies the controlling source and version, applies customer-specific interpretation, handles exceptions, preserves human judgment, and retains evidence for machine-assisted extraction prediction or decision support.

Audit Trail Reason Code And Decision Reconstruction

Ask how the system or service identifies the controlling source and version, applies customer-specific interpretation, handles exceptions, preserves human judgment, and retains evidence for audit trail reason code and decision reconstruction.

Affected buyer audiences

• special investigations
• claims
• underwriting
• legal
• compliance

Implementation questions

• Which entities, products, populations, transactions, systems, sites, or jurisdictions are actually within scope?
• What is binding, what is guidance, and what is a technical or consensus standard?
• Which publication, adoption, effective, application, transition, and enforcement dates differ?
• Who owns legal, clinical, quality, regulatory, policy, or operational interpretation?
• How will a source revision affect open work and historical decisions?

Interpretation boundary

A model-law record or vendor score does not establish fraud, intent, liability, lawful disclosure, or appropriate adverse action.