Shift Technology

Learning Objectives

• Understand Shift Technology's role in insurance fraud detection and claims AI
• Identify the platform's claims, underwriting, and SIU capabilities
• Evaluate when Shift fits an insurer's tech stack vs Verisk or in-house fraud detection

What Is Shift Technology?

Shift Technology is the AI-powered insurance fraud detection and claims-decisioning platform used by global P&C (Property and Casualty) and health insurers. The platform applies machine learning across claims, underwriting, and SIU (Special Investigations Unit) workflows — identifying suspicious claims for further investigation while accelerating processing of legitimate claims that don't require manual review.

The strategic positioning: while Guidewire provides the operational core systems and Verisk provides industry analytics, Shift focuses specifically on fraud detection and claims AI — competing with both incumbent insurance fraud platforms (NICE Actimize, in-house insurer tools) and broader insurance AI platforms.

Pricing & Customer Base

Custom enterprise pricing for global P&C and health insurance carriers.

Shift's pricing typically scales with claim volume and the number of insurance lines covered.

Core Capabilities

AI-Powered Claims Fraud Detection

The flagship capability. Shift's AI analyzes incoming claims for fraud signals:

• Staged accident patterns — auto claims with characteristics of organized fraud rings
• Exaggerated injury claims — workers comp or auto bodily injury with patterns inconsistent with reported events
• Provider-side health fraud — billing patterns indicating phantom services or upcoded procedures
• Identity fraud — claims tied to identity-theft patterns

Suspicious claims are routed to SIU teams; legitimate claims proceed through standard processing.

SIU (Special Investigations Unit) Workflow

Beyond initial detection, Shift supports the SIU investigation workflow:

• Case management for active investigations
• Network analysis identifying connections across claims (organized rings)
• Document review tools
• Investigation reporting

For SIU teams, Shift's tooling improves productivity vs purely manual investigation.

Underwriting Risk Analytics

Shift's AI extends to underwriting:

• New business risk signals — flagging applicants with suspicious profiles
• Renewal risk — identifying changes in risk that justify pricing adjustments
• Submission analytics — patterns across submission data

Health Insurance Fraud

Health insurance fraud has different dynamics than P&C — provider fraud (billing for services not provided), member fraud (eligibility manipulation, prescription fraud), organized health fraud rings. Shift's health-insurance-specific models target these patterns distinct from P&C use cases.

Subrogation Identification

A meaningful adjacent capability. Shift's AI surfaces subrogation opportunities — claims where another party (often another insurer) should bear financial responsibility. Insurance subrogation recovery is a substantial revenue line for many carriers; AI improves identification.

Claims Decisioning Beyond Fraud

Beyond fraud, Shift's claims-decisioning platform supports straight-through processing for legitimate claims that don't require manual review. Combined with fraud detection, this covers both ends of the claim spectrum: accelerate legitimate claims, investigate suspicious ones.

Strengths

• Insurance-specific AI: Trained on insurance claims data and patterns
• Multi-line coverage: P&C + health insurance fraud detection
• SIU workflow integration: Beyond detection into investigation
• Underwriting risk extension: Same AI capability across new business and renewal
• Subrogation identification: Adjacent revenue capture
• Claims decisioning platform: Both fraud and non-fraud claims
• Global insurer customer base: Established at major P&C and health insurers

Limitations & Considerations

• Insurance-only: Doesn't help banking, securities, or other financial-crime use cases
• Custom-quote pricing: Not transparent
• Implementation effort: Multi-month integration with claims systems
• Vendor concentration risk: Specialty vendors face larger broader-platform competitors
• AI accuracy trade-offs: False positives waste SIU time; false negatives let fraud through
• Less integrated with broader insurance platforms: Shift adds to Guidewire / Verisk rather than replacing
• Smaller than NICE Actimize across financial services: NICE Actimize is broader but less insurance-deep

Best Use Cases

When to choose alternatives:

• Broader financial-crime platform → NICE Actimize for AML + fraud + insurance
• Insurance core operational platform → Guidewire, Duck Creek, Insurity
• Insurance industry data + analytics → Verisk Analytics for underwriting + claims analytics
• Property catastrophe modeling → Verisk or Moody's RMS
• In-house fraud development → some large insurers build internal teams instead

Key Takeaways

• Shift Technology is the AI-powered insurance fraud detection and claims-decisioning platform used by global P&C and health insurers
• Applies machine learning across claims fraud detection, SIU investigation workflows, underwriting risk analytics, subrogation identification, and claims decisioning beyond fraud
• Insurance-specific AI trained on insurance claims data — captures industry-specific patterns (staged accidents, organized rings, provider fraud) that generic fraud platforms miss
• Multi-line coverage across P&C and health insurance, with the same AI capabilities extending across claims, underwriting, and renewal workflows
• Best fit for global P&C and health insurers; for broader financial-crime needs across banking + insurance use NICE Actimize; for core insurance operational systems use Guidewire; for industry analytics use Verisk