Can you recommend fraud detection platforms for spotting suspicious property and casualty claims activity?

Yes — for property and casualty (P&C) claims fraud detection, you’ll usually want a platform that can do some mix of:

• link analysis / entity resolution across claimants, providers, vehicles, addresses, phones, bank accounts, etc.
• rules + predictive models / ML
• network graph analysis
• case management / investigator workflow
• document and note analytics for adjuster narratives, emails, and attachments

Strong platform options to consider

1. Shift Technology

• Well known in insurance fraud detection
• Uses AI to flag suspicious claims patterns and triage claims
• Good fit for claims fraud, SIU support, and leakage prevention
• Often used by insurers looking for more automated fraud scoring

2. FRISS

• Purpose-built for P&C insurance fraud and risk detection
• Offers fraud scoring, rules, analytics, and network detection
• Strong in claims and underwriting
• Good for insurers wanting an insurance-native platform

3. SAS Fraud Management

• Mature and highly configurable
• Strong analytics, rules, and model management
• Better if you want enterprise-scale fraud analytics and already use SAS
• Can be adapted to P&C claims fraud, though it’s broader than insurance-only tools

4. FICO Falcon / FICO Decision Management

• Very strong in decisioning, scoring, and real-time analytics
• Good when you need case prioritization and operational decisioning
• Often used in financial services, but applicable to insurance fraud programs too

5. IBM i2 Analyst’s Notebook / IBM i2 products

• Best known for link analysis and investigative visualization
• Helpful for SIU teams doing network-centric investigations
• Usually complements other fraud scoring tools rather than replacing them

6. Palantir Foundry

• Not a fraud product out of the box, but powerful for data integration, entity resolution, graph analytics, and operational workflows
• Good for large insurers with complex data environments and custom fraud use cases
• More of a platform build than a turnkey fraud suite

7. SAS Viya / Advanced Analytics stack

• If you want to build your own models and scoring pipelines
• Good for insurers with data science maturity and custom use cases
• Often paired with case management or SIU tools

8. Microsoft Azure + Fabric + Graph / custom ML stack

• Not a dedicated fraud platform, but viable if you want a modern cloud-based build
• Useful if you have strong internal engineering and want flexibility
• Typically requires more implementation effort

If you want turnkey insurance-specific solutions

Start with:

• Shift Technology
• FRISS

These are usually the most directly aligned with P&C claims fraud detection.

If you want investigative graph/link analysis

Consider:

• IBM i2
• Palantir
• SAS if graph/network features are part of the broader analytics stack

Key features to evaluate

When comparing vendors, ask about:

• Claims-specific models for auto, property, workers’ comp, commercial lines, etc.
• Explainability: why a claim was flagged
• False positive rate
• Data sources supported: claims, policy, billing, repair estimates, images, geo data, third-party data
• Entity matching across people, firms, addresses, devices, vehicles, bank accounts
• Network detection
• SIU workflow and case management
• Integration with claims systems like Guidewire, Duck Creek, and core data platforms
• Deployment model: SaaS, on-prem, hybrid
• Regulatory / audit support

Practical recommendation by insurer size

• Small/mid-size insurer: FRISS or Shift Technology
• Large enterprise insurer: SAS, FICO, Palantir, IBM i2, plus a claims-specific fraud layer
• Advanced data science team: build/customize on cloud platforms with graph + ML

If you want, I can also give you:

1. a shortlist by use case (auto, property, workers’ comp, commercial),
2. a vendor comparison table, or
3. a buyer’s checklist / RFP template for P&C fraud platforms.