Shift Claims Fraud Detection
Shift Claims Fraud Detection: Cloud software that prioritizes suspicious claims and helps investigate fraud networks. Ranked #29 of 30 in Insurance Analytics Software by our editors (6.7/10); pricing: Pricing on request; best for enterprise claims fraud investigation.
At a glance
- Editor score6.7 / 10
- PricingPricing on request
- Best forEnterprise claims fraud investigation
- Facts checked29 Sep 2026
Where it wins
- Scores claims and prioritizes alerts for investigation
- Analyzes claims text, scanned documents, images, and videos
- Resolves entities and visualizes suspicious relationships
Where it doesn't
- Focused on claims fraud rather than broader insurance analytics
- Pricing is available through sales contact rather than published plans
- Guidewire ClaimCenter is the only named integration
Our verdict on Shift Claims Fraud Detection
Shift Claims Fraud Detection is cloud software for property and casualty insurers investigating suspicious claims. It is aimed at enterprise claims teams and special investigation units that need to identify individual and network fraud, then direct handlers toward cases for review. Its scope is claims fraud detection and investigation rather than a broad suite of insurance analytics.
The standout capability is its treatment of varied claims evidence. The system scores claims against fraud scenarios, uses automatic anomaly detection and natural language processing, and analyzes structured data alongside scanned documents, images, and videos. It can also use external location and weather data. Data cleansing and entity resolution help connect information that may point to hidden relationships; network visualizations give investigators a way to examine those connections. Prioritized alerts include explanations and contextual guidance, while real-time metrics track activity and cost savings.
For insurers using Guidewire ClaimCenter, that named integration may help the product fit an existing claims workflow. The vendor describes the offering as SaaS-based, with cloud deployment, and sells it through a demo or sales contact rather than published prices. That means buyers will need to discuss commercial terms directly with Shift Technology. Teams seeking a focused system for fraud triage and investigation may find the feature set relevant; organizations looking for broad analytics beyond claims fraud, or a solution centered on a wider set of named integrations, should compare alternatives before choosing it.
Shift Claims Fraud Detection pricing
Shift Claims Fraud Detection fact sheet
| Free plan | Not verified |
|---|---|
| Paid from | Not verified |
| Analytics areas | Claims fraud detection; individual and network fraud; anomaly detection; claims investigation and triage |
| Modeling methods | Automatic anomaly detection; privileged learning from fraud-handler classifications; natural language processing; entity resolution; AI-based fraud scenario scoring |
| Catastrophe modeling | Not verified |
| Deployment | Cloud |
| Data connectors | Structured and unstructured claims data; scanned documents; images; videos; external location and weather data |
| Output formats | Not verified |
| Deployment | Cloud |
| Platforms | Web |
| Built for | Enterprise (editorial estimate) |
| Integrations | 1 integrations: Guidewire ClaimCenter |
| Pricing | Pricing on request |
| Website | shift-technology.com |
| Facts checked | 29 Sep 2026 |
Shift Claims Fraud Detection integrations
Shift Claims Fraud Detection lists 1 integrations on its own site.
- Guidewire ClaimCenter
Alternatives to Shift Claims Fraud Detection
- Aon PathWiseA broad actuarial and risk platform for enterprise life and annuity insurers and reinsurers.9.4
- FIS Insurance Risk SuiteA broad actuarial and risk suite for insurers that need connected modeling and reporting.9.3
- SAS InsuranceA broad insurance analytics portfolio for insurers managing actuarial, capital and regulatory work.9.2
See all Shift Claims Fraud Detection alternatives →
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Reviewed by iTechGuides Editors · Editorial team · Updated Sep 2026
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