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Quantiphi AI for Insurance from Quantiphi
Combines advanced analytics and machine learning to optimize underwriting, improve claims management, and enhance customer experience in the insurance industry.
Product analysis by function
Predictive Analytics Platforms for Business Intelligence and Analytics
Advanced tools that use statistical models and machine learning to predict future outcomes like claim frequency, severity, customer retention, and fraud probability.
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Data Integration
(11 Yes /11 Known /13 Possible features)
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Multi-source Data Connectivity Ability to integrate and ingest data from various sources such as databases, cloud platforms, spreadsheets, and APIs. |
Quantiphi advertises broad data integration with cloud, APIs, and insurers’ core systems as part of its insurance analytics platform. | |
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Real-time Data Sync Real-time synchronization of incoming data streams for up-to-date predictions. |
Quantiphi highlights real-time data processing and analytics for insurance, indicating real-time data sync is supported. | |
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Data Cleansing Tools Automated tools to clean, deduplicate, and normalize raw insurance data. |
Quantiphi mentions advanced data processing, including data cleaning and preparation, in its AI offerings for insurance. | |
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Batch Processing Speed The rate at which batch data loads or ETL jobs are run. |
No information available | |
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Automated Data Mapping Automatic mapping of data fields from source systems to platform schema. |
Automatic mapping is a standard feature in Quantiphi’s machine learning pipeline automation. | |
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Data Enrichment APIs Integration with third-party services to enrich internal data (e.g., credit scores, vehicle history). |
Quantiphi partners with and integrates third-party enrichment data providers (e.g. vehicle history, geospatial, credit). | |
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Historic Data Upload Limits Maximum volume of historic data that can be uploaded for modeling. |
No information available | |
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Schema Change Detection Detection and alerting when upstream data schemas change. |
The platform supports schema change management and alerting as part of integration connectors. | |
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Event-driven Updates Support for updating models or insights when new events/data arrive. |
Event-driven updates are supported as Quantiphi AI triggers workflows/models as new data/events are ingested. | |
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Data Lineage Tracking Traceability of data sources and transformations for audit and compliance. |
Quantiphi provides data lineage tracking in its platform for compliance and auditability. | |
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Data Privacy Controls Built-in tools for masking or redacting sensitive PII (personally identifiable information). |
Data privacy, redaction, and masking are featured for compliance (PII handling) in Quantiphi’s insurance stack. | |
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Integration with Core Insurance Systems Connections with policy administration, claims, underwriting, and customer management systems. |
Quantiphi offers pre-built connectors for core insurance systems (policy, claims, underwriting). | |
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Partner Data Sharing Secure tools and permissions for controlled sharing of datasets with partners. |
The platform supports controlled, secure data sharing with broker/partners via role-based access and workflows. |
Model Building & Customization
(13 Yes /13 Known /13 Possible features)
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Graphical Model Builder Drag-and-drop or visual tools for constructing predictive models without code. |
Quantiphi offers drag-and-drop and visual model building tools as part of their low-code/no-code environment. | |
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Custom Algorithm Support Ability to author, import, and use custom algorithms in analytics pipelines. |
Users can author/import custom algorithms; Python/R/Spark support in advanced use cases. | |
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Automated Feature Engineering Automatic creation and selection of predictive features from raw insurance data. |
Automated feature engineering is a part of Quantiphi’s ML workflow, enabling creation/selection of predictive features from raw data. | |
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Hyperparameter Tuning Tool-assisted searching for optimal model parameters. |
Hyperparameter tuning is available in the automated ML toolkit. | |
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Model Versioning Automatic tracking and management of model versions and their metadata. |
Full model versioning is included, tracking metadata and deployments. | |
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Pre-built Insurance Models Library of industry-specific models, e.g., for claim frequency, fraud detection, churn prediction. |
Pre-built models for claim frequency, fraud, churn etc. are key selling points mentioned for insurance. | |
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No-Code/Low-Code Interface Options for business users to create models without programming knowledge. |
Quantiphi offers low-code/no-code tools for business user modeling. | |
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Code-based Model Support Support for Python, R, or other programming languages for building custom models. |
Support for code-based models (Python/R); relevant for custom/advanced data science teams. | |
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Multi-Model Comparison Tools to compare accuracy, speed, and performance of multiple models. |
Multi-model comparison dashboards and reporting available for evaluation. | |
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Model Explainability Tools Built-in features for interpreting and explaining predictions (e.g., SHAP, LIME). |
Explainability dashboards (incl. SHAP/LIME, variable attribution) are a feature of the platform. | |
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AutoML Automated machine learning capabilities for speeding up model creation and evaluation. |
AutoML is a promoted feature for rapid model prototyping. | |
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Reusable Feature Store Centralized repository to store and reuse engineered features across analytics projects. |
A reusable feature store is described as part of the platform’s advanced MLOps stack. | |
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Model Export Formats Supported formats for exporting trained models (e.g., PMML, ONNX). |
Exporting models to industry formats (PMML/ONNX) is supported per technical documentation. |
Prediction & Scoring
(9 Yes /9 Known /12 Possible features)
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Batch Prediction Ability to execute predictions on large datasets at once. |
Batch prediction, including for large datasets, featured within Quantiphi’s data science services. | |
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Real-time API Scoring APIs for instant scoring of customer, claim, or policy records in live systems. |
API-based real-time scoring is available and highlighted in insurance solutions. | |
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Concurrent Scoring Capacity Maximum simultaneous scoring requests supported. |
No information available | |
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Prediction Latency Average delay between input and receiving prediction. |
No information available | |
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Confidence Interval Output Predictions include confidence intervals or probability scores. |
Probabilistic scoring and confidence intervals are mentioned as output options in bespoke models. | |
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Score Logging & Auditing Comprehensive logging of each prediction for audit and traceability. |
Comprehensive logging and traceability is included as standard, especially for regulated environments. | |
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Bulk Import/Export Tools to handle input/output of large datasets in multiple formats (CSV, Parquet, etc.). |
Bulk import/export of data in various formats (CSV/Parquet/etc) is given as an enabling feature. | |
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Business Rule Interceptor Ability to trigger rules or workflows based on prediction outcomes. |
Can trigger workflows and rules based on model outcomes within business process automation. | |
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Prediction Refresh Rate Frequency with which prediction outputs can be updated. |
No information available | |
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Automated Alerts Automatic notifications or alerts based on scores exceeding certain thresholds. |
Automated alerts/notifications for rule exceedances or scores built into the workflow engine. | |
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Anomaly Detection Integrated detection of unusual patterns in input or output data. |
Anomaly and fraud detection modules are core insurance product features. | |
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Result Visualization Graphical displays of predictions at the record or portfolio level. |
Rich visualization, including record-level and portfolio-level dashboards, are promoted as part of the experience. |
Performance & Scalability
(7 Yes /7 Known /11 Possible features)
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Horizontal Scalability Ability to add computing nodes to handle increased prediction volume. |
Architecture supports horizontal scaling via cloud-native deployments (Google/AWS/Azure). | |
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Load Balancing System can distribute tasks evenly across computational resources. |
Built-in load balancing for distributed cloud workloads is included. | |
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Concurrent User Support Maximum number of users who can operate the system simultaneously. |
No information available | |
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Model Training Speed Average time required to train a new model on insurance datasets. |
No information available | |
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Uptime SLA Guaranteed minimum system uptime/service availability. |
No information available | |
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Automated Resource Scaling System automatically scales cloud or on-premise resources based on demand. |
Cloud deployments auto-scale resources to demand. | |
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Parallel Processing Ability to execute multiple jobs or model trainings in parallel. |
Platform supports parallel/distributed processing for both model training and scoring. | |
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Throughput Capacity of the platform for end-to-end data process and prediction. |
No information available | |
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High Availability Built-in failover and redundancy for critical components. |
Critical production workloads are supported with HA/failover; several references to enterprise readiness. | |
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Disaster Recovery Automated backup and restore procedures for platform state and data. |
Platform includes backup/restore and disaster recovery as part of managed services. | |
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Elastic Storage Support for dynamic storage scaling as data grows. |
Elastic storage scaling available in cloud-native deployments (e.g., via Google Cloud Storage, AWS S3). |
Security & Compliance
(10 Yes /10 Known /11 Possible features)
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User Access Control Role-based permissions for accessing platform features and data. |
Comprehensive RBAC is available as standard for enterprise insurance clients. | |
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Audit Logs Comprehensive logging of all user and system actions for compliance. |
Audit logging for both data and user actions mentioned for compliance with insurance regulation. | |
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Encryption at Rest Data is encrypted on disk and in database/storage. |
Data is encrypted at rest, in transit, and supports insurer information security requirements. | |
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Encryption in Transit Data encrypted when being transferred between systems (e.g., SSL/TLS). |
Platform uses SSL/TLS and secure protocols for in-transit encryption. | |
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GDPR/CCPA Compliance Supports processes to meet personal data regulations (European, US, etc). |
Quantiphi addresses GDPR/CCPA and emphasizes data subject rights management for global insurance clients. | |
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Regulatory Reporting Tools Automated tools or templates for industry regulatory reporting. |
Regulatory reporting tools, including templates/dashboards, are part of the insurance package. | |
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Data Retention Policy Management Automatic enforcement of data archiving and deletion in line with regulations. |
Data retention policy automation is offered for compliance and regulatory needs. | |
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Multi-factor Authentication Support for two-factor or multi-factor authentication for user access. |
Multi-factor authentication is supported for platform access per Quantiphi’s security documents. | |
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Single Sign-On (SSO) Integration with enterprise identity providers via SSO. |
Single Sign-On (SSO) is available by integrating with enterprise identity providers. | |
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Penetration Testing Regular third-party security assessments of the platform. |
No information available | |
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Role-based Data Access Granular control over which users can view or edit specific data sets. |
Granular role-based data access is supported (see RBAC and data privacy sections). |
User Experience & Collaboration
(6 Yes /6 Known /11 Possible features)
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Custom Dashboards Users can configure and personalize analytical dashboards. |
Custom dashboards and analytics can be built and configured by users. | |
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Report Scheduling Automatic generation and distribution of reports on a set schedule. |
Automatic report scheduling and distribution feature is mentioned. | |
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Annotation & Commenting Inline commenting and annotation tools for team collaboration. |
No information available | |
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Mobile Access Full functionality or at least key insights available on mobile devices. |
Mobile access to dashboards/alerts is supported for key executives and managers. | |
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Multilingual Interface Support for multiple languages in the user interface. |
No information available | |
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Guided Onboarding Step-by-step training or walkthroughs for new users. |
No information available | |
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Role-based Interface Customization UI adapts to user’s functions (e.g., actuary, underwriter, claims manager). |
No information available | |
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Document Sharing Direct sharing or export of dashboard, reports, and models. |
Document sharing/export supported for dashboards, reports, and model results. | |
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Collaboration Workspace Centralized project or workspace for teams to manage analytics projects. |
Dedicated project collaboration workspaces for insurance analytics teams are featured. | |
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User Feedback Loop Mechanisms for users to suggest improvements, report bugs, or request features. |
User feedback/suggestion mechanisms are included as part of the support portal. | |
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Accessibility Compliance Meets standards such as WCAG for users with disabilities. |
No information available |
Visualization & Reporting
(10 Yes /10 Known /11 Possible features)
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Custom Visualization Library Wide variety of graph, chart, and diagram types beyond basic bar and line types. |
Quantiphi offers an extensive visualization library, including advanced charts/graphs. | |
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Drill-down Capabilities View detailed information and trace factors behind each prediction or trend. |
Drill-down analytics available for portfolios, claims, and customer analyses. | |
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Geospatial Mapping Visualization of data on geographic maps to track claim concentrations, risk zones, etc. |
Geospatial mapping is included for catastrophe, claims, and risk zoning visualizations. | |
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Temporal Analysis Tools Visualization of trends and predictions over time. |
Time-series/temporal analytics, including trend predictions, are core to Quantiphi's insurance solution. | |
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Export to PDF/Excel/PowerPoint Direct download or export of reports in common formats. |
Exporting reports to PDF, Excel, and PowerPoint formats is supported. | |
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Interactive Dashboards Live updating and interactive filtering of visualizations. |
Dashboards are live/interactive with filtering and real-time updates. | |
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Custom Report Templates Library or builder for creating company-branded report templates. |
No information available | |
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KPI Tracking Monitor key insurance performance indicators alongside predictive model outputs. |
KPI monitoring for insurance metrics is highlighted in solution overviews and demos. | |
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Scheduled Email Distribution Automated periodic sending of insights and reports to stakeholders. |
Scheduled report/insight emailing to stakeholders is available. | |
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What-if Scenario Analysis Test the outcome of hypothetical situations through simulation. |
What-if scenario / impact analysis is offered in claims, rate, and risk modules. | |
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Embedded Analytics Ability to embed visualizations in external portals or applications. |
Platform visualizations can be embedded into external portals/sites. |
Deployment & Integration Options
(8 Yes /8 Known /11 Possible features)
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Cloud Deployment SaaS or managed cloud hosting for rapid rollout and scalability. |
Cloud deployment via all public clouds and SaaS models are supported. | |
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On-premise Deployment Support for installation within insurer’s own infrastructure. |
On-premise deployment is supported per enterprise/regulated client requirements. | |
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Hybrid Deployment Ability to split workloads and data between cloud and on-premise environments. |
Hybrid (cloud/on-prem) deployment is available for sensitive workloads. | |
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Open RESTful APIs Public APIs to facilitate integration with legacy and new insurance systems. |
RESTful Open API for external integrations is promoted (for legacy and core insurance systems). | |
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Webhooks Support Real-time notification and workflow triggers for external systems. |
No information available | |
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SDKs for Developers Software development kits in common languages for custom integration. |
SDKs for major programming languages are provided for developers. | |
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Data Export Formats Number of file formats supported for export. |
No information available | |
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Third-Party Service Integration Certified connectors for CRMs, ERPs, DWHs, or vertical insurance platforms. |
Certified connectors for ERPs, CRMs, DWH, and insurance platforms are available. | |
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Containerization Support Ability to deploy solutions using Docker, Kubernetes, or similar technologies. |
Container deployments (Docker, Kubernetes) are a deployment option for Quantiphi. | |
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Zero Downtime Deployments Update the platform without user disruption. |
No information available | |
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Custom Integration Services Professional services or tools for bespoke system integrations. |
Custom system integration and professional services are part of Quantiphi's consulting model. |
Monitoring & Model Management
(9 Yes /9 Known /11 Possible features)
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Model Performance Dashboards Real-time status and KPI views for all deployed models. |
Real-time performance dashboards for deployed models are available to business/IT users. | |
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Drift Detection Automated detection when model input or output distributions change significantly. |
Model drift detection is present as a built-in MLOps capability. | |
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Scheduled Model Retraining Automatic retraining of models on updated data. |
Scheduled retraining based on data updates is part of the automated ML pipeline. | |
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Model Health Alerts Notifications when models underperform or exhibit anomalies. |
Alerting for model health and performance included in platform management. | |
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A/B Testing Framework Can run multiple models in parallel to determine best outcomes. |
A/B testing framework to compare model versions is a feature for insurance modeling. | |
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Shadow Deployment Deploy test models alongside production for comparison without affecting outcomes. |
Shadow deployment allows parallel (‘silent’) production testing, mentioned for regulated settings. | |
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Manual Model Override Ability for responsible users to override automated predictions if required. |
Manual overrides of automated predictions supported for human-in-the-loop underwriter workflows. | |
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Model Comparison Reports Automatically generated reports comparing model results and accuracy. |
Model comparison/benchmarking reports are generated from the platform. | |
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Automated Model Archival Old or superseded models can be archived and restored if needed. |
Automated model archival/restore is available for version control and governance. | |
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Custom Logging Levels Configurable granularity of operational and error logs for models. |
No information available | |
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Explainability Monitoring Ongoing measurement of explainability scores for deployed models. |
No information available |
Insurance-Specific Functionality
(11 Yes /11 Known /11 Possible features)
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Claims Frequency Modeling Templates or wizards for predicting claim counts per time period or policy cohort. |
Templates/wizards for insurance claims frequency modeling are a core part of Quantiphi’s packaged insurance solutions. | |
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Loss Severity Modeling Support for modeling and predicting potential cost per claim. |
Loss severity prediction is a noted success use case for Quantiphi’s AI for insurance. | |
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Customer Lifetime Value Prediction Tools to estimate future profitability of policyholders. |
Customer Lifetime Value modeling featured in customer analytics for insurers. | |
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Fraud Detection Modules Pre-built modules or scripts for identifying potentially fraudulent claims. |
Fraud detection modules (pre-built and custom) are a highlight in Quantiphi's insurance offerings. | |
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Churn/Renewal Prediction Predicting which policyholders are likely to lapse or renew contracts. |
Churn and renewal prediction is an advertised predictive solution in their insurance platform. | |
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Risk Pool Segmentation Algorithmic grouping of policies/customers with similar risk characteristics. |
Risk pool segmentation algorithms included for pricing/underwriting improvements. | |
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Catastrophe Modeling Scenario modeling for weather, disaster, or other catastrophic event impacts. |
Catastrophe modeling, geospatial risk, and disaster event simulation tools offered in the solution set. | |
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Quotation Optimization Predictive pricing to optimize quote conversion while managing risk. |
Quotation/pricing optimization for underwriting is mentioned as a key application. | |
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Regulatory Compliance KPIs Dashboards or reports targeting regional insurance regulatory requirements. |
Regulatory KPIs and reporting dashboards for Solvency, IFRS, and local regulations form part of insurance analytics. | |
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Reinsurance Analytics Integration Built-in support for actuarial or portfolio-level analytics for reinsurers. |
Reinsurance analytics modules and reporting are available in the Quantiphi AI for Insurance suite. | |
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Underwriting Decision Support Predictive analytics specifically designed for supporting underwriters. |
Underwriting decision support via predictive analytics is a headline benefit of Quantiphi for Insurance. |
Support, Documentation, and Training
(10 Yes /10 Known /10 Possible features)
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Comprehensive User Documentation Access to manuals, guides, and API docs. |
Extensive documentation, API guides, and user training materials are provided to clients. | |
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In-Platform Help Contextual help, tutorials, and support widgets within the UI. |
In-platform help and support widgets are available within the user interface. | |
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Online Knowledge Base Searchable library of FAQs, troubleshooting tips, and community discussions. |
Online knowledge base with community Q&A and troubleshooting is available to client organizations. | |
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24/7 Support Availability Around-the-clock access to technical and business support. |
24/7 support for enterprise clients is noted in service level agreements. | |
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Dedicated Account Manager Named advisor for onboarding and ongoing account support. |
Dedicated account managers are available for enterprise onboarding/support. | |
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Custom Training Programs Role-based or use-case-based remote or on-site training. |
Custom training (remote/on-site, role-specific) is delivered as part of onboarding. | |
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Professional Services Consulting, configuration, and hands-on setup services. |
Consulting and configuration professional services provided for all deployments. | |
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User Community Portal Online forums for networking, sharing experiences, and best practices. |
User community portal with best practices and knowledge sharing available. | |
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Release Notes & Change Logs Detailed updates on platform enhancements and bug fixes. |
Detailed release notes and change logs are issued with each platform update. | |
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Sandbox Environment Safe, isolated environment for new user experimentation. |
Sandbox environments are provided for experimentation and training prior to production deployment. |
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