Integrates advanced analytics, AI, and machine learning to help insurers in claims and underwriting analytics, pricing optimization, fraud detection, and customer lifecycle management.
More about BRIDGEi2i Analytics Solutions
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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Multi-source Data Connectivity Ability to integrate and ingest data from various sources such as databases, cloud platforms, spreadsheets, and APIs. |
Vendor documentation asserts the product integrates with customer, claims, policy, and external data via connectors and APIs for a holistic analytics view. | |
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Real-time Data Sync Real-time synchronization of incoming data streams for up-to-date predictions. |
No information available | |
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Data Cleansing Tools Automated tools to clean, deduplicate, and normalize raw insurance data. |
Claims data normalization and fraud detection imply automated cleansing and deduplication of input datasets. | |
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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 described in data onboarding process in the solution overview. | |
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Data Enrichment APIs Integration with third-party services to enrich internal data (e.g., credit scores, vehicle history). |
References integration of external AI-driven insights, including enrichment with credit scores and telematics. | |
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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. |
No information available | |
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Event-driven Updates Support for updating models or insights when new events/data arrive. |
Event-triggered insights and recommendation engines indicated, supporting automated updates to risk and pricing models as new data arrives. | |
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Data Lineage Tracking Traceability of data sources and transformations for audit and compliance. |
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Data Privacy Controls Built-in tools for masking or redacting sensitive PII (personally identifiable information). |
BRIDGEi2i provides 'intelligent data privacy and governance', implying PII masking/redaction capabilities. | |
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Integration with Core Insurance Systems Connections with policy administration, claims, underwriting, and customer management systems. |
Mention of seamless integration with core insurance systems for claims, underwriting, and policy analytics. | |
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Partner Data Sharing Secure tools and permissions for controlled sharing of datasets with partners. |
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Graphical Model Builder Drag-and-drop or visual tools for constructing predictive models without code. |
Drag-and-drop model construction tools described as part of the suite's business user functionality. | |
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Custom Algorithm Support Ability to author, import, and use custom algorithms in analytics pipelines. |
Custom algorithms can be imported/created as demonstrated in client use cases and platform technical FAQ. | |
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Automated Feature Engineering Automatic creation and selection of predictive features from raw insurance data. |
Feature engineering automation is part of the AI/machine learning automation messaging. | |
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Hyperparameter Tuning Tool-assisted searching for optimal model parameters. |
AI/ML workflow includes hyperparameter tuning automation as per solution architecture examples. | |
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Model Versioning Automatic tracking and management of model versions and their metadata. |
Full model lifecycle management highlighted, including versioning. | |
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Pre-built Insurance Models Library of industry-specific models, e.g., for claim frequency, fraud detection, churn prediction. |
Industry-specific models (claims, fraud, churn, pricing) described as pre-built and customizable. | |
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No-Code/Low-Code Interface Options for business users to create models without programming knowledge. |
Emphasis on business user enablement: low-code/no-code tools available for model building. | |
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Code-based Model Support Support for Python, R, or other programming languages for building custom models. |
Data scientist tools include support for Python/R custom scripting. | |
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Multi-Model Comparison Tools to compare accuracy, speed, and performance of multiple models. |
Platform supports comparing model results and champions against challengers. | |
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Model Explainability Tools Built-in features for interpreting and explaining predictions (e.g., SHAP, LIME). |
Solution overview references model explainability, including SHAP/LIME or similar tools. | |
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AutoML Automated machine learning capabilities for speeding up model creation and evaluation. |
Automated machine learning capabilities highlighted for rapid prototyping. | |
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Reusable Feature Store Centralized repository to store and reuse engineered features across analytics projects. |
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Model Export Formats Supported formats for exporting trained models (e.g., PMML, ONNX). |
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Batch Prediction Ability to execute predictions on large datasets at once. |
Batch scoring supported for large insurance datasets. | |
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Real-time API Scoring APIs for instant scoring of customer, claim, or policy records in live systems. |
References to API-driven, real-time scoring workflows. | |
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Concurrent Scoring Capacity Maximum simultaneous scoring requests supported. |
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Prediction Latency Average delay between input and receiving prediction. |
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Confidence Interval Output Predictions include confidence intervals or probability scores. |
Probability/confidence interval output is part of the model output schema for decision support. | |
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Score Logging & Auditing Comprehensive logging of each prediction for audit and traceability. |
Score/audit logging for regulatory traceability and analytics. | |
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Bulk Import/Export Tools to handle input/output of large datasets in multiple formats (CSV, Parquet, etc.). |
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Business Rule Interceptor Ability to trigger rules or workflows based on prediction outcomes. |
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Prediction Refresh Rate Frequency with which prediction outputs can be updated. |
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Automated Alerts Automatic notifications or alerts based on scores exceeding certain thresholds. |
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Anomaly Detection Integrated detection of unusual patterns in input or output data. |
Anomaly/fraud detection modules for claims indicate anomaly detection capabilities. | |
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Result Visualization Graphical displays of predictions at the record or portfolio level. |
Dashboards demonstrate graphical portfolio, claim-level, and customer-level result visualizations. |
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Horizontal Scalability Ability to add computing nodes to handle increased prediction volume. |
Cloud-scale and clustering referenced for high-volume insurance workloads. | |
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Load Balancing System can distribute tasks evenly across computational resources. |
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Concurrent User Support Maximum number of users who can operate the system simultaneously. |
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Model Training Speed Average time required to train a new model on insurance datasets. |
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Uptime SLA Guaranteed minimum system uptime/service availability. |
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Automated Resource Scaling System automatically scales cloud or on-premise resources based on demand. |
Elastic/automated resource scaling features highlighted as part of managed analytics platform. | |
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Parallel Processing Ability to execute multiple jobs or model trainings in parallel. |
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Throughput Capacity of the platform for end-to-end data process and prediction. |
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High Availability Built-in failover and redundancy for critical components. |
Platform describes high availability architecture, including redundancy and failover. | |
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Disaster Recovery Automated backup and restore procedures for platform state and data. |
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Elastic Storage Support for dynamic storage scaling as data grows. |
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User Access Control Role-based permissions for accessing platform features and data. |
Role-based access control listed for regulatory, operational, and analytics modules. | |
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Audit Logs Comprehensive logging of all user and system actions for compliance. |
Comprehensive user and system activity logs referenced in compliance/traceability. | |
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Encryption at Rest Data is encrypted on disk and in database/storage. |
Encryption at rest specifically mentioned as part of the security posture and compliance certifications. | |
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Encryption in Transit Data encrypted when being transferred between systems (e.g., SSL/TLS). |
References to SSL/TLS-secured communication and API endpoints. | |
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GDPR/CCPA Compliance Supports processes to meet personal data regulations (European, US, etc). |
Solution explicitly states support for GDPR and similar regional data regulations. | |
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Regulatory Reporting Tools Automated tools or templates for industry regulatory reporting. |
Automated regulatory reporting templates, as part of compliance features, are advertised. | |
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Data Retention Policy Management Automatic enforcement of data archiving and deletion in line with regulations. |
Data retention management is highlighted for compliance support. | |
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Multi-factor Authentication Support for two-factor or multi-factor authentication for user access. |
User authentication includes multi-factor options per documentation. | |
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Single Sign-On (SSO) Integration with enterprise identity providers via SSO. |
No information available | |
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Penetration Testing Regular third-party security assessments of the platform. |
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Role-based Data Access Granular control over which users can view or edit specific data sets. |
Role-based, granular data access mechanisms highlighted for compliance clients. |
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Custom Dashboards Users can configure and personalize analytical dashboards. |
Dashboards are customizable for user/role/functional area. | |
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Report Scheduling Automatic generation and distribution of reports on a set schedule. |
No information available | |
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Annotation & Commenting Inline commenting and annotation tools for team collaboration. |
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Mobile Access Full functionality or at least key insights available on mobile devices. |
No information available | |
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Multilingual Interface Support for multiple languages in the user interface. |
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Guided Onboarding Step-by-step training or walkthroughs for new users. |
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Role-based Interface Customization UI adapts to user’s functions (e.g., actuary, underwriter, claims manager). |
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Document Sharing Direct sharing or export of dashboard, reports, and models. |
Document and dashboard sharing called out as a capability for collaboration. | |
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Collaboration Workspace Centralized project or workspace for teams to manage analytics projects. |
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User Feedback Loop Mechanisms for users to suggest improvements, report bugs, or request features. |
User feedback features present as support/help and improvement mechanisms. | |
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Accessibility Compliance Meets standards such as WCAG for users with disabilities. |
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Custom Visualization Library Wide variety of graph, chart, and diagram types beyond basic bar and line types. |
Rich data visualization options, including custom charting, stated in marketing and case studies. | |
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Drill-down Capabilities View detailed information and trace factors behind each prediction or trend. |
. | No information available |
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Geospatial Mapping Visualization of data on geographic maps to track claim concentrations, risk zones, etc. |
Geospatial/risk mapping listed among visualization types for claims and catastrophes. | |
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Temporal Analysis Tools Visualization of trends and predictions over time. |
Time-series/temporal trend analysis for portfolio and claims analytics described. | |
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Export to PDF/Excel/PowerPoint Direct download or export of reports in common formats. |
Export to PDF, Excel, PowerPoint is included in reporting suite. | |
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Interactive Dashboards Live updating and interactive filtering of visualizations. |
Interactive, filterable dashboards supported for end users. | |
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Custom Report Templates Library or builder for creating company-branded report templates. |
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KPI Tracking Monitor key insurance performance indicators alongside predictive model outputs. |
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Scheduled Email Distribution Automated periodic sending of insights and reports to stakeholders. |
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What-if Scenario Analysis Test the outcome of hypothetical situations through simulation. |
Simulation and scenario analysis for pricing and risk assessments available to users. | |
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Embedded Analytics Ability to embed visualizations in external portals or applications. |
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Cloud Deployment SaaS or managed cloud hosting for rapid rollout and scalability. |
Cloud deployment (SaaS) is a standard offering. | |
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On-premise Deployment Support for installation within insurer’s own infrastructure. |
On-premise deployments available for clients with strict data residency/security needs. | |
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Hybrid Deployment Ability to split workloads and data between cloud and on-premise environments. |
No information available | |
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Open RESTful APIs Public APIs to facilitate integration with legacy and new insurance systems. |
RESTful open APIs discussed as integration path with enterprise 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. |
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Data Export Formats Number of file formats supported for export. |
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Third-Party Service Integration Certified connectors for CRMs, ERPs, DWHs, or vertical insurance platforms. |
Certified connectors for vertical insurance core platforms described. | |
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Containerization Support Ability to deploy solutions using Docker, Kubernetes, or similar technologies. |
Container-based deployment (Docker etc) described for enterprise clients. | |
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Zero Downtime Deployments Update the platform without user disruption. |
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Custom Integration Services Professional services or tools for bespoke system integrations. |
Professional services available for bespoke and custom integration needs. |
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Model Performance Dashboards Real-time status and KPI views for all deployed models. |
Dedicated dashboards and KPI tracking for model performance monitoring. | |
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Drift Detection Automated detection when model input or output distributions change significantly. |
Drift detection for data/model monitoring included per AI operations/monitoring documentation. | |
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Scheduled Model Retraining Automatic retraining of models on updated data. |
Scheduled/automated model retraining built into platform operational cycles. | |
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Model Health Alerts Notifications when models underperform or exhibit anomalies. |
Model health, performance, outlier alerts are part of AI monitoring suite. | |
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A/B Testing Framework Can run multiple models in parallel to determine best outcomes. |
Champion/challenger (A/B) testing framework offered for production model selection. | |
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Shadow Deployment Deploy test models alongside production for comparison without affecting outcomes. |
No information available | |
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Manual Model Override Ability for responsible users to override automated predictions if required. |
No information available | |
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Model Comparison Reports Automatically generated reports comparing model results and accuracy. |
Model comparison reports automatically generated as part of model management. | |
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Automated Model Archival Old or superseded models can be archived and restored if needed. |
Lifecycle and archival of superseded models described in documentation. | |
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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 |
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Claims Frequency Modeling Templates or wizards for predicting claim counts per time period or policy cohort. |
Specialized claim frequency/predictive risk templates featured in insurance analytics toolkit. | |
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Loss Severity Modeling Support for modeling and predicting potential cost per claim. |
Solution supports modeling loss severity and claims payout prediction. | |
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Customer Lifetime Value Prediction Tools to estimate future profitability of policyholders. |
Customer lifetime value (CLV) analytics part of the 'customer lifecycle management' module. | |
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Fraud Detection Modules Pre-built modules or scripts for identifying potentially fraudulent claims. |
Pre-built fraud detection models and anomaly scoring described in detail. | |
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Churn/Renewal Prediction Predicting which policyholders are likely to lapse or renew contracts. |
Churn/renewal modeling referenced in customer lifecycle/policy management modules. | |
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Risk Pool Segmentation Algorithmic grouping of policies/customers with similar risk characteristics. |
Risk segmentation/cluster analysis is an advertised key functionality. | |
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Catastrophe Modeling Scenario modeling for weather, disaster, or other catastrophic event impacts. |
Scenario modeling for catastrophe/disaster risk analytics described in insurance and reinsurance modules. | |
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Quotation Optimization Predictive pricing to optimize quote conversion while managing risk. |
Predictive pricing and quotation optimization referenced for quote conversion goal. | |
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Regulatory Compliance KPIs Dashboards or reports targeting regional insurance regulatory requirements. |
Regulatory dashboards and compliance metrics featured as role-specific analytics. | |
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Reinsurance Analytics Integration Built-in support for actuarial or portfolio-level analytics for reinsurers. |
Reinsurance analytics and portfolio management capabilities referenced for enterprise/large carrier clients. | |
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Underwriting Decision Support Predictive analytics specifically designed for supporting underwriters. |
Underwriting analytics/decision support is a principal use case on vendor site and collateral. |
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Comprehensive User Documentation Access to manuals, guides, and API docs. |
Access to full suite documentation, guides, and API specs described. | |
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In-Platform Help Contextual help, tutorials, and support widgets within the UI. |
Contextual support and tutorials indicated in UI walkthroughs and client onboarding. | |
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Online Knowledge Base Searchable library of FAQs, troubleshooting tips, and community discussions. |
Online knowledge base and FAQ resource described for product support. | |
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24/7 Support Availability Around-the-clock access to technical and business support. |
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Dedicated Account Manager Named advisor for onboarding and ongoing account support. |
Dedicated account manager cited for enterprise insurance clients. | |
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Custom Training Programs Role-based or use-case-based remote or on-site training. |
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Professional Services Consulting, configuration, and hands-on setup services. |
Professional services and consulting highlighted in services section. | |
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User Community Portal Online forums for networking, sharing experiences, and best practices. |
User community portals/forums mentioned for product users. | |
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Release Notes & Change Logs Detailed updates on platform enhancements and bug fixes. |
Detailed release notes and change logs available with each platform update. | |
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Sandbox Environment Safe, isolated environment for new user experimentation. |
Sandbox/test environments available for experimentation and proof-of-concept use. |
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