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CLARA Analytics from Munich Re
An AI-based risk assessment platform that uses advanced analytics and machine learning to help insurers evaluate and price risks more accurately. It provides predictive modeling, claims analysis, and fraud detection capabilities to improve underwriting decisions and operational efficiency.
Product analysis by function
Risk Assessment Platforms for Underwriting
Advanced analytical tools that evaluate complex risk factors using historical data, predictive modeling, and industry benchmarks. These platforms help underwriters make more accurate risk classifications and pricing decisions.
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Data Integration
(6 Yes /6 Known /10 Possible features)
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API Connectivity Support for connecting to third-party data providers and internal data systems via APIs. |
CLARA Analytics is described as employing advanced analytics and machine learning, which typically require robust API connectivity to various data sources. | |
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Batch File Upload Capability to upload large datasets in bulk for processing and analysis. |
Given that the platform supports claims analysis and risk analytics on large datasets, batch file upload is a basic expectation for such platforms. | |
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Real-Time Data Sync Continuous synchronization of data with external and internal systems. |
Real-time data sync is commonly required for predictive modeling, claims monitoring, and operational efficiency. | |
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Data Source Flexibility Number of supported data sources (e.g., credit bureaus, telematics, social data). |
No information available | |
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Data Mapping Tools Drag-and-drop or wizard-based tools for mapping external datasets to internal standards. |
No information available | |
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Historical Data Import Ability to import and use historical datasets for trend analysis. |
Analyzing historical claims to identify trends is a key part of CLARA's analytics approach. | |
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Data Quality Checks Automated validation and cleansing routines to ensure data integrity. |
Automated validation and cleansing are necessary for machine learning models to ensure data integrity. | |
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Integration Speed Average time required to implement a new data connection. |
No information available | |
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Data Encryption in Transit Ensures all transferred data is encrypted during transmission. |
Mention of advanced analytics and integration implies industry-standard data encryption in transit for compliance and security. | |
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Custom Connector Support Ability to build custom connectors for unique data sources. |
No information available |
Risk Modeling & Analytics
(7 Yes /7 Known /10 Possible features)
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Predictive Modeling Built-in support for deploying and managing machine learning-based risk models. |
The product explicitly provides predictive modeling capabilities using machine learning. | |
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Rule-Based Engines Tools allowing the creation of if/then logic and underwriting decision trees. |
Rule-based engines usually complement predictive analytics for underwriting automation. | |
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Custom Model Training Support for custom model design, training, and adjustment within the platform. |
Platforms with built-in analytics and machine learning often support custom model training. | |
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Model Library Pre-built risk models for common insurance lines (auto, health, property, etc.). |
No information available | |
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Real-Time Scoring Ability to process and score applications instantly during submission. |
Real-time scoring is essential for claims automation and advanced underwriting. | |
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Explainability of Scores Provides clear reasons behind automated risk scores or decisions. |
‘Explainability of scores’ is increasingly standard in AI-driven risk analytics for regulatory and adoption reasons. | |
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Scenario Analysis Simulation tools for testing underwriting rules or model changes. |
Advanced risk and scenario analysis tools are a core value proposition for CLARA Analytics to simulate rule/model changes. | |
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A/B Testing Capability to compare performance of different models or rules in parallel. |
No information available | |
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Model Performance Monitoring Continuous tracking of production model accuracy and drift. |
Continuous monitoring of production model accuracy is a standard practice in AI risk analytics to ensure ongoing relevance. | |
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Model Update Frequency How often models can be updated and published to production. |
No information available |
User Experience & Usability
(4 Yes /4 Known /10 Possible features)
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Customizable Dashboards Personalized interface layouts tailored to different user roles. |
No information available | |
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Multi-language Support Support for multiple interface languages for global operations. |
No information available | |
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Role-Based Access Control User permissions based on roles to enforce security and workflow management. |
Role-based access is required in all enterprise insurance analytics platforms for privacy and workflow management. | |
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Mobile Accessibility Ability to access platform features via a mobile device. |
No information available | |
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Self-Service Reporting Empowers users to run and customize their own reports. |
Ad hoc and customizable reporting is standard in analytics tools and is likely present to empower users. | |
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Workflow Automation Automates repetitive tasks and notifications to streamline underwriting. |
Workflow automation is key to increasing operational efficiency and is generally present in modern risk/claims platforms. | |
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Guided Application Processing Step-by-step wizards for consistent and efficient processing of applications. |
No information available | |
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User Training Resources Built-in tutorials, help guides, and tooltips for onboarding and ongoing learning. |
No information available | |
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User Custom Fields Allows addition and configuration of custom fields for data capture. |
Custom field configuration is typically necessary to support varying client data requirements. | |
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Interface Response Speed Average interface action completion time. |
No information available |
Regulatory Compliance
(4 Yes /4 Known /10 Possible features)
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Audit Trail Automated logging of all changes to data, models, and rules. |
Audit trails are standard in platforms dealing with risk and compliance, particularly in insurance. | |
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Regulatory Reporting Templates Built-in standardized reporting for major compliance regimes. |
No information available | |
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Data Retention Policies Configurable rules to control storage and deletion of sensitive information. |
Data retention policies are required for compliance in insurance data processing. | |
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Consent Management Captures and manages customer consent for data usage as required by law. |
No information available | |
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Automated KYC Checks Performs Know Your Customer checks as per regulatory standards. |
No information available | |
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Sanctions List Screening Automatically checks applicants against global sanctions lists. |
No information available | |
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Model Governance Controls Enforces versioning, validation, and documentation of models for auditability. |
Model governance is a requirement for AI-based decisioning, given compliance and accountability needs. | |
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Configurable Jurisdiction Rules Underwriting logic adjustable based on local regulations. |
No information available | |
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Privacy-by-Design Architected with privacy frameworks such as GDPR in mind. |
CLARA Analytics is used in insurance; privacy-by-design is likely built-in given GDPR and similar frameworks. | |
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Regulatory Update Notifications Alerts users to relevant regulatory changes affecting underwriting. |
No information available |
Security & Privacy
(2 Yes /2 Known /10 Possible features)
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Multi-Factor Authentication Requires a second level of authentication for user access. |
No information available | |
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Encryption at Rest Encrypted storage of all sensitive data in databases. |
Encryption at rest is an industry standard for sensitive insurance data. | |
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Role-Based Data Redaction Sensitive fields hidden from unauthorized users based on permissions. |
Role-based redaction is standard for platforms handling sensitive claims and personal data. | |
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Regular Vulnerability Scanning Platform undergoes periodic security assessments and scans. |
No information available | |
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Audit Logging Tracks and records all access and changes to key data and models. |
No information available | |
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Data Masking Obscures sensitive information in test environments. |
No information available | |
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Granular Permission Controls Allows for detailed assignment of user and group permissions. |
No information available | |
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Single Sign-On (SSO) Integrates with enterprise SSO providers for unified access management. |
No information available | |
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Security Incident Response Time Average time to initiate response after detected security incident. |
No information available | |
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Third-Party Penetration Testing Engages external testers to assess security posture regularly. |
No information available |
Reporting & Business Intelligence
(1 Yes /1 Known /10 Possible features)
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Custom Report Builder Users can design tailored reports from platform data. |
No information available | |
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Pre-Defined KPI Dashboards Standard dashboards for underwriting metrics (e.g., loss ratio, approval rate). |
No information available | |
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Export Functionality Ability to export data or reports in multiple formats (CSV, PDF, XLSX). |
No information available | |
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Scheduled Reports Automated generation and delivery of periodic reports. |
No information available | |
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Real-Time Analytics Live updates to dashboards as new data arrives. |
Real-time analytics is key for operational efficiency in CLARA Analytics' claims and risk assessment offering. | |
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Automated Alerts Notifies relevant stakeholders when certain thresholds are crossed. |
No information available | |
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Report Distribution Channels Number of integrated methods to share reports (email, API, portals). |
No information available | |
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Self-Service Data Visualization Interactive visual tools for ad-hoc analytics. |
No information available | |
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Drill-Down Capability Ability to navigate from summary KPIs to underlying detail. |
No information available | |
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Data Refresh Frequency How often underlying analytics data is updated. |
No information available |
Automation & Decisioning
(3 Yes /3 Known /10 Possible features)
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Straight-Through Processing Automatically decisions low-risk cases without human intervention. |
Automation of low-risk claims is a stated benefit of the platform; this is straight-through processing. | |
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Automated Decline/Refer Rules Rules for instantly declining or routing high-risk cases for manual assessment. |
Fraud and automated decisioning/triage are frequently part of CLARA's claims decision rule automation. | |
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Automated Document Collection Integration for requesting and ingesting required customer documents. |
No information available | |
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Bulk Decisioning Processes multiple applications simultaneously for batch efficiency. |
No information available | |
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Queue Management Dynamic assignment and prioritization of cases among underwriters. |
No information available | |
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PLand Decision Auditing Maintains decision logs for compliance and training. |
No information available | |
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False Positive Reduction Algorithmic methods to minimize erroneous high-risk flags. |
Machine learning based systems like CLARA invest in false positive reduction for effective claims/fraud detection. | |
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Decision Throughput Rate Number of applications processed per hour. |
No information available | |
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Decision Time Average time for a decision to be made per application. |
No information available | |
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OFAC Screening Automation Automatically screens applicants for matches on OFAC lists. |
No information available |
Third-Party Integration Ecosystem
(2 Yes /2 Known /10 Possible features)
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Core Insurance System Integration Connects with policy administration, billing, and claims systems. |
Integration with core policy, billing, and claims systems is necessary for a risk analytics platform to function in the insurance context. | |
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Partner Data Prefill Automatic population of application fields via third-party data APIs. |
No information available | |
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Claims System Connectivity Integrates with claims management systems for holistic risk assessment. |
Claims system integration is essential to CLARA's claims improvement offerings. | |
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BI Platform Export Exports analytics data to third-party BI tools. |
No information available | |
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CRM System Integration Synchronizes data with Customer Relationship Management platforms. |
No information available | |
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Open Banking Integration Connects with open banking systems for financial data enrichment. |
No information available | |
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Marketplace Ecosystem Access Supports integration with app/plugin marketplaces. |
No information available | |
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Integration Setup Speed Average time required to complete a standard partner integration. |
No information available | |
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Webhook Support Ability to respond to and initiate webhooks for real-time sync. |
No information available | |
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Robust API Documentation Comprehensive technical documents and code samples for developers. |
No information available |
Configurability & Scalability
(3 Yes /3 Known /10 Possible features)
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Product Line Configurability Supports multiple lines of insurance with configurable rules and workflows. |
CLARA Analytics is positioned for multiple use cases; configurability for various product lines is likely. | |
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Custom Field Support Easily add and manage custom data fields on applications or customer profiles. |
Custom field management is typically supported for insurance customer profiling. | |
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Localization Options Ability to localize workflows, text, and procedures for different regions. |
No information available | |
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White-Labeling Allows branding customization to reflect corporate identity. |
No information available | |
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Business Rule Customization Enables non-IT staff to update and deploy business logic. |
Business rule customization is a common requirement for non-IT staff in insurance operations. | |
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Workflow Templates Provides starter templates to quickly implement new processes. |
No information available | |
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Concurrent User Capacity Maximum number of active users supported at once. |
No information available | |
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Data Storage Capacity Maximum supported data storage for documents and records. |
No information available | |
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Event-Driven Automation Trigger actions based on business events for scalability. |
No information available | |
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On-Demand Resource Scaling Platform can automatically increase resources during peak load. |
No information available |
Support, Maintenance & SLAs
(4 Yes /4 Known /10 Possible features)
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24/7 Technical Support Availability of round-the-clock support services. |
No information available | |
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Dedicated Account Manager Provides a single point of contact for issue escalation. |
No information available | |
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Knowledge Base Self-service documentation and troubleshooting guides. |
Online documentation and support articles are standard for analytics platforms targeted at enterprise clients. | |
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Automated Patch Management Automatic deployment of updates and patches. |
Automated updates/patches are common in AI SaaS offerings to maintain regulatory and functional compliance. | |
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Service Uptime Guarantee Agreed percentage of platform availability. |
No information available | |
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Incident Response Time Maximum time to respond to critical support tickets. |
No information available | |
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Release Notes Accessibility Transparent communication about new features and bug fixes. |
Providing release notes and product change notification is standard among digital insurance solutions. | |
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Onboarding Support Structured onboarding process for new clients. |
Large vendors like Munich Re offer onboarding support for their complex risk platforms. | |
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Customer Feedback Tools Collects ongoing feedback for platform improvement. |
No information available | |
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Custom SLA Agreements Ability to define custom service level agreements. |
No information available |
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