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Oracle Analytical Cloud from Oracle Financial Services
Provides robust analytics capabilities including data visualization, machine learning, and predictive analytics to improve decision-making, streamline processes, and enhance customer experiences.
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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. |
Oracle Analytics Cloud offers extensive data connectivity, including integration with databases, spreadsheets, REST APIs, and cloud platforms. | |
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Real-time Data Sync Real-time synchronization of incoming data streams for up-to-date predictions. |
Real-time data sync is described in Oracle documentation via streaming and real-time connector support. | |
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Data Cleansing Tools Automated tools to clean, deduplicate, and normalize raw insurance data. |
The platform provides data preparation and cleansing tools, including deduplication and normalization. | |
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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. |
Automated recommendations for data mapping and schema alignment are present in Oracle Analytics Cloud data ingestion workflows. | |
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Data Enrichment APIs Integration with third-party services to enrich internal data (e.g., credit scores, vehicle history). |
Supports enrichment via integration with external data providers and APIs. | |
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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. |
Oracle Analytics Cloud monitors for schema changes; alerting/notification is documented in OAC data integration features. | |
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Event-driven Updates Support for updating models or insights when new events/data arrive. |
Can trigger model updates or refreshes when new events occur via integration settings. | |
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Data Lineage Tracking Traceability of data sources and transformations for audit and compliance. |
Data lineage visualization and audit tools are available to trace data origin and transformations. | |
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Data Privacy Controls Built-in tools for masking or redacting sensitive PII (personally identifiable information). |
Built-in data privacy tools, including masking, are available for regulatory compliance. | |
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Integration with Core Insurance Systems Connections with policy administration, claims, underwriting, and customer management systems. |
Oracle has pre-built connectors for policy administration, claims, and core insurance systems. | |
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Partner Data Sharing Secure tools and permissions for controlled sharing of datasets with partners. |
Granular sharing and permission settings enable controlled partner data sharing. |
Model Building & Customization
(11 Yes /11 Known /13 Possible features)
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Graphical Model Builder Drag-and-drop or visual tools for constructing predictive models without code. |
Visual builder and drag-and-drop modeling are available for analytic and predictive workflows. | |
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Custom Algorithm Support Ability to author, import, and use custom algorithms in analytics pipelines. |
SDKs and open interfaces enable custom algorithm integration in analytics pipelines. | |
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Automated Feature Engineering Automatic creation and selection of predictive features from raw insurance data. |
Automated feature engineering functionality for machine learning is included in Oracle Data Flows. | |
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Hyperparameter Tuning Tool-assisted searching for optimal model parameters. |
OAC includes hyperparameter tuning for supported ML algorithms. | |
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Model Versioning Automatic tracking and management of model versions and their metadata. |
Model versioning and metadata tracking are standard for deployed models. | |
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Pre-built Insurance Models Library of industry-specific models, e.g., for claim frequency, fraud detection, churn prediction. |
No information available | |
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No-Code/Low-Code Interface Options for business users to create models without programming knowledge. |
OAC supports no-code and low-code interfaces for business users via visual modeling tools. | |
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Code-based Model Support Support for Python, R, or other programming languages for building custom models. |
Supports Python/R through Oracle Machine Learning integration or external execution. | |
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Multi-Model Comparison Tools to compare accuracy, speed, and performance of multiple models. |
Model comparison tools are available for evaluating multiple models' performance and accuracy. | |
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Model Explainability Tools Built-in features for interpreting and explaining predictions (e.g., SHAP, LIME). |
OAC provides explainability tools utilizing feature importance and prediction explanations. | |
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AutoML Automated machine learning capabilities for speeding up model creation and evaluation. |
The platform can automate ML workflow steps for rapid prototyping ('AutoML'). | |
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Reusable Feature Store Centralized repository to store and reuse engineered features across analytics projects. |
No information available | |
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Model Export Formats Supported formats for exporting trained models (e.g., PMML, ONNX). |
OAC can export models in multiple open formats (e.g., PMML, ONNX), as per Oracle ML 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 support is built into OAC for handling large data scoring tasks. | |
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Real-time API Scoring APIs for instant scoring of customer, claim, or policy records in live systems. |
APIs allow for real-time scoring/inference within Oracle Analytics Cloud. | |
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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. |
ML modules support outputting confidence intervals or probability scores. | |
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Score Logging & Auditing Comprehensive logging of each prediction for audit and traceability. |
Prediction and scoring logs/auditing features are provided for traceability in the analytics platform. | |
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Bulk Import/Export Tools to handle input/output of large datasets in multiple formats (CSV, Parquet, etc.). |
Handles bulk import/export with large and multiple file formats including CSV, Parquet, and Excel. | |
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Business Rule Interceptor Ability to trigger rules or workflows based on prediction outcomes. |
Business rule triggers based on analytic outcomes can be configured in Oracle Analytics workflows. | |
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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. |
Notifications and alerting triggers are configurable in OAC. | |
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Anomaly Detection Integrated detection of unusual patterns in input or output data. |
OAC supports anomaly detection via Oracle Machine Learning and analytic workflows. | |
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Result Visualization Graphical displays of predictions at the record or portfolio level. |
Visualizations and dashboards inherently provide record- and portfolio-level result visualization. |
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. |
OAC supports elastic scaling and distributed compute via OCI, enabling horizontal scalability. | |
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Load Balancing System can distribute tasks evenly across computational resources. |
Load balancing is managed through Oracle Cloud Infrastructure, documented as part of OAC cluster management. | |
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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. |
Resource scaling is automated through Oracle Cloud, adjusting compute/resources based on demand. | |
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Parallel Processing Ability to execute multiple jobs or model trainings in parallel. |
OAC supports parallel processing for ETL, ML, and analytics. | |
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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. |
High availability is part of Oracle's cloud architecture. | |
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Disaster Recovery Automated backup and restore procedures for platform state and data. |
Disaster recovery, backup, and restore procedures are integral to OCI and thus OAC. | |
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Elastic Storage Support for dynamic storage scaling as data grows. |
Elastic storage is provided by the underlying Oracle Cloud platform. |
Security & Compliance
(11 Yes /11 Known /11 Possible features)
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User Access Control Role-based permissions for accessing platform features and data. |
Extensive role-based access control configuration for users and data is a standard OAC feature. | |
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Audit Logs Comprehensive logging of all user and system actions for compliance. |
Comprehensive audit logging is included for both data and actions. | |
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Encryption at Rest Data is encrypted on disk and in database/storage. |
Encryption at rest is a security default for all Oracle Cloud-based storage/services. | |
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Encryption in Transit Data encrypted when being transferred between systems (e.g., SSL/TLS). |
Encryption in transit is implemented via SSL/TLS throughout Oracle Cloud. | |
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GDPR/CCPA Compliance Supports processes to meet personal data regulations (European, US, etc). |
OAC supports GDPR/CCPA compliance with privacy tools and audit controls. | |
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Regulatory Reporting Tools Automated tools or templates for industry regulatory reporting. |
Regulatory reporting templates and automation are available in OAC. | |
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Data Retention Policy Management Automatic enforcement of data archiving and deletion in line with regulations. |
Data retention and lifecycle policies are configurable in the Oracle Cloud Console. | |
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Multi-factor Authentication Support for two-factor or multi-factor authentication for user access. |
Supports multi-factor authentication as part of Oracle Identity and Access Management. | |
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Single Sign-On (SSO) Integration with enterprise identity providers via SSO. |
SSO integration with SAML, OAuth, etc., is fully supported for enterprise SSO. | |
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Penetration Testing Regular third-party security assessments of the platform. |
OCI/OAC undergoes regular third-party penetration testing for security compliance. | |
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Role-based Data Access Granular control over which users can view or edit specific data sets. |
Role-based data access at dataset, report, and field level is supported. |
User Experience & Collaboration
(9 Yes /9 Known /11 Possible features)
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Custom Dashboards Users can configure and personalize analytical dashboards. |
Users can create and personalize dashboards. | |
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Report Scheduling Automatic generation and distribution of reports on a set schedule. |
Report scheduling and email distribution are available out of the box. | |
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Annotation & Commenting Inline commenting and annotation tools for team collaboration. |
Annotation and commenting features are supported in dashboard collaboration. | |
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Mobile Access Full functionality or at least key insights available on mobile devices. |
Mobile access via Oracle Analytics Cloud mobile applications. | |
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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. |
New-user onboarding is guided in the UI and through interactive tutorials. | |
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Role-based Interface Customization UI adapts to user’s functions (e.g., actuary, underwriter, claims manager). |
Interface elements and dashboards can be role-customized. | |
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Document Sharing Direct sharing or export of dashboard, reports, and models. |
Supports document and dashboard sharing/export. | |
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Collaboration Workspace Centralized project or workspace for teams to manage analytics projects. |
Collaboration workspaces for project teams are available. | |
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User Feedback Loop Mechanisms for users to suggest improvements, report bugs, or request features. |
Feedback mechanisms and user input for feature requests are supported. | |
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Accessibility Compliance Meets standards such as WCAG for users with disabilities. |
No information available |
Visualization & Reporting
(11 Yes /11 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. |
Advanced visualizations and extensible UI support more than basic chart types. | |
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Drill-down Capabilities View detailed information and trace factors behind each prediction or trend. |
Drill-down in visualizations is supported. | |
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Geospatial Mapping Visualization of data on geographic maps to track claim concentrations, risk zones, etc. |
Geospatial and map visualizations are available. | |
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Temporal Analysis Tools Visualization of trends and predictions over time. |
Temporal analysis features and timeline visualizations are standard. | |
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Export to PDF/Excel/PowerPoint Direct download or export of reports in common formats. |
Reports can be exported in PDF, Excel, and PowerPoint formats. | |
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Interactive Dashboards Live updating and interactive filtering of visualizations. |
Interactive dashboards are a core OAC offering. | |
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Custom Report Templates Library or builder for creating company-branded report templates. |
Custom report templates and branding are supported. | |
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KPI Tracking Monitor key insurance performance indicators alongside predictive model outputs. |
KPI tracking widgets are standard in Oracle dashboards. | |
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Scheduled Email Distribution Automated periodic sending of insights and reports to stakeholders. |
Scheduled distribution of dashboards/reports via email is supported. | |
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What-if Scenario Analysis Test the outcome of hypothetical situations through simulation. |
'What-if' and scenario analyses are available in predictive modeling modules. | |
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Embedded Analytics Ability to embed visualizations in external portals or applications. |
Embedded analytics for integration with other portals/applications is documented for OAC. |
Deployment & Integration Options
(10 Yes /10 Known /11 Possible features)
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Cloud Deployment SaaS or managed cloud hosting for rapid rollout and scalability. |
Oracle Analytics Cloud is offered as a SaaS, managed via OCI. | |
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On-premise Deployment Support for installation within insurer’s own infrastructure. |
On-premise deployment is available via Oracle Analytics Server. | |
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Hybrid Deployment Ability to split workloads and data between cloud and on-premise environments. |
Hybrid deployment is possible by splitting workloads between OAC and on-premise Oracle instances. | |
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Open RESTful APIs Public APIs to facilitate integration with legacy and new insurance systems. |
Provides open REST APIs for integration. | |
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Webhooks Support Real-time notification and workflow triggers for external systems. |
Webhooks and workflow integration modules are documented features. | |
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SDKs for Developers Software development kits in common languages for custom integration. |
SDKs for customization and integration in common languages are available. | |
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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 CRM, ERP, and DWH integration are available. | |
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Containerization Support Ability to deploy solutions using Docker, Kubernetes, or similar technologies. |
Supports container-based deployment (Docker, Kubernetes) for microservices. | |
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Zero Downtime Deployments Update the platform without user disruption. |
Zero-downtime deployments are supported by Oracle Cloud deployment mechanisms. | |
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Custom Integration Services Professional services or tools for bespoke system integrations. |
Professional services and tools for custom integration are part of Oracle's offerings. |
Monitoring & Model Management
(10 Yes /10 Known /11 Possible features)
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Model Performance Dashboards Real-time status and KPI views for all deployed models. |
Model performance monitoring and dashboarding are available for all deployed models. | |
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Drift Detection Automated detection when model input or output distributions change significantly. |
Automated model drift detection is part of model monitoring tools. | |
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Scheduled Model Retraining Automatic retraining of models on updated data. |
Scheduled retraining can be set for models with automated data pipeline refresh. | |
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Model Health Alerts Notifications when models underperform or exhibit anomalies. |
Model health alerting and performance notification settings are built-in. | |
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A/B Testing Framework Can run multiple models in parallel to determine best outcomes. |
A/B testing framework is part of Oracle's analytic modeling capabilities. | |
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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. |
Manual model override—users can intervene in automated processes as required. | |
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Model Comparison Reports Automatically generated reports comparing model results and accuracy. |
Automatic creation of model comparison reports is available. | |
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Automated Model Archival Old or superseded models can be archived and restored if needed. |
Automated model archival and restore functionality is supported. | |
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Custom Logging Levels Configurable granularity of operational and error logs for models. |
Logging and monitoring granularity is configurable for analytics and ML. | |
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Explainability Monitoring Ongoing measurement of explainability scores for deployed models. |
Ongoing explainability metrics and monitoring are available. |
Insurance-Specific Functionality
(0 Yes /0 Known /11 Possible features)
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Claims Frequency Modeling Templates or wizards for predicting claim counts per time period or policy cohort. |
No information available | |
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Loss Severity Modeling Support for modeling and predicting potential cost per claim. |
No information available | |
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Customer Lifetime Value Prediction Tools to estimate future profitability of policyholders. |
No information available | |
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Fraud Detection Modules Pre-built modules or scripts for identifying potentially fraudulent claims. |
No information available | |
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Churn/Renewal Prediction Predicting which policyholders are likely to lapse or renew contracts. |
No information available | |
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Risk Pool Segmentation Algorithmic grouping of policies/customers with similar risk characteristics. |
No information available | |
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Catastrophe Modeling Scenario modeling for weather, disaster, or other catastrophic event impacts. |
No information available | |
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Quotation Optimization Predictive pricing to optimize quote conversion while managing risk. |
No information available | |
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Regulatory Compliance KPIs Dashboards or reports targeting regional insurance regulatory requirements. |
No information available | |
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Reinsurance Analytics Integration Built-in support for actuarial or portfolio-level analytics for reinsurers. |
No information available | |
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Underwriting Decision Support Predictive analytics specifically designed for supporting underwriters. |
No information available |
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. |
Comprehensive online and embedded documentation is available for Oracle Analytics Cloud. | |
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In-Platform Help Contextual help, tutorials, and support widgets within the UI. |
Contextual and in-platform help is provided in the UI. | |
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Online Knowledge Base Searchable library of FAQs, troubleshooting tips, and community discussions. |
Online knowledge base and support portal are maintained by Oracle. | |
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24/7 Support Availability Around-the-clock access to technical and business support. |
24/7 support is offered with different Oracle support contracts. | |
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Dedicated Account Manager Named advisor for onboarding and ongoing account support. |
Dedicated account managers are assigned for enterprise clients. | |
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Custom Training Programs Role-based or use-case-based remote or on-site training. |
Offers custom and role-based training programs. | |
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Professional Services Consulting, configuration, and hands-on setup services. |
Professional services and consulting are available for onboarding and setup. | |
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User Community Portal Online forums for networking, sharing experiences, and best practices. |
Oracle maintains user community forums and networking resources. | |
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Release Notes & Change Logs Detailed updates on platform enhancements and bug fixes. |
Detailed release notes and change logs are published with each update. | |
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Sandbox Environment Safe, isolated environment for new user experimentation. |
Sandbox/test environments are available for development and safe experimentation. |
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