Insurance Business Scenarios
Insurance solutions that turn data into reliable business value
Consistent data, agile insights and scalable architecture across all policy, claims, agent and customer contacts.
Your Basic Data Infrastructure in Insurance
Standardized, scalable model covering policy, claims, sales and customer experience. Each element in the model maps directly to business processes and drives use cases. Replicated architecture provides flexibility in new product development. Reliability with data quality, business glossary, metadata and traceability.
Moving from Data to Business Value
Integration of legacy and agency systems into modern DWH. Data ingestion, ETL/ELT, data quality, cleansing and standardization processes. Balance of scale, security and cost with cloud, hybrid or on-prem infrastructure options. Reduced latency and met SLAs with management, monitoring and optimization.
Maximum Efficiency in Agencies
Segmentation by performance; disseminating best practices, supporting low-performing agencies. Classification based on sales volume, new policies, customer risk and loyalty analysis. Integration of the distribution channel with digital: agency + digital hybrid approaches. Designing incentive & reward mechanisms for accurate targeting with analytics.
Understanding the Customer, Creating Value
CLV & segmentation to identify the most valuable clusters and increase profitability and retention. Personalized marketing with behavioral, demographic and channel data. UX and journey maps for consistent experience across touchpoints. Proactive detection of churn risk and cross-sell/upsell opportunities.
Insurance Self Service Reports
By providing accessible, visualized reports for decision makers, you can provide data-driven organizational agility with exploratory tools for analysts. You can create customized dashboards for different stakeholders using interactive and visual dashboards compatible with mobile and desktop devices. You can prepare routine reports such as operational KPIs, agency performances and customer trends, and use drill-down capabilities for detailed analysis. With data security and access controls, you can define who and how data can be viewed. With self-service BI tools, analysts and managers can perform independent analysis and data science teams can focus on exploratory analysis.
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