Risk Relationship Life Event Analytical Modeling Platform
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Solution Overview
Problem
The process of updating insurance policies to reflect significant life events is inefficient, requiring time and effort from both insurance agents and policyholders, and is inconvenient for direct updates without agent or company involvement.
Innovation Solution
A risk relationship life event analytical modeling platform that uses a back-end application server to determine potential risk relationships, retrieve relevant records, execute analytical models for adjustment recommendations, and automatically transmit these recommendations to communication addresses, facilitating faster and more accurate policy adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If an experienced insurance agent manually guides a policyholder through questions to obtain information about life events, then the policy adjustments can be determined accurately, but the process is inefficient and requires significant time and effort from both the agent and policyholder
Solution Approach 1:
The system enables policyholders to automatically update their insurance policies by connecting their personal data sources (e.g., HR systems, government databases) to the insurance platform. The policyholder's information is automatically retrieved and used to determine policy adjustments without requiring manual agent intervention, thus maintaining accuracy while dramatically improving efficiency.
Solution Approach 2:
The manual mechanical process of agent-policyholder interaction is replaced with an automated electronic system that uses data APIs and algorithms to automatically detect life events, retrieve relevant information, and determine policy adjustments. This substitution eliminates the time-consuming manual questioning process while preserving the accuracy of adjustments through systematic data analysis.
2Ease of operation
If an insurance agent manually collects and processes information about life events, then policy adjustments can be determined, but the process is inconvenient for policyholders who wish to update policies directly without agent involvement
Solution Approach 1:
The system empowers policyholders to independently update their policies by providing them with direct access to the policy management platform. Policyholders can connect their personal data sources, review detected life events, and approve policy adjustments without needing to contact an agent, making the process convenient and eliminating time delays associated with manual agent involvement.
Solution Approach 2:
The system proactively identifies life events by continuously monitoring policyholder data sources before the policyholder even realizes the need for update. By performing preliminary detection and preparation of policy adjustment recommendations, the system eliminates the time policyholders would otherwise spend initiating and coordinating updates with agents.
3Reliability
If traditional manual processes are used for policy updates, then insurance agents can guide policyholders through the process, but the process requires significant time and effort from both parties
Solution Approach 1:
The complex manual coordination process between agents and policyholders is replaced with an automated electronic system that uses standardized data interfaces and algorithmic decision-making. The system maintains reliability by using the same logical criteria that agents would apply, while eliminating the coordination complexity through automated data exchange and systematic processing workflows.
Solution Approach 2:
The system creates a universal platform that handles multiple functions (data collection, life event detection, policy analysis, adjustment determination, and communication) that were previously distributed across multiple manual processes. This consolidation maintains the reliability of policy adjustment determination while reducing the overall system complexity by eliminating the need for coordinated human actions across multiple steps.
Data Source
AI summary
A system to provide a risk relationship life event analytical modeling platform via a back-end application computer server of an enterprise. The system may include a risk relationship data store that contains electronic records representing potential risk relationships between the enterprise and a plurality of entities. Each record may include an electronic record identifier, at least one third-party indication associated with an upcoming life event, and a communication address. The server may determine a selected potential risk relationship and retrieve, from the risk relationship data store, the electronic record associated with the selected potential risk relationship. An analytical model may be executed based on the upcoming life event to generate a proactive notification including information based on the upcoming life event and data in the electronic record. The server may then automatically transmit information about the proactive notification to the communication address.