Insurance Product Model Metadata Segmentation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current insurance policy administration systems require extensive and costly software changes to manage new policy lines, coverage types, or risk units, as these elements are typically hardcoded, making it difficult to adapt to diversity in insurance policies and increasing the risk of coding errors.
Innovation Solution
An insurance product model-based approach that uses metadata to define policy structures, allowing new information to be incorporated into the model without reprogramming, enabling the interpretation of supplemental policy-specific data to facilitate insurance-related actions such as policy creation and management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If policy lines, coverage types, and risk units are hardcoded into the software system, then the system structure is simple and stable, but the system cannot adapt to new policy lines, coverage types, or risk units without extensive and costly software changes
Solution Approach 1:
The patent segments the policy administration system into distinct modular components: policy lines, coverage types, and risk units are separated into independent data structures that can be individually managed, added, or modified without affecting the entire system. This segmentation enables flexible adaptation to new policy requirements while maintaining system stability.
Solution Approach 2:
The patent implements a universal policy administration framework that can handle multiple policy lines, coverage types, and risk units through a common set of data structures and processing logic. This universal approach allows the system to accommodate diverse insurance products without requiring separate hardcoded implementations for each policy type.
2Ease of manufacture
If policy structures are hardcoded into the software, then the system is stable and reliable, but any changes require extensive reprogramming that increases coding risks and time consumption
Solution Approach 1:
The patent transforms the static hardcoded policy structures into dynamic, configurable data structures that can be modified without reprogramming. The system uses data-driven definitions for policy lines, coverage types, and risk units, allowing administrators to update policy structures by modifying data configurations rather than writing code, thereby reducing coding risks while maintaining system reliability.
3Productivity
If separate database tables, screens, and processing logic are created for each risk unit, coverage, and policy line, then the system is well-organized and maintainable, but the system cannot support new policy elements without creating additional separate components
Solution Approach 1:
The patent merges the management of policy lines, coverage types, and risk units into a unified data structure framework. Instead of maintaining completely separate components for each policy element, the system uses integrated data structures with standardized fields and relationships, reducing the number of separate components needed while improving productivity in policy creation and management.
Data Source
AI summary
An insurance product model comprising insurance policy metadata is provided (101) in a computer memory. The insurance policy metadata may comprise, at least in part, data that describes information that comprises a given corresponding insurance policy. A computer then serves to substantively interpret (102) this insurance product model to facilitate obtaining supplemental policy-specific data. The supplemental policy-specific data and the insurance policy metadata comprise separate and discrete data models and may, if desired, be stored (103) separately from one another. So configured, these teachings further support using (104) the insurance product model and the supplemental policy-specific data to facilitate an insurance-related action.