Modular Risk Rater Data Structure for Insurance Portfolio Analysis
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Solution Overview
Problem
Insurance companies face challenges in quickly and comprehensively calculating the financial impact and risk metrics for adding insurance policies to their portfolios, particularly due to the complexity of determining desirable policies based on location and likelihood of damage from threats like floods, fires, and bad weather, which requires a sophisticated and customizable framework.
Innovation Solution
A modular system for building risk evaluation products that includes a risk rater data-structure with abstracted representations, allowing non-specialists to generate and implement risk rating schemes on-the-fly, comprising risk characteristic input fields, mathematical operations, rule calls, and lookup table calls, facilitating modification and updating without affecting other system components.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a sophisticated framework is used to determine desirable policies based on location and likelihood of damage, then the accuracy and comprehensiveness of risk evaluation is improved, but the complexity of the system increases
Solution Approach 1:
The risk evaluation framework is segmented into distinct modular components: risk rating schemes, rule sets, lookup tables, and calculation engines. Each component can be independently configured, modified, and maintained, allowing the system to achieve high evaluation accuracy through sophisticated multi-peril assessment while managing complexity through clear separation of concerns. The modular architecture enables non-specialists to work with specific segments without needing to understand the entire system.
Solution Approach 2:
The patent introduces an intermediary layer between the complex risk evaluation logic and the end users. This intermediary provides standardized interfaces and abstraction layers that hide the underlying complexity of multi-peril risk calculations, rule evaluations, and financial metric determinations. Non-specialist users interact through simplified interfaces while the intermediary handles the sophisticated computations behind the scenes.
2Adaptability or versatility
If the system is made highly customizable to adapt to changing conditions, then the adaptability is improved, but the ease of operation deteriorates due to the need for specialized programming
Solution Approach 1:
The risk rating schemes and rule sets are designed to be dynamic and reconfigurable without requiring system redesign. Users can add, modify, or remove risk characteristics, rules, and lookup tables through configuration interfaces. The system adapts to changing business conditions by allowing runtime modifications to evaluation parameters while maintaining operational simplicity through standardized configuration mechanisms that do not require specialized programming knowledge.
Solution Approach 2:
The system enables non-specialist users to perform self-service configuration and customization of risk evaluation parameters. Through intuitive interfaces, users can independently adjust risk characteristics, modify rule sets, and update lookup tables based on changing business needs without requiring programmer intervention. This self-service capability maintains ease of operation while achieving high adaptability.
3Reliability
If the system processes complex multi-peril risk data comprehensively, then the reliability of risk assessment is improved, but the processing time increases
Solution Approach 1:
The system performs preliminary actions by pre-configuring risk rating schemes, rule sets, and lookup tables before actual risk assessments are conducted. Risk characteristics and evaluation criteria are established in advance, allowing the processing engine to execute assessments efficiently by applying pre-compiled logic rather than computing everything from scratch. This preliminary setup maintains comprehensive multi-peril evaluation while reducing runtime processing time.
Solution Approach 2:
The patent replaces traditional mechanical computing approaches with optimized processing engines that use efficient algorithms and data structures for evaluating complex multi-peril risks. The system substitutes brute-force calculation methods with smarter computational techniques, including rule-based evaluation engines and pre-computed lookup tables, thereby maintaining reliable comprehensive assessment while significantly reducing processing time.
Data Source
AI summary
The present disclosure describes an approach to constructing and implementing risk rating products that provides a number of advantages. Instead of hard-coding attributes of a risk rating scheme, which requires the assistance of a trained programming specialist for any modifications, adjustments, or new products, the present invention provides a set of modular tools that assist non-specialists in on-the-fly generation and implementation of risk rating products. The modularity of this approach facilitates the modification and/or updating of a system component without affecting the operation of other components. Described herein are embodiments of a risk rater data-structure, which comprises an abstracted representation of a risk rating scheme that may be loaded into and/or interpreted by other system components to generate a user interface for processing risk information and generating insurance quotes.