Flexible Risk Package Framework for Automated Generation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing systems face challenges in efficiently and accurately generating risk relationship packages, particularly in assessing package profitability and updating rates, which can be costly and time-consuming due to the need for frequent filings with state insurance departments.
Innovation Solution
A flexible structure framework is implemented using a computer server that accesses risk relationship package data, transmits potential risk coverage types, receives user selections, and calculates overall attribute values based on pre-determined rules and algorithms, allowing for automated generation and updating of risk relationship packages.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If package changes are made using traditional methods, then package profitability and rate levels can be assessed, but full rate, rule, and form filings with state DOI are required which are costly and time consuming
Solution Approach 1:
The patent segments the risk relationship package into modular components (coverage types, limits, deductibles, endorsements) that can be independently selected and configured. This segmentation allows the system to generate packages by assembling pre-approved modules without requiring complete re-filing with state DOI, thereby reducing time and cost while maintaining regulatory compliance.
Solution Approach 2:
The system performs preliminary actions by pre-approving rate, rule, and form templates with the state DOI before actual package generation. Once these foundational elements are approved, the system can rapidly configure specific packages by selecting from pre-approved options without requiring repeated full filings, thus accelerating package development while ensuring regulatory adherence.
2Measurement precision
If traditional package assessment methods are used, then package profitability can be evaluated, but the process is difficult and complex
Solution Approach 1:
The patent implements feedback mechanisms where the system automatically calculates package profitability metrics (such as loss ratios, expense ratios, and combined ratios) based on selected package components and historical data. This real-time feedback allows underwriters to assess package profitability accurately during the configuration process, eliminating the need for complex manual calculations and iterative assessments.
Solution Approach 2:
The system performs self-service by automatically generating profitability assessments and regulatory compliance checks when package components are selected. The system autonomously evaluates package attributes, calculates pricing, and ensures compliance with state requirements without requiring complex external assessment tools or manual intervention, thereby simplifying the overall process while maintaining precision.
3Adaptability or versatility
If flexible package configurations are enabled, then package customization is improved, but package profitability assessment becomes more difficult
Solution Approach 1:
The patent creates a universal assessment framework that handles diverse package configurations through standardized algorithms. The system uses a common set of pricing rules, rating factors, and profitability calculations that work across all package types and configurations. This universal approach allows flexible customization of package components while maintaining consistent and manageable profitability assessment methodology, eliminating the need for separate assessment processes for different package types.
Data Source
AI summary
A risk relationship package data store may contain electronic records, each electronic record representing a risk relationship package between an enterprise and an entity, and including, for each package, an electronic record identifier and an overall attribute value. A computer server may transmit, to a remote device associated with the entity, a set of potential types of risk coverage based on information in an available type of risk coverage data store. The server may then receive an indication of a selected subset of the potential types of risk coverage and, based on the received indication and a pre-determined rule, generate a risk relationship package for the entity using a flexible structure framework. The server may calculate an overall attribute value for the package based on an attribute algorithm (such that at least one reduction to the overall attribute value is applied based on an amount associated with the selected subset).