Convertible Term Product Pricing via Big Data Segmentation
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Solution Overview
Problem
Current insurance products are not attractive to younger consumers due to their high cost and lack of flexibility, and existing term products struggle to adapt to changing market trends, making it difficult to create new products that meet evolving customer needs.
Innovation Solution
A computer-implemented system using big data analytics to disaggregate existing term product pricing, assess market needs, and reconstitute products by dividing them into constituent parts, applying insights from big data analytics to re-price and re-constitute them, creating a new pricing and selling model for convertible term products.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing term products are offered to younger consumers, then the products provide the type of protection customers are seeking, but the products are too expensive and lack flexibility
Solution Approach 1:
The patent segments the term product into multiple components (pure protection component and investment component) that can be separately priced and combined. This allows customers to choose only the protection portion at a lower cost, making the product more attractive to younger consumers while maintaining the reliability of protection coverage.
Solution Approach 2:
The patent introduces dynamic convertibility features that allow the product structure to change over time. Customers can convert between different product types (term insurance to permanent insurance) based on their changing needs, adding flexibility without compromising the core protection coverage.
2Reliability
If existing term products are designed for traditional markets, then the products meet established customer needs, but the products cannot adapt to constantly changing market trends
Solution Approach 1:
The patent creates dynamically adjustable product structures that can adapt to changing market conditions and customer preferences. The convertible term product allows transitions between different insurance types, enabling the product to evolve with market trends while maintaining core protection performance.
Solution Approach 2:
The patent designs a universal product platform that can serve multiple market segments and functions. The same base product can be configured for different customer groups (young consumers, traditional customers) and can transform into different insurance types, providing both reliability and adaptability.
3Adaptability or versatility
If term products are created to address new market needs, then the products may be more attractive to younger consumers, but the difficulty of creating new insurance products increases
Solution Approach 1:
The patent segments the product development process into standardized components that can be independently designed, priced, and tested. This modular approach reduces development complexity by allowing teams to work on separate components simultaneously and reuse proven components across different product variants.
Solution Approach 2:
The patent implements a phased product development approach where core protection components are developed first with proven pricing models, and additional features (investment components, conversion options) are added incrementally. This reduces initial development complexity while maintaining flexibility for future enhancements.
Data Source
AI summary
Methods and systems for developing profitable convertible term products are disclosed. The methods include the disaggregation of the pricing of existing term products and the use of big data analytics to identify opportunities to improve the acceptance of the product within a particular share of the market. Then, a pricing model and a selling model are built to test the product.