Geolocated Insurance Subscription via Distributed Ledger
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Solution Overview
Problem
Current systems for online insurance policy subscription lack utilization of mobile device capabilities like geolocation for targeted offers, fail to ensure contract inalterability without paper support, and inadequately protect user privacy and combat fraud.
Innovation Solution
A method and system utilizing geolocation-enabled mobile applications connected to a back-end infrastructure for secure, real-time insurance policy selection, purchase, and registration, employing semantic search algorithms, AI, cryptography, and blockchain for secure storage and dynamic contract management, along with mechanisms for fraud prevention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If distributed ledgers are used for secure transactions, then transaction security is improved, but system complexity increases
Solution Approach 1:
The patent introduces a digital platform as an intermediary layer between users and the distributed ledger system. This platform handles complex blockchain operations, smart contract execution, and coordination with multiple insurance companies, thereby maintaining high security while shielding users from underlying system complexity.
Solution Approach 2:
The system is divided into modular components: mobile application layer, digital platform layer, and distributed ledger layer. Each layer handles specific functions independently, allowing the complex blockchain infrastructure to be managed separately from user interactions, thus reducing perceived complexity while maintaining security.
2Adaptability or versatility
If mobile device capabilities are fully exploited for targeted offers, then service personalization is improved, but data processing requirements increase
Solution Approach 1:
The system processes and analyzes mobile device data locally where possible, and only transmits essential information to the digital platform. Geolocation data, device sensors, and user preferences are processed to generate personalized insurance offers without requiring complete raw data transmission, thus reducing overall data processing requirements while maintaining high personalization.
3Reliability
If geolocation and device data are collected for fraud prevention, then fraud detection capability is improved, but user privacy concerns increase
Solution Approach 1:
The digital platform acts as an intermediary that processes geolocation and device data through encrypted channels. Personal identifiers are removed or anonymized during processing, and only essential verification data is stored on the distributed ledger. This maintains strong fraud detection capabilities while protecting user privacy through multiple layers of data protection.
4Productivity
If smart contracts are used for automatic policy management, then operational efficiency is improved, but contract flexibility decreases
Solution Approach 1:
The system implements dynamic smart contracts that can be updated and modified through predefined governance mechanisms. While maintaining automatic execution for core terms, the contracts allow for flexible adjustments in coverage parameters, premiums, and conditions through authorized updates, thus balancing operational efficiency with contract flexibility.
Data Source
AI summary
A system for subscribing insurance policies from geolocated mobile devices, that uses geolocation to allow customers to select a suitable policy and finalize a purchase thereof, the system enabling selection of a policy from a plurality of policies categorized or automatically suggested according to user preferences, reservation of special contractual conditions, entering of necessary documents from a mobile device, and purchasing of policies online from the mobile device, the system including a mobile application that operates on the mobile device and a central infrastructure that includes user and insurance policy databases, a policy-position element generator, and a generator of insurance proposals, based on machine learning algorithms.


