Dispute Resolution System Using Distributed Register and ML
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing systems for monitoring resource transactions and resolving disputes rely on corruptible or manipulatable data storage, lacking secure and immutable storage solutions that allow distributed, verifiable data access for multiple parties involved in dispute resolution.
Innovation Solution
A system combining machine learning with a distributed register for secure, immutable storage of transaction data, enabling enhanced dispute validation, communication, and historical review through natural language processing and intelligent data forwarding, ensuring unauthorized data manipulation is prevented and verified data is accessible to relevant entities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a distributed register is implemented for secure, immutable storage of transaction data, then data security and reliability are improved, but system complexity increases
Solution Approach 1:
The patent introduces a dispute resolution system that acts as an intermediary layer between the distributed register and the parties involved in transactions. This mediator coordinates dispute resolution processes, manages evidence submission, and facilitates communication without requiring direct manipulation of the underlying distributed register infrastructure, thereby simplifying the user interface while maintaining security.
Solution Approach 2:
The system creates simplified copies or representations of the complex distributed register data that are accessible to users and dispute resolution participants. Instead of requiring direct interaction with the full distributed register system, participants work with curated data copies that maintain the immutability and security properties while being easier to manipulate and understand.
2Productivity
If machine learning and natural language processing are integrated for dispute validation and analysis, then dispute resolution efficiency is improved, but computational resource requirements increase
Solution Approach 1:
The system performs preliminary machine learning analysis and natural language processing on transaction data and dispute evidence before formal dispute resolution begins. By pre-processing and validating data using ML algorithms, the system reduces the computational burden during actual dispute resolution proceedings and identifies cases that require human intervention versus those that can be automatically resolved.
Solution Approach 2:
The patent applies machine learning and NLP selectively to only those disputes or data elements that require such analysis, rather than processing all transaction data uniformly. The system identifies cases where ML intervention adds value and applies computational resources accordingly, avoiding excessive processing for simple or clearly-resolvable disputes.
3Reliability
If multiple parties are granted access to verify data records on the distributed register, then transparency and trust are improved, but data access management complexity increases
Solution Approach 1:
The patent segments data access permissions by role and dispute stage, creating different access levels for different parties (e.g., plaintiffs, defendants, neutral arbitrators, system administrators). Each party type receives tailored access rights appropriate to their function in the dispute resolution process, simplifying access management while maintaining comprehensive transparency where needed.
Solution Approach 2:
The distributed register system is designed to serve multiple functions simultaneously: it acts as a secure transaction ledger, a dispute evidence repository, a communication platform, and a verification system. This multi-functionality reduces the need for separate systems for each purpose and simplifies overall access management by providing a unified interface for diverse operations.
Data Source
AI summary
The systems and methods described include the ability to store resource transaction information in an immutable and distributed, verifiable fashion. The system includes enhanced means for retrieving, interacting with, and visualizing such information via user interface on a variety of user device types utilizing multiple information communication channels. The system is further configured to intelligently extract and analyze data to provide dispute identification information to an end user and further determine appropriate resolution actions based on historical data and extrapolated pattern identification.