Autonomous Data Containers With AI for Transaction Data Control
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Solution Overview
Problem
Consumers lack control over their financial transaction data, which is stored in static structures and not fully utilized, and providers face challenges in effectively using this data due to its proliferation.
Innovation Solution
Implementing autonomous data containers with embedded artificially intelligent agents that can analyze transaction information, make purchases on behalf of consumers, and detect fraud, while allowing decentralized storage and communication among multiple containers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If financial transaction data is stored in static data structures in databases owned by financial parties, then the data can be queried by various services, but consumers do not have access to their own financial transaction data and have limited control over how the data is used
Solution Approach 1:
The patent segments the centralized data storage system into distributed autonomous data containers, each owned and controlled by an individual consumer. Each container holds a portion of the consumer's financial transaction data and operates independently, enabling consumers to have direct control over their own data while maintaining system functionality through the collective action of multiple containers.
Solution Approach 2:
The autonomous data containers are equipped with embedded artificial intelligence agents that enable self-service capabilities. These agents automatically manage data access requests, authenticate users, control data sharing permissions, and execute transactions without requiring consumers to directly manage the technical infrastructure, thus providing consumer control while minimizing operational complexity.
2Productivity
If financial transaction data is stored in multiple locations across different databases, then data proliferation occurs, but providers in control of the data may not be able to put all the data to good use
Solution Approach 1:
The autonomous data containers are designed with multi-functionality to address various data utilization needs. Each container can selectively share data with different services based on consumer preferences, enabling the same data to be used for multiple purposes (spending analysis, credit scoring, marketing, fraud detection) simultaneously without compromising accessibility or utility.
Solution Approach 2:
The system implements feedback mechanisms where the embedded AI agents continuously monitor data access patterns, transaction outcomes, and consumer preferences. This feedback enables dynamic adjustment of data sharing policies and improves data utilization efficiency over time by learning from past interactions and optimizing which services receive access to which data.
3Adaptability or versatility
If autonomous data containers with embedded artificially intelligent agents are implemented, then consumers can control their data usage and data can be efficiently utilized for personalized purchases and fraud detection, but the device complexity increases
Solution Approach 1:
The system employs a nested structure where autonomous data containers are distributed across a network infrastructure. Each container is a self-contained unit with embedded AI agents, but multiple containers can be hierarchically organized and coordinated through the broader network, allowing complex functionality to emerge from simpler individual components working together.
Data Source
AI summary
An autonomous data container and methods of use are disclosed. The autonomous data container includes a data storage structure for storing financial transaction information. The autonomous data container also includes an artificially intelligent agent stored as code within the container. The artificially intelligent agent can run on a system storing the autonomous data container. The artificially intelligent agent can access transaction information in the data storage structure and make predictions and/or decisions on a consumer's behalf. The artificially intelligent agent can make new purchases on the consumer's behalf. The artificially intelligent agent can also provide fraud alerts for the consumer.