Secure Transaction Data Hierarchy for Financial Service Providers
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Solution Overview
Problem
Current methods lack an integrated solution for securely storing, monitoring, and analyzing user transaction data, leading to cumbersome manual tracking and significant data security concerns across multiple financial service providers.
Innovation Solution
A computer-implemented system that establishes a secure connection with a client device to authenticate and store transaction data in a hierarchy of nodes, allowing for secure analysis and automatic generation of reminders for follow-up actions, using a security token and rule-based search algorithms to classify and link transaction data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual tracking of transaction data is used across multiple financial service providers, then data can be collected from various sources, but data security concerns increase due to potential misappropriation, spoofing, and theft
Solution Approach 1:
The patent introduces a centralized transaction monitoring system that acts as an intermediary between users and multiple financial service providers. This system collects, stores, and analyzes transaction data in a secure centralized location, eliminating the need for users to manually track and store sensitive data across multiple providers. The intermediary system implements security measures including encrypted data storage, controlled access protocols, and automated verification processes, thereby reducing data security risks while maintaining comprehensive data collection capabilities
Solution Approach 2:
The system provides automated transaction monitoring and analysis capabilities that eliminate manual tracking by users. The centralized system automatically collects transaction data from multiple providers, profiles purchase history, generates analytical reports, and sends notifications about follow-up actions without requiring user intervention. This self-service approach reduces the security burden on users while maintaining comprehensive transaction oversight
2Object-affected harmful factors
If centralized storage of transaction data is implemented, then data security is improved through controlled access, but system complexity increases due to authentication and security token management
Solution Approach 1:
The system implements preliminary authentication by requiring users to register and receive security tokens before accessing the transaction monitoring system. This preliminary action establishes secure access controls upfront, ensuring that only authenticated users can access their transaction data. The security tokens are issued in advance and stored securely, eliminating the need for complex authentication during each transaction access and simplifying the overall security management
Solution Approach 2:
The system transforms complex security management into simplified parameter-based access control. Each user is assigned a unique security token that serves as a parameter for authentication. The system uses these tokens to automatically verify user identity and grant appropriate access levels without requiring complex multi-factor authentication processes. This parameter change from complex authentication protocols to simple token-based access reduces system complexity while maintaining strong security
3Productivity
If automated analysis of transaction data is implemented, then productivity is improved by eliminating manual tracking, but device complexity increases due to hierarchy of nodes and rule-based search algorithms
Solution Approach 1:
The patent segments transaction data into a hierarchical structure of nodes organized by categories (e.g., retail, dining, entertainment) and subcategories. Each transaction is classified into appropriate nodes based on its characteristics, enabling efficient storage and retrieval. This segmentation allows the system to process and analyze large volumes of transaction data systematically without requiring complex unstructured data management, thereby improving productivity while organizing complexity in a manageable hierarchical format
Solution Approach 2:
The system creates standardized templates and profiles for different transaction types and categories. Once a transaction pattern is identified and classified, the system creates a template that can be automatically applied to similar future transactions. This copying mechanism eliminates the need to manually analyze each individual transaction, significantly improving processing efficiency. The templates store the classification rules and analysis logic, reducing the computational complexity required for each new transaction while maintaining comprehensive analysis capabilities
Data Source
AI summary
Methods and systems are described herein for securely analyzing transaction data of a user. A server computing device establishes a secure connection with a client device, which transmits transaction data to the server. The server establishes a hierarchy of nodes to profile a user's purchase history. The hierarchy includes a plurality of article nodes and category nodes. The server creates a new article node instance corresponding to the transaction data, the new article node storing descriptive properties of at least one item purchased by the user determined from the transaction data. The server links the new article node instance to at least one of the category nodes by classifying the descriptive properties of the item purchased with respect to relationships defined by the hierarchy. The server generates and transmits an event trigger to remind the user of a follow-up action and authenticates the client before the trigger is delivered.