Account Synchronization Matching System for Investment Data
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Solution Overview
Problem
Investment advisers face challenges in transferring and synchronizing account information across different computer systems without requiring extensive intervention, particularly in consolidating data from various online brokerage systems with diverse organizational structures.
Innovation Solution
A system and method that allows investment advisers to register on both data providing and consolidating systems, using matching rules and triggers to automatically transfer, modify, or delete accounts, while handling unique and non-unique matches, and notifying users for manual intervention when necessary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If account information is manually transferred and synchronized between data providing systems and data consolidating systems, then data accuracy and consistency can be maintained, but the complexity of operation and time required increase significantly
Solution Approach 1:
The system enables self-service synchronization where the data consolidating system automatically retrieves account information from data providing systems using configured retrieval rules, matching rules, and triggers without requiring manual intervention. The system serves itself by autonomously performing data transfer, matching, and synchronization tasks based on predefined parameters.
Solution Approach 2:
The system requires preliminary configuration of retrieval rules, matching rules (including unique and non-unique match criteria), and triggers before synchronization begins. These pre-configured parameters enable the system to automatically execute data transfer and matching operations without real-time human intervention, reducing operational complexity while maintaining accuracy.
2Adaptability or versatility
If extensive manual intervention is used to transfer account information between systems, then complex matching scenarios can be handled, but productivity and efficiency decrease
Solution Approach 1:
The system handles diverse matching scenarios by changing and adjusting multiple parameters including unique match criteria, non-unique match criteria, trigger conditions, and retrieval rules. These configurable parameters enable the system to adapt to different matching requirements (one-to-one, one-to-many, many-to-one relationships) while maintaining automated high-speed operation.
Solution Approach 2:
The system dynamically adjusts its matching and retrieval behavior based on configured rules and triggers. The automation adapts to different data scenarios by applying appropriate matching logic (unique vs. non-unique matches) and retrieval strategies without requiring manual reconfiguration, thereby maintaining both versatility and productivity.
3Productivity
If automated data transfer is implemented between systems with different organizational structures, then productivity increases, but measurement precision and data matching accuracy may deteriorate
Solution Approach 1:
The system incorporates feedback mechanisms where matching results are evaluated against configured criteria. Non-unique matches are identified and flagged for potential review, and the system can adjust retrieval and matching operations based on feedback from previous synchronization cycles, thereby maintaining high accuracy while operating automatically.
Solution Approach 2:
The system acts as an intermediary between data providing systems and data consolidating systems with different organizational structures. It uses configurable retrieval rules and matching rules as mediators to translate and adapt data between different systems, ensuring accurate matching despite structural differences while maintaining automated operation.
4Adaptability or versatility
If multiple retrieval rules and matching criteria are configured to handle diverse account structures, then adaptability improves, but device complexity increases
Solution Approach 1:
The system segments the data synchronization process into distinct configurable components: retrieval rules for data extraction, matching rules for data association (unique and non-unique), and triggers for operation initiation. This segmentation allows each component to be configured and managed independently, reducing overall system complexity while maintaining high adaptability.
Solution Approach 2:
The system employs universal configurable parameters and rules that can be applied across different data providing systems and consolidating systems regardless of their organizational structures. This multi-functionality allows the same framework to handle diverse matching scenarios without requiring system-specific customization, thereby reducing complexity while maintaining versatility.
Data Source
AI summary
A system and method synchronizes accounts across different computer systems using a matching computer system and a network, when the accounts on the source computer system are organized differently than they are on the destination computer system.