Relationship Mapping Using Conditional Rules and Base Data Layers
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Solution Overview
Problem
Existing systems struggle to efficiently manage and store data on relationships between entities due to varying definitions and regulations, leading to redundancy and increased computational resources.
Innovation Solution
A system and method for generating and managing base layer data objects that represent entities and relationships, using conditional rules to identify contextual relationships, which are adaptable to changing definitions and regulations, reducing redundancy by leveraging a centralized data store.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data is collected and stored for each specific relationship definition, then relationship data can be managed according to specific contexts, but data redundancy and storage costs increase
Solution Approach 1:
The patent implements a universal base layer data object structure that serves multiple relationship contexts. Instead of creating separate data structures for each relationship type, the system uses a single standardized format with configurable attributes that can represent different relationship definitions (counterparty, beneficial owner, controlled entity, etc.), eliminating the need to store multiple copies of the same underlying data.
Solution Approach 2:
The patent segments relationship data into two distinct layers: base layer data objects (containing fundamental entity information) and relationship layer data objects (containing contextual relationship definitions). This segmentation allows the base layer to be stored once and reused across multiple relationships, while the relationship layer stores only the varying contextual attributes, significantly reducing overall data volume.
2Adaptability or versatility
If relationship data is collected and stored for multiple contexts, then comprehensive relationship mapping is achieved, but computational resources increase
Solution Approach 1:
The patent performs preliminary action by pre-defining standardized base layer data object structures and relationship types before actual relationship mapping occurs. This pre-configuration enables the system to quickly match entities to appropriate relationship templates without performing complex computations during data processing, reducing real-time computational resource consumption while maintaining support for multiple contexts.
3Measurement precision
If targeted data collection is performed for each relationship definition, then data accuracy for specific purposes is improved, but data collection and processing time increases
Solution Approach 1:
The universal base layer data object structure collects comprehensive entity information once in a standardized format that satisfies multiple relationship definitions simultaneously. This eliminates the need for separate targeted data collection processes for each relationship type, reducing data collection and processing time while maintaining the accuracy required for different purposes through the configurable relationship layer.
Data Source
AI summary
Systems and method for relationship mapping may include server(s) for providing base layer data objects to a computing device including entity and relationship base layer data objects. The server(s) may receive a conditional rule from a computing device which defines contextual relationship between two entity base layer data objects. The server(s) may determine that a first entity base layer data object and a second entity base layer data object satisfy the contextual relationship by applying the conditional rule received from the computing device to attributes corresponding to first and second entity base layer data objects. The server(s) may store an association between the first and second entity base layer data object in accordance with the contextual relationship.