Recursive Relationship Discovery System for Business Linkage Analysis

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Solution Overview

Problem

Existing systems for determining comprehensive business relationships between counter-parties lack effective automated and evolving curation capabilities, often relying on insufficient precision and accuracy, leading to inconsistent results and inefficient use of manual adjudication resources.

Innovation Solution

A recursive process that combines automated and manual curation, rules-based adjudication of multiple sources, and self-learning algorithms to accurately determine interrelationship contexts, leveraging historical experiences and dynamic data for scalable and precise relationship assessment.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If automated adjudication is used to determine business relationships, then productivity increases, but measurement precision deteriorates

Engineering Contradiction:

Improverelationship determination speedVSAvoidrelationship accuracy

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The system implements feedback loops where adjudication results are continuously evaluated against ground truth data. Performance metrics are tracked and used to refine adjudication rules and algorithms, enabling the automated system to improve its precision over time while maintaining high productivity

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The adjudication system dynamically adjusts its behavior based on relationship complexity and confidence levels. Simple relationships are processed automatically with high speed, while complex or low-confidence cases are routed to manual review, creating a dynamic system that optimizes both productivity and precision adaptively

Inventive Principle:

Principle #15Dynamics

2Measurement precision

If manual adjudication is used to ensure accuracy, then measurement precision improves, but productivity deteriorates

Engineering Contradiction:

Improverelationship accuracyVSAvoidrelationship determination speed

Core Design Contradiction:

Measurement precisionVSProductivity

Solution Approach 1:

Manual adjudication is applied selectively only to cases where automated systems cannot determine relationships with sufficient confidence. The majority of straightforward cases are resolved automatically, while manual resources are concentrated on the subset of complex cases requiring human judgment

Inventive Principle:

Principle #16Partial or excessive action

Solution Approach 2:

The adjudication process is segmented into multiple stages: initial automated filtering, confidence assessment, selective manual review, and final validation. This segmentation allows manual adjudication to focus only on specific critical subsets rather than processing all relationships

Inventive Principle:

Principle #1Segmentation

3Measurement precision

If multiple data sources are integrated to improve relationship detection, then measurement precision improves, but device complexity deteriorates

Engineering Contradiction:

Improverelationship detection accuracyVSAvoidsystem architecture complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The system employs intermediary components including standardized data integration layers, relationship graphs as intermediate representations, and modular adjudication services. These intermediaries simplify the complexity of integrating multiple data sources by providing standardized interfaces and abstraction layers

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system implements universal data models and standardized schemas that can represent multiple data sources and relationship types through common structures. This universality allows diverse data sources to be integrated without proportionally increasing system complexity

Inventive Principle:

Principle #6Universality (Multi-functionality)

4Measurement precision

If comprehensive evaluation of multiple indicia is performed, then measurement precision improves, but loss of time deteriorates

Engineering Contradiction:

Improverelationship verification accuracyVSAvoidadjudication processing time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system performs preliminary filtering and pre-processing of indicia before full evaluation. High-confidence relationships are identified and validated using simplified criteria, while only ambiguous cases undergo comprehensive multi-indicia evaluation, reducing overall processing time

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS10019681B2Multidimensional recursive learning process and system used to discover complex dyadic or multiple counterparty relationships

Publication Date: 2018.07.10 THE DUN & BRADSTREET CORP

AI summary

A multidimensional recursive and self-perfecting process used to discover dyadic or multi-counterparty relationships between parties, the process comprising: (a) collecting information from a plurality of data sources; (b) discovering dyadic or multi-counterparty relationships between the parties from the collected information; (c) clustering the parties to infer the dyadic or multi-counterparty relationships between the parties based on common or partially intersecting attributes between the parties, thereby forming clustered parties; (d) evaluating the clustered parties for business linkage potential by integrating the collected information and contextually assessing indicia from the data sources to detect and measure consistency and inconsistency for a given party or dyadic or multi-counterparty relationship; (e) positing and evaluating relationship type and role said party plays in each relationship; and (f) assessing the confidence level regarding the likelihood that the dyadic or multi-counterparty relationship exists between the parties.