Dynamic Credit Evaluation Using Segmented Trade Data
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Solution Overview
Problem
Current credit reports lack the necessary current and relevant trade experiences to enable accurate creditworthiness decisions, especially in volatile economic environments, and fail to provide granular insights into payment behavior trends.
Innovation Solution
A computer-implemented method and system that processes and aggregates detailed trade data, enriches it with demographics for segmentation, and applies customer-specific evaluation criteria to generate timely and accurate credit reports, allowing for user-defined prioritization and event-driven alerts, and includes meta-data tagging for enhanced relevancy and classification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a payment index score is calculated as a weighted average of all trade experiences, then a single credit rating is produced, but the score masks differences in payment behavior across different parties and relationships
Solution Approach 1:
The patent segments the single payment index score into multiple industry-specific payment index scores. Instead of providing one overall credit rating, the system divides the evaluation into separate scores for different industries (e.g., manufacturing, retail, services), allowing customers to see how their payment behavior compares across different sector peers. This segmentation reveals payment behavior differentiation that was previously masked in a single aggregate score.
2Productivity
If only 12 months of trade history is captured in a single payment experience, then a quick snapshot is provided, but sensitivity analyses based on payment dates become difficult
Solution Approach 1:
The patent segments the 12-month trade history into multiple industry-specific time periods. Each industry receives its own payment index calculation based on trade experiences occurring within the past 12 months, but the segmentation allows for further analysis by industry sector. This enables sensitivity analyses by comparing payment behaviors across different industries while maintaining the 12-month look-back period for each sector.
3Ease of operation
If conventional trade reporting summarizes payment experiences under normal market conditions, then decisioning is simplified, but visibility into payment behavior trends is masked during volatile conditions
Solution Approach 1:
The patent implements dynamic payment index scores that adapt to market conditions. The system continuously monitors trade experiences and recalculates industry-specific payment indices in real-time, allowing the scores to reflect current economic conditions and emerging payment behavior trends. This dynamic approach maintains decisioning simplicity while providing visibility into trends during volatile markets, as the scores automatically adjust to incorporate new information about payment patterns.
4Device complexity
If a single payment index score is provided for all industries, then processing is simplified, but the score is not predictive of how a company will pay a particular party in specific industries
Solution Approach 1:
The patent segments the single payment index into multiple industry-specific payment indices. Instead of calculating one overall score, the system calculates separate payment indices for each industry sector, which significantly improves prediction accuracy. Each industry-specific score is based on trade experiences and payment behaviors characteristic of that sector, making the scores more reliable indicators of how a company will pay parties in specific industries.
Data Source
AI summary
A computer implemented method and system for providing a credit evaluation report, the method comprising: searching a reference file of entities; identifying an entity of interest; determining user specified rules or criteria; selecting at least one relevant trade experience from a database of trade experiences for the entity of interest based upon the user specified rules or criteria, records for comparison to the relevant trade experience, and/or peer groups; and generating the credit evaluation report of the entity of interest based upon the relevant trade experience.