Occupational Risk Scoring for Creditworthiness Assessment
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Solution Overview
Problem
Current financial account providers lack the ability to effectively assess long-term creditworthiness of customers, as they do not utilize occupational stability data, leading to limited insights into a customer's ability to repay debt and resulting in inadequate risk analysis and credit line optimization.
Innovation Solution
A system and process that incorporates occupational stability data to determine creditworthiness by assigning risk band scores to occupations based on stability indicators, generating an occupational risk score for customers, which is then used to calculate their creditworthiness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional credit assessment methods (credit score, household income, assets) are used, then the present situation and ability to repay debt can be assessed, but long-term creditworthiness and stability cannot be determined
Solution Approach 1:
The system collects and stores occupational data (occupation type, tenure, industry) in advance during account opening and periodic reviews, so that when creditworthiness assessment is needed, this preliminary occupational stability information is already available to enhance the prediction accuracy without requiring additional data collection at assessment time
Solution Approach 2:
The patent adds a new dimension of occupational stability assessment by introducing occupation-type indicators (stable vs. unstable occupations), occupation tenure, and industry stability metrics to the traditional credit assessment framework, transforming the assessment from purely financial metrics to a multi-dimensional evaluation that includes occupational characteristics
2Reliability
If occupational data is collected and analyzed, then long-term creditworthiness prediction improves, but system complexity increases
Solution Approach 1:
The system segments occupations into stable and unstable categories based on predefined criteria (occupation type, tenure requirements, industry stability), allowing the complex occupational data to be processed through discrete classification rules rather than continuous analysis, thereby reducing computational complexity while maintaining prediction reliability
Solution Approach 2:
The patent transforms qualitative occupational characteristics into quantitative parameters (occupation-type indicator variables, tenure duration in months, industry stability indices) that can be directly integrated with numerical credit scoring models, enabling the system to handle occupational data using standard statistical methods without requiring complex analytical frameworks
Data Source
AI summary
Systems and methods are disclosed for determine creditworthiness based on the stability of the customer's occupation. Occupational risk scores may be used to group stable or unstable occupations and may be used in conjunction with other indicators of creditworthiness. Risk band scores may also be used to determine creditworthiness. Other aspects of the disclosed embodiments are described herein.