Ability-to-Repay Scoring Using Dynamic Expense Classification
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing ability-to-repay (ATR) analysis methods are static and fail to accurately assess a borrower's capacity to repay loans due to their reliance on fixed income and expense sources, neglecting dynamic changes in financial stability.
Innovation Solution
A system and method that dynamically evaluates a borrower's ability to repay by classifying debits into discretionary and non-discretionary expenses, adjusting discretionary expenses, and computing an ability-to-pay score based on adjusted income and expenses, providing a more accurate creditworthiness assessment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If static ATR analysis is used to evaluate creditworthiness, then the evaluation process is simple and quick, but the accuracy of assessing a borrower's true repayment capacity deteriorates because it relies on fixed income and expense sources that do not reflect dynamic financial changes
Solution Approach 1:
The patent transforms the static ATR evaluation into a dynamic system by continuously monitoring financial accounts and updating the ability-to-repay score in real-time based on changing income and expense patterns. The system processes ongoing transaction data to reflect current financial capacity rather than relying on historical snapshots, thereby improving measurement precision while managing complexity through automated data processing.
Solution Approach 2:
The system changes the evaluation parameters from fixed income/expense sources to dynamic cash flow patterns by analyzing actual transaction data. It adjusts the ability-to-repay score based on varying financial conditions, including discretionary versus non-discretionary expenses, thereby capturing the true dynamic repayment capacity without requiring an overly complex manual evaluation process.
2Measurement precision
If traditional ATR scoring rules are applied that penalize borrowers with negative collections activity or bankruptcy filings, then the evaluation process is straightforward, but the accuracy deteriorates because these borrowers may have lost the most points despite potentially having strong current repayment capacity
Solution Approach 1:
The system performs preliminary analysis of current cash flow patterns and financial stability before applying traditional scoring penalties. By evaluating the borrower's current ability to service debt based on real-time financial data, the system can offset or mitigate historical negative events if the borrower demonstrates strong current repayment capacity, thereby improving assessment accuracy while maintaining operational simplicity through automated rule-based adjustments.
Solution Approach 2:
The system incorporates feedback loops where current financial performance information continuously updates the ability-to-repay score. Borrowers with strong current cash flow and financial stability can improve their scores despite historical negative events, as the system provides ongoing feedback based on actual repayment behavior and financial conditions rather than relying solely on static historical penalties.
3Measurement precision
If discretionary expenses are fully counted in ATR analysis, then the evaluation process is simple, but the accuracy deteriorates because it assumes all income and expenses will continue, ignoring the dynamic nature of financial obligations
Solution Approach 1:
The system segments expenses into discretionary and non-discretionary categories by analyzing transaction patterns and merchant types. Non-discretionary expenses (essential living costs, existing debt payments) are treated as committed obligations, while discretionary expenses (entertainment, dining, optional purchases) are treated differently in the ATR calculation. This segmentation improves measurement precision by reflecting true committed payment capacity while managing complexity through automated classification algorithms.
Data Source
AI summary
A system for determining an ability-to-pay an obligation is provided. The system may be configured to electronically receive a query for a transaction between a borrower and a lender. The system may be configured to receive a plurality of data associated with the borrower, and may classify debits within the data as either discretionary or non-discretionary expenses. The system may be configured to adjust the discretionary expenses by an amount based on at least one type associated with the discretionary expenses to generate adjusted discretionary expenses. Using the adjusted discretionary expenses and credits within the data, the system may be configured to compute an ability-to-pay score for the borrower. The system may generate a report including the ability-to-pay score for the borrower and may transmit the report to the requester that issued the query.