Multi-Category Debt Strategy Optimization via Surrogate Modeling
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Solution Overview
Problem
Existing digital services for debt management are one-dimensional, often recommending only one type of product and failing to consider individual needs and constraints, leading to suboptimal debt management strategies.
Innovation Solution
The development of optimized debt service strategy solutions utilizing products across multiple categories, leveraging trained surrogate models to estimate parameters and an optimizer model to determine the most effective strategy adhering to user-defined constraints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If existing digital services recommend only one type of product for debt management, then the service complexity is reduced and ease of operation is improved, but the adaptability to individual financial situations deteriorates and the quality of debt management advice worsens
Solution Approach 1:
The patent segments the debt management solution into multiple product categories (balance transfer cards, personal loans, credit card consolidation, student loan refinancing) rather than recommending a single product type. This segmentation allows the system to evaluate different product types independently and select the most appropriate category based on individual user circumstances, thereby improving adaptability while maintaining operational simplicity through automated comparison and recommendation.
Solution Approach 2:
The system implements multi-functionality by creating a unified debt management platform that evaluates and recommends across multiple product categories simultaneously. The optimizer model serves multiple functions: it assesses user financial situations, compares various debt relief products, considers user constraints (monthly budget, credit score, debt amount), and generates personalized recommendations. This universal approach enables a single service to adapt to diverse individual needs across different debt scenarios.
2Device complexity
If existing digital services analyze only base level financial information, then the data processing complexity is reduced, but the measurement precision of individual financial situations deteriorates
Solution Approach 1:
The system performs preliminary actions by collecting and organizing comprehensive user financial information before generating recommendations. It gathers detailed data including monthly budget constraints, credit score, existing debt amounts, interest rates, and payment histories. This preliminary data collection and structuring enables subsequent precise analysis without requiring complex real-time processing during the recommendation phase, thus balancing measurement precision with manageable data processing complexity.
Solution Approach 2:
The patent introduces an optimizer model as an intermediary between raw user financial data and recommendation outputs. This intermediary component processes comprehensive user information (including constrained monthly budget, credit score, debt characteristics) and translates it into evaluated debt service strategies. The optimizer model acts as a mediator that handles the complexity of analyzing multiple financial parameters simultaneously, enabling precise measurement of individual financial situations while keeping the overall system architecture manageable through modular processing.
3Ease of operation
If existing services fail to consider user constraints such as monthly budget, then the service operation is simplified, but the reliability of debt management advice deteriorates
Solution Approach 1:
The system applies local quality by incorporating specific user constraints (monthly budget, credit score requirements, debt amount thresholds) into the recommendation process for each individual user. Rather than applying a uniform recommendation approach, the optimizer model evaluates user-specific constraints and tailors the debt management advice accordingly. This ensures that recommendations are locally optimized for each user's financial situation, improving reliability while maintaining operational simplicity through automated constraint-based filtering and selection.
Data Source
AI summary
Systems, apparatuses, methods, and computer program products are disclosed for developing an optimized debt service strategy solution utilizing products across multiple product categories. An example method includes receiving, by communications hardware, a user dataset. The example method also includes processing, by surrogate modeling circuitry, the user dataset using a plurality of surrogate models. The example method also includes generating, by the surrogate modeling circuitry and based on the processing of the user dataset, a parameter estimation set. The example method also includes determining, by optimizer modeling circuitry and based on the user dataset and the parameter estimation set, at least one debt service strategy solution comprising at least one product of a first product category from a plurality of products associated with multiple product categories. The example method also includes causing presentation, by communications hardware, of the at least one debt service strategy solution.