Dynamic Installment Configuration via Machine Learning

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Solution Overview

Problem

Existing systems lack efficient methods to determine and configure conditions and incentives associated with installment options, leading to suboptimal user experiences and financial outcomes.

Innovation Solution

A computer-implemented method and system that identifies installment options and determines conditions and incentives using machine-learning models applied to user profile data, allowing for real-time monitoring and adjustment of conditions and incentives.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If traditional installment options are used without personalized conditions and incentives, then the system complexity is low, but user satisfaction and financial outcomes are suboptimal

Engineering Contradiction:

Improveuser satisfactionVSAvoidsystem complexity

Core Design Contradiction:

Ease of operationVSDevice complexity

Solution Approach 1:

The system dynamically adjusts installment parameters (interest rates, payment schedules, conditions) based on machine-learning models analyzing user profile data. This transforms static installment options into adaptive, personalized configurations that optimize user satisfaction while managing system complexity through automated parameter determination.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The machine-learning models automatically determine conditions and incentives based on user profile data without requiring manual configuration. The system self-adjusts installment options based on analyzed user behavior and characteristics, reducing the need for complex manual setup while improving personalization.

Inventive Principle:

Principle #25Self-service

2Productivity

If multiple conditions and incentives are configured for installment options, then user engagement and financial management improve, but the difficulty of detecting and measuring conditions increases

Engineering Contradiction:

Improvefinancial management effectivenessVSAvoidcondition monitoring complexity

Core Design Contradiction:

ProductivityVSDifficulty of detecting and measuring

Solution Approach 1:

The system continuously monitors user actions against configured conditions and provides real-time feedback by determining whether conditions are satisfied. This feedback mechanism automatically triggers incentive processing when conditions are met, simplifying the measurement of complex conditions through automated verification of user actions.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

Manual monitoring and measurement of conditions is replaced by automated machine-learning models and computer-implemented methods that detect user actions and determine condition satisfaction. This substitution reduces the operational complexity of measuring multiple conditions while improving financial management effectiveness.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Measurement precision

If real-time monitoring of user actions is implemented, then condition satisfaction is accurately determined, but the use of energy and computational resources increases

Engineering Contradiction:

Improvecondition satisfaction accuracyVSAvoidcomputational resource consumption

Core Design Contradiction:

Measurement precisionVSUse of energy by moving object

Solution Approach 1:

The system monitors only the specific user actions relevant to condition satisfaction rather than all possible actions. By focusing computational resources on detecting only those actions that trigger condition evaluation, the system achieves accurate condition satisfaction determination while minimizing unnecessary computational energy consumption.

Inventive Principle:

Principle #16Partial or excessive action

Data Source

PatentUS20250166001A1Determining conditions and incentives associated with installment options

Publication Date: 2025.05.22 SYNCHRONY BANK

AI summary

Disclosed embodiments may provide techniques for configuring conditions and incentives associated with installment options. A computer-implemented method can include identifying an installment option and an alternative installment option associated with an account. In some instances, the alternative installment option is associated with an incentive, which can be applied when one or more conditions associated with the account are satisfied. The computer-implemented method can also include receiving a user selection of the alternative installment option. The computer-implemented method can also include detecting in real-time a set of actions performed for the account, in which the set of actions can be associated with the one or more conditions. The computer-implemented method can also include determining in real-time that the one or more conditions have been satisfied based on the set of actions. The computer-implemented method can also include processing the incentive associated with the alternative installment option.