Behavior Engine for Real-Time Purchase Incentive Feedback
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Solution Overview
Problem
Existing fund disbursement programs lack effective mechanisms to incentivize positive purchase behaviors and discourage negative ones among participants, as they rely on traditional payment systems without real-time analysis and feedback mechanisms.
Innovation Solution
A system and method that analyze transaction data from enrolled payment accounts to determine purchase behavior scores, using classification criteria and behavior parameters set by fund providers, and provide responses such as rewards or remedial actions based on these scores to influence participants' purchasing habits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional payment systems are used without real-time analysis, then system simplicity is maintained, but the ability to incentivize positive purchase behaviors and discourage negative ones is lost
Solution Approach 1:
The system implements real-time feedback by continuously monitoring transaction data, calculating behavior scores, and providing immediate responses to participants. The behavior engine analyzes spending patterns and communicates back to participants through the payment account system, creating a closed-loop feedback mechanism that enables dynamic behavior modification without requiring complete system redesign
Solution Approach 2:
The patent introduces a behavior engine as an intermediary component between the traditional payment system and participants. This intermediary layer processes transaction data, applies classification criteria and behavior parameters, and generates responses without disrupting the core payment infrastructure, thus adding adaptability while containing complexity growth
2Measurement precision
If real-time transaction analysis is implemented, then purchase behavior can be effectively monitored and responded to, but processing time and computational resources increase
Solution Approach 1:
The system performs preliminary actions by pre-establishing classification criteria and behavior parameters before transaction analysis begins. These rules are configured in advance, allowing the behavior engine to quickly match transactions against predetermined criteria rather than performing complex analysis in real-time, thus maintaining measurement precision while reducing processing time
Solution Approach 2:
The patent segments the transaction analysis process into distinct components: transaction data collection, classification against predefined criteria, behavior parameter application, and response generation. This segmentation allows each component to be optimized independently, improving overall processing efficiency while maintaining analytical accuracy
Data Source
AI summary
Systems and methods are provided for use in responding to purchase behaviors of participants of disbursement programs. One exemplary method includes accessing transaction data associated with a payment account, where the payment account is associated with a participant and a disbursement program and where the transaction data is representative of a number of transactions made to the payment account. The method also includes identifying, for each of the transactions, a classification based on at least one classification criteria and calculating a behavior score based on at least one behavior parameter and the classification of at least one of the transactions. And, when the behavior score satisfies a remedial threshold, causing a remedial response to be provided to the participant, whereby the remedial response indicates to the participant to alter one or more purchase behaviors.