Dynamic Reward Category Ranking for Adaptive Point Allocation
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Solution Overview
Problem
Existing loyalty program systems assign fixed rewards categories that do not adjust based on individual spending patterns, leading to inefficiencies and the need for multiple credit cards to maximize rewards, resulting in redundant backend systems and resource waste.
Innovation Solution
A system that monitors and dynamically adjusts point allocations based on periodic rankings of transaction categories using a single financial vehicle, optimizing point assignments by capturing changes in spending trends and eliminating the need for multiple cards.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If fixed reward categories are assigned to all cardholders, then backend systems are simple and easy to manage, but the system cannot adapt to individual spending patterns and requires multiple credit cards to maximize rewards
Solution Approach 1:
The patent implements dynamic point allocation where the system automatically adjusts reward categories and point values based on each cardholder's spending patterns. The backend system monitors transactions in real-time and dynamically reconfigures reward structures without requiring manual intervention or multiple static card programs, thus achieving adaptability while maintaining manageable complexity.
Solution Approach 2:
The system changes the parameters of point allocation by adjusting the number of points awarded to different transaction categories based on individual cardholder behavior. Instead of fixed parameters, the system dynamically modifies point values and category assignments to optimize rewards for each user's specific spending patterns, eliminating the need for multiple cards with different fixed structures.
2Productivity
If multiple credit cards are issued with different fixed reward categories, then consumers can maximize rewards for different purchase types, but system resources are wasted through redundant backend systems
Solution Approach 1:
The patent creates a universal backend system that serves all cardholders with a single multi-functional platform. This system can dynamically configure and manage multiple reward structures within one infrastructure, allowing it to optimize rewards for different spending patterns without requiring separate backend systems for each card type, thus eliminating resource waste while maintaining productivity.
Solution Approach 2:
The system merges multiple static reward programs into a single dynamic program. By combining the functionality of what would traditionally require multiple separate credit cards with fixed categories into one card with adaptive rewards, the system consolidates backend processing requirements and eliminates redundant infrastructure while preserving the ability to optimize rewards across different purchase types.
3Productivity
If statically programmed backend systems are used for each reward category, then reward assignment is simple and fast, but the system cannot capture changes in spending trends
Solution Approach 1:
The patent implements a feedback mechanism where the backend system continuously monitors cardholder transactions and uses this information to automatically adjust reward categories and point allocations. The system processes spending data in real-time, identifies trends, and dynamically reconfigures reward structures accordingly, maintaining fast point assignment while adapting to changing spending patterns without requiring static programming for each scenario.
Data Source
AI summary
In one aspect of the present disclosure, a device includes one or more memories having computer-readable instructions stored therein and one or more processors. The one or more processors are configured to execute the computer-readable instructions to receive, over a period of time, information regarding transactions conducted in association with a user account; identify a category associated with one or more of the transactions based on the information, wherein identifying yields a number of categories; generate a ranking of the categories based on a transaction parameter; assign a different number of points to corresponding transactions in one or more of the categories based on the ranking, with a highest number of points assigned to the corresponding transactions in at least one category with highest ranking; and apply the corresponding number of points to the user account.