Geofence-Based Transaction Processing for Local Merchant Incentives
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Solution Overview
Problem
The existing electronic transaction processing systems burden small merchants with higher interchange fees and incentivize consumers to favor big box retailers over local businesses, due to fee structures and rewards programs that favor national chains, leading to a decline in support for small and local merchants.
Innovation Solution
Implementing systems and methods that process electronic transactions based on physical geography, allowing merchants to generate incentives by matching consumer geofences with merchant geofences, enabling differential transaction processing and rewards for local purchases.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional interchange fee structures are used, then credit card networks and issuers receive adequate funding, but small merchants are burdened with high fees and consumers are incentivized to favor big box retailers
Solution Approach 1:
The system applies different transaction processing rules and fee structures based on the geographical location of the merchant. Local merchants within the consumer's geofence receive preferential treatment with reduced fees or incentives, while non-local merchants are processed under standard conditions. This resolves the contradiction by creating local quality variations in fee structures that protect small merchants while maintaining overall system reliability.
Solution Approach 2:
The system dynamically changes the interchange fee parameter based on the consumer-merchant geographical relationship. When a consumer shops at a local merchant (within geofence), the fee parameter is adjusted to be more favorable compared to shopping at non-local merchants. This parameter change resolves the contradiction by making fees adaptive rather than static, protecting small local merchants while maintaining funding for the payment network.
2Ease of operation
If credit card issuers implement rewards programs for national chains, then consumers are incentivized to shop at big box retailers, but local small merchants lose consumer support
Solution Approach 1:
The system creates geographically-specific rewards by comparing the consumer's location (via geofence) with the merchant's location. Consumers receive rewards or incentives specifically when shopping at local merchants within their geofence, while standard rewards apply for non-local merchants. This resolves the contradiction by providing local quality in rewards distribution that supports small merchants while maintaining ease of operation through automated geolocation-based differentiation.
Solution Approach 2:
The system pre-establishes geofences for merchants and pre-configures incentive rules before transactions occur. When a consumer enters a merchant's geofence, the incentive is automatically applied without requiring separate rewards program enrollment or manual configuration. This preliminary action resolves the contradiction by making local merchant support as convenient as national chain rewards, eliminating the barrier that previously drove consumers to big box retailers.
3Device complexity
If uniform transaction processing is applied to all merchants, then system simplicity is maintained, but consumers have incentive to travel to large national chains instead of local merchants
Solution Approach 1:
The system introduces geographically-based differentiation in transaction processing by comparing consumer and merchant geofences. Transactions at local merchants (within geofence) are processed with special incentives, while transactions at non-local merchants follow standard processing. This resolves the contradiction by applying local quality to transaction processing, encouraging consumers to shop locally without significantly increasing system complexity through the use of automated geolocation technology.
Solution Approach 2:
The system uses geofence technology as an intermediary to automatically determine whether a merchant is local to the consumer. This intermediary component handles the complexity of geographical matching, allowing the rest of the transaction processing system to remain relatively simple while still enabling differentiated treatment. The geofence intermediary resolves the contradiction by automating the complexity management, reducing consumer travel to national chains without burdening the overall system.
Data Source
AI summary
Methods are disclosed for processing electronic transactions between a merchant and a consumer based on physical geography. A method includes receiving payment data associated with a consumer payment card; transmitting the payment data, over a network, to a third party; receiving, over the network, information for determining whether a geofence associated with the merchant matches a geofence associated with the consumer; and processing a transaction with the consumer based on whether the consumer geofence ID matches a geofence ID associated with the merchant. Systems for processing electronic transactions between a merchant and a consumer based on physical geography are also disclosed.