Fair Distribution of Digital Payments: Balancing Transaction Flows for Regulatory Compliance

2025-11-30

arXiv.org

AI Summary

This study addresses the problem of fairly redistributing payment traffic under the regulatory constraint that no single UPI application may handle more than 30% of total transaction volume, modeling it as a Minimum Edge Activation Flow (MEAF) problem on a bipartite graph to minimize the number of additional payment applications users must install. The work formally defines this regulation-driven problem for the first time and proves its NP-completeness. To solve it efficiently, the authors propose a scalable two-stage decoupled allocation strategy (DTAS) that combines integer linear programming with heuristic methods, leveraging structural properties of traffic flows and capacity reuse mechanisms. Experimental results demonstrate that DTAS generates near-optimal, high-quality solutions within seconds on large-scale semi-synthetic networks, substantially improving regulatory compliance efficiency.

Abstract

The concentration of digital payment transactions in just two UPI apps like PhonePe and Google Pay has raised concerns of duopoly in India s digital financial ecosystem. To address this, the National Payments Corporation of India (NPCI) has mandated that no single UPI app should exceed 30 percent of total transaction volume. Enforcing this cap, however, poses a significant computational challenge: how to redistribute user transactions across apps without causing widespread user inconvenience while maintaining capacity limits? In this paper, we formalize this problem as the Minimum Edge Activation Flow (MEAF) problem on a bipartite network of users and apps, where activating an edge corresponds to a new app installation. The objective is to ensure a feasible flow respecting app capacities while minimizing additional activations. We further prove that Minimum Edge Activation Flow is NP-Complete. To address the computational challenge, we propose scalable heuristics, named Decoupled Two-Stage Allocation Strategy (DTAS), that exploit flow structure and capacity reuse. Experiments on large semi-synthetic transaction network data show that DTAS finds solutions close to the optimal ILP within seconds, offering a fast and practical way to enforce transaction caps fairly and efficiently.

Problem

• digital payments
• transaction flow balancing
• regulatory compliance
• capacity constraints
• user inconvenience

Innovation

• Minimum Edge Activation Flow
• Bipartite Flow Network
• Scalable Heuristics
• Transaction Cap Enforcement
• Decoupled Two-Stage Allocation