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

TL;DR

This paper formulates and addresses the challenge of fairly redistributing digital payment transactions among apps to comply with regulatory caps, proposing scalable heuristics that balance efficiency and fairness.

Contribution

It formalizes the transaction redistribution problem as an NP-Complete flow problem and introduces the DTAS heuristic for practical, near-optimal solutions.

Findings

DTAS achieves solutions close to optimal within seconds

The problem is NP-Complete, indicating computational complexity

Heuristics effectively enforce transaction caps fairly and efficiently

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.