Quantum Virtualization for Scalable Fintech Workflows: Multi-Tenant qVMs in Quantum Cloud Environments

Abstract

As financial technology (FinTech) systems evolve toward increasingly sophisticated, data-intensive, and latency-sensitive computational pipelines, quantum computing is emerging as a transformative enabler for optimization, security, and high-performance analytics. However, practical deployment remains limited by scarce quantum hardware, noisy environments, and the need to support heterogeneous users with diverse workloads. This study introduces a quantum virtualization framework that leverages multi-tenant quantum virtual machines (qVMs) to provide scalable, flexible, and secure access to quantum resources in cloud-based environments. The proposed architecture virtualizes quantum hardware through layered abstraction, dynamic qubit allocation, and workload-adaptive circuit scheduling to support concurrent FinTech workloads such as portfolio optimization, fraud detection, blockchain verification, and quantum-safe cryptographic operations. Benchmark simulations demonstrate that qVM-enabled multi-tenancy improves hardware utilization by up to 40%, reduces queueing latency, and enables isolation between concurrent clients without compromising quantum circuit fidelity. These findings highlight the potential of quantum virtualization to accelerate the industrial adoption of quantum computing in the FinTech sector, enabling scalable, secure, and cost-efficient quantum-as-a-service (QaaS) ecosystems.