A Quantitative Cost-Benefit Analysis of Integrating Permissioned Enterprise Blockchain Networks in US Commercial Banking
- Authors
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Abiodun Okunola
Ladoke Akintola University TechnologyAuthor
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- Keywords:
- Permissioned Blockchain, Commercial Banking, Cost-Benefit Analysis, Settlement Latency, Fraud Mitigation, Enterprise Distributed Ledger Technology
- Abstract
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The United States commercial banking sector faces escalating operational costs, settlement inefficiencies, and fraud-related losses that challenge the sustainability of legacy financial infrastructure. While blockchain technology has emerged as a transformative force in financial services, a significant research gap exists in the quantitative evaluation of permissioned enterprise blockchain networks specifically within the US commercial banking context. This study conducts a comprehensive quantitative cost-benefit analysis of integrating Hyperledger Fabric-based permissioned blockchain networks across US commercial banking operations, examining operational overhead reduction, settlement latency improvement, and fraud-associated loss mitigation. Using quarterly data from 2010 to 2025 sourced from the Federal Reserve System's FRED database and synthetic transaction datasets validated against industry benchmarks, the research employs Autoregressive Distributed Lag (ARDL) modeling and comparative performance analysis. The findings demonstrate that permissioned blockchain integration yields a 60-80% reduction in per-transaction operational costs, settlement latency improvement from T+2 to near-instantaneous finality, and a 6.3% enhancement in fraud detection accuracy compared to conventional validation frameworks. These results provide empirical evidence supporting enterprise distributed ledger technology as a viable infrastructure investment for US commercial banks, with implications for regulatory policy, institutional strategy, and financial system resilience.
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- Published
- 07/15/2026
- Section
- Articles
- License
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Copyright (c) 2026 Abiodun Okunola (Author)

This work is licensed under a Creative Commons Attribution 4.0 International License.
