Distributed Ledgers and Secure Multiparty Computation for Financial Reporting and Auditing - Cao, Sean Shun; Cong, Lin William; Yang, Baozhong (Management Science, 2025)
To understand the disruption and implications of distributed ledger technologies for financial reporting and auditing, we analyze firm misreporting, auditor monitoring and competition, and regulatory policy in a unified model. A federated blockchain for financial reporting and auditing can improve verification efficiency not only for transactions in private databases but also for cross-chain verifications through privacy-preserving computation protocols. Despite the potential benefit of blockchains, private incentives for firms and first-mover advantages for auditors can create inefficient under-adoption or partial adoption that favors larger auditors. Although a regulator can help coordinate the adoption of technology, endogenous choice of transaction partners by firms can still lead to adoption failure. Our model also provides an initial framework for further studies of the costs and implications of the use of distributed ledgers and secure multiparty computation in financial reporting, including the positive spillover to discretionary auditing and who should bear the cost of adoption. This paper was accepted by David Simchi-Levi, finance. Funding: The authors gratefully acknowledge research support from the FinTech Laboratory at J. Mack Robinson College of Business at Georgia State University, the Center for Research in Security Prices at the University of Chicago, the Ripple University Blockchain Research Initiative, and the Smith AI Initiative for Capital Market Research at the University of Maryland. Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2023.02577 .