Driving a More Prosperous Future
Distributed Ledgers and Secure Multi-Party Computation for Financial Reporting and Auditing
August 2024
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.
Sean Cao, Associate Professor (with tenure), Robert H. Smith School of Business, University of Maryland, United States of America
Applied AI for finance and accounting: Alternative data and opportunities
February 2024
Big data and artificial intelligence (AI) have transformed the finance industry by altering the way data and information are generated, processed, and incorporated into decision-making processes. Data and information have emerged as a new class of assets, facilitating efficient contracting and risk-sharing among corporate stakeholders. Researchers have also increasingly embraced machine learning and AI analytics tools, which enable them to exploit empirical evidence to an extent that far surpasses traditional methodologies. In this review article, prepared for a special issue on Artificial Intelligence (AI) and Finance in the Pacific-Basin Finance Journal, we aim to provide a summary of the evolving landscape of AI applications in finance and accounting research and project future avenues of exploration. Given the burgeoning mass of literature in this field, it would be unproductive to attempt an exhaustive catalogue of these studies. Instead, our goal is to offer a structured framework for categorizing current research and guiding future studies. We stress the importance of blending financial domain expertise with state-of-the-art data analytics skills. This fusion is essential for researchers and professionals to harness the opportunities offered by data and analytical tools to better comprehend and influence our financial system.
Sean Cao, Associate Professor (with tenure), Robert H. Smith School of Business, University of Maryland, United States of America