Since 2009, blockchain has served as a potentially transformative information technology expected to be as revolutionary as the Internet. Originally developed as a methodology to record cryptocurrency transactions, blockchain's functionality has evolved into a large number of applications, such as banking, financial markets, insurance, voting systems, leasing contracts, and government service. Despite such advancements, the application of blockchain to accounting and assurance remains under-explored. This paper aims to provide an initial discussion on how blockchain could enable a real-time, verifiable, and transparent accounting ecosystem. Additionally, blockchain has the potential to transform current auditing practices, resulting in a more precise and timely automatic assurance system.

SYNOPSIS This paper discusses an overall framework of Big Data in accounting, setting the stage for the ensuing collection of essays that presents the ongoing evolution of corporate data into Big Data, ranging from the structured data contained in modern ERPs to loosely connected unstructured and semi-structured information from the environment. These essays focus on the sources, uses, and challenges of Big Data in accounting (measurement) and auditing (assurance). They consider the changing nature of accounting records and the incorporation of nontraditional sources of data into the accounting and auditing domains, as well as the need for changes in the accounting and auditing standards, and the new opportunities for audit analytics enabled by Big Data. Additionally, the papers discuss the interaction of Big Data and traditional sources of data, as well as Big Data's impact on audit judgment and behavioral research. Both accounting academics and accounting practitioners will benefit from learning about the significant potential benefits of Big Data and the inevitable challenges and obstacles in the way of its utilization. Advanced accounting students would also benefit from exposure to these emerging issues to enhance their future career development.

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SUMMARY Modern audit engagements often involve examination of clients that are using Big Data and analytics to remain competitive and relevant in today's business environment. Client systems now are integrated with the cloud, the Internet of Things, and external data sources such as social media. Furthermore, many engagement clients are now integrating this Big Data with new and complex business analytical approaches to generate intelligence for decision making. This scenario provides almost limitless opportunities and the urgency for the external auditor to utilize advanced analytics. This paper first positions the need for the external audit profession to move toward Big Data and audit analytics. It then reviews the regulations regarding audit evidence and analytical procedures, in contrast to the emerging environment of Big Data and advanced analytics. In a Big Data environment, the audit profession has the potential to undertake more advanced predictive and prescriptive-oriented analytics. The next section proposes and discusses six key research questions and ideas, followed with emphasis on the research needs of quantification of measurement and reporting. This paper provides a synthesis and review of the concerns facing the audit community with the growing use of Big Data and complex analytics by their clients. It contributes to the literature by expanding upon these emerging concerns and providing opportunities for future research.