The use of blockchain technology to automate verification processes has the potential transform the financial auditing sector by cutting costs, boosting efficiency, and enhancing data privacy, according to recent research.
Smith AI Initiative for Capital Market Research director and co-founder and Smith School associate professor Sean Cao spearheaded the study examining the potential of “permissioned blockchains” in financial reporting and auditing and aid in partnerships without “sacrificing” data privacy of clients.
Cao co-authored the research titled “Distributed Ledgers and Secure Multiparty Computation for Financial Reporting and Auditing” along with Lin William Cong of Cornell University and Baozhong Yang of Georgia State University.
The study found that blockchain-based systems can automate the verification of financial transactions, reducing the need for lengthy manual checks.
One of the primary hurdles in auditing is claimed to be the time-consuming nature of transaction verification, compounded by privacy concerns and often low response rates from transaction partners.
The research suggested that a blockchain-based distributed ledger system could overcome these obstacles by automatically verifying all receipts efficiently and cost-effectively.
While blockchain cannot replace transactions that require discretion, Cao said that the adoption of this technology could lead to a 70% cost saving for auditing firms.
However, for the system to have a global impact, widespread adoption is necessary. The research team has developed a mathematical model to align the incentives of auditors, clients, and regulators, aiming to “maximise the unity of the three parties,” Cao added.
Cao said: Cao said: “A lot of auditing firms want to use blockchain and they want to apply technology. I wanted to build a use case for blockchain that works for auditing firms.”
This is not Cao’s first foray into the design of such systems. His earlier work, “Architecture for Auditing Automation and Trust Building in Public Markets,” was published in the IEEE journal Computer in 2020.
