Enhancement of audit quality control using accounting fraud prediction model

Starting from July 2016, Ernst & Young ShinNihon LLC (EY ShinNihon), a member firm of EY, will implement a framework to predict future accounting fraud and further enhance the quality control of accounting audits. EY ShinNihon will also collaborate with Mr. Akinobu Shuto, Associate Professor of the Graduate School of Economics at the University of Tokyo, to improve the accuracy of their accounting fraud prediction model.

The accounting fraud prediction model is a tool to predict future material misstatements or potential restatements of annual securities reports by comparing data against the characteristics of past financial statements containing material misstatements. The model is built with the use of machine learning technology based on corporate information, mainly financial statements data, of publicly traded non-financial companies from the past five years. Going forward, with the cooperation of Associate Professor Shuto, a leading expert in research on the prediction of accounting fraud, EY ShinNihon will work to improve the accuracy of the model by incorporating inputs such as rules of thumb based on the experience of accounting auditors.

The risk values statistically generated by the accounting fraud prediction model will be shared with audit teams and utilized to identify risks of material misstatements in the accounting audit of publicly traded and other companies, enabling the performance of thorough audits. This information will also be used in risk analysis for the acceptance and continuance of engagements. With all these efforts, EY ShinNihon will strive to increase the sophistication of its quality control.

Conceptual image of quality control using the accounting fraud prediction model

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