行動計量学
Online ISSN : 1880-4705
Print ISSN : 0385-5481
ISSN-L : 0385-5481
原著
日本の上場企業における売上過大計上による不正会計の検知
—マハラノビス距離を用いた機械学習による方法—
東海林 和雄中村 亮介尾崎 幸謙
著者情報
ジャーナル フリー

2020 年 47 巻 2 号 p. 123-140

詳細
抄録

The purpose of this study is construction of the prediction model to discriminate incorrect accounting information. Two features of this research are to adopt methods of detecting auditing practices and to target for analysis that the accounting information which the sales are overestimated. Specifically, unlike in previous research, we approach to detect fraudulent means without uniform accounting phenomena for each fraudulent means. Furthermore, we applied accounting distortions and discomfort auditors feel as explanatory variables. This discomfort is measured by Mahalanobis distance. In the results of this analysis, the prediction model of machine learning that is adopted practical methods that detect incorrect accounting shows a high probability of fraud.

著者関連情報
© 2020 日本行動計量学会
前の記事 次の記事
feedback
Top