چکیده مقاله
One of the most important goals of an independent audit is to discover and identify fraudulent financial reports By presenting a model that includes financial and non financial criteria for discovering distorted financial statements, this research succeeded in identifying distorted financial reports in companies listed on the Tehran Stock Exchange using data mining techniques The meaning of six variables from two financial and non financial dimensions and using a sample of companies accepted in Tehran Stock Exchange consisting of 1303 years companies including 21 fraudulent companies and 168 non fraudulent companies during the years 2011 to 2021 have been investigated and it has been analyzed using data mining techniques including decision tree, neural networks and Bayesian methods The research results show that the Bayesian method more accurately discovers distorted financial statements
نویسندگان
Hossein Alikhani Dehaghi
Islamic Azad University Department of Accounting, Dolatabad Branch Isfahan, Iran
شیوه ارجاع
Alikhani Dehaghi, Hossein,1401,Detecting fraudulent financial statements: a data mining approach,The 13th International Conference on New Researches in Management, Economics, Accounting and Banking
ارائهشده در
مجموعه مقالات سیزدهمین کنفرانس بین المللی پژوهش های نوین در مدیریت، اقتصاد، حسابداری و بانکداری19 اسفند 1401