Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/241713 
Year of Publication: 
2021
Citation: 
[Journal:] Journal of Open Innovation: Technology, Market, and Complexity [ISSN:] 2199-8531 [Volume:] 7 [Issue:] 2 [Publisher:] MDPI [Place:] Basel [Year:] 2021 [Pages:] 1-20
Publisher: 
MDPI, Basel
Abstract: 
Identifying fraudulent financial statements is important in open innovation to help users analyze financial statements and make investment decisions. It also helps users be aware of the occurrence of fraud in financial statements by considering the associated pattern. This study aimed to find associated fraud patterns in financial ratios from financial statements on the Stock Exchange of Thailand using discretization of the financial ratios and frequent pattern growth (FP-Growth) association rule mining to find associated patterns. We found nine associated patterns in financial ratios related to fraudulent financial statements. This study is different from others that have analyzed the occurrence of fraud by using mathematics for each financial item. Moreover, this study discovered six financial items related to fraud: (1) gross profit, (2) primary business income, (3) ratio of primary business income to total assets, (4) ratio of capitals and reserves to total debt, (5) ratio of long-term debt to total capital and reserves, and (6) ratio of accounts receivable to primary business income. The three other financial items that were different from other studies to be focused on were (1) ratio of gross profit to primary business profit, (2) ratio of long-term debt to total assets, and (3) total assets.
Subjects: 
detecting fraudulent patterns
financial statement
association rule mining
discretization
innovation
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

Files in This Item:
File
Size
766.22 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.