Detecting and Analyzing Fraudulent Patterns of Financial Statement for Open Innovation Using Discretization and Association Rule Mining

Sawangarreerak, Siriporn; Thanathamathee, Putthiporn

doi:10.3390/joitmc7020128

Cited by 8 publications

(10 citation statements)

References 26 publications

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“…In order to guarantee businesses' continuity and growth, it is vital to pledge efficient corporate management. However, due to fraud, several businesses fail [31], causing economic, social, and environmental calamities [6]. Considering the harmful effects of fraud, it is also important to notice that firms' investors are also harmed by fraud, which will have repercussions in the loss of confidence of potential investors [32].…”

Section: Shareholder Value Creationmentioning

confidence: 99%

Effect of Computer Assisted Audit Tools on Corporate Sustainability

Samagaio

Diogo

2022

Sustainability

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The literature is fertile in studies that examine the determinants of internal and external auditors’ adoption of computer-assisted audit tools and techniques (CAATs), often ignoring their practical effects on audit quality and organizational performance. This study provides novel evidence on the type of CAATs used by internal auditors, tests the effect of their adoption on corporate sustainability, and explores the moderating effect of organizational characteristics. In this paper, we used data from Portuguese internal auditors collected through a survey, whose research hypotheses were analyzed by the partial least squares–structural equation modeling technique. We found that internal auditors use CAATs moderately in the exercise of their tasks. The results of our study show that there is a strong and positive effect of the use of CAATs by internal auditors on fraud detection in the purchase-to-pay business process, and that the intensity of this relationship is not influenced by the type and size of the entity. This study complements previous research and provides support to practitioners’ decisions that can boost the use of CAATs in internal auditing to make organizations more sustainable.

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Section: Shareholder Value Creationmentioning

confidence: 99%

Effect of Computer Assisted Audit Tools on Corporate Sustainability

Samagaio

Diogo

2022

Sustainability

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“…As a well-established data mining process, ARM is one of the techniques involved in data mining to discover interesting knowledge, such as patterns, changes, associations, and significant structures from many databases [18]. The ARM techniques are employed to model dependencies between dataset items.…”

Section: The Arm and Its Importancementioning

confidence: 99%

“…For example, Sawangarreerak and Thanathamathee [18] investigated the fraud pattern associations with financial ratios based on the Stock Exchange of Thailand financial statements with frequent pattern growth (FP-Growth) ARM. Resultantly, nine significant fraudulent financial statement patterns proved useful for investors and users in decision-making.…”

Section: The Arm and Its Importancementioning

confidence: 99%

Association Rules Mining for Hospital Readmission: A Case Study

et al. 2021

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As an indicator of healthcare quality and performance, hospital readmission incurs major costs for healthcare systems worldwide. Understanding the relationships between readmission factors, such as input features and readmission length, is challenging following intricate hospital readmission procedures. This study discovered the significant correlation between potential readmission factors (threshold of various settings for readmission length) and basic demographic variables. Association rule mining (ARM), particularly the Apriori algorithm, was utilised to extract the hidden input variable patterns and relationships among admitted patients by generating supervised learning rules. The mined rules were categorised into two outcomes to comprehend readmission data; (i) the rules associated with various readmission length and (ii) several expert-validated variables related to basic demographics (gender, race, and age group). The extracted rules proved useful to facilitate decision-making and resource preparation to minimise patient readmission.

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“…Prevare u poslovanju predstavljaju pitanje ozbiljne društvene i ekonomske zabrinutosti. Jedan od problema koji dovodi do neuspešnog poslovanja i izaziva bankrot je prevara koja predstavlja namerni postupak pojedinaca ili grupe, uključujuć i menadžere preduzeć a koji imaju odgovornost u upravljaju zaposlenima ili treć im licima, ali se ponašaju prevarno radi nezakonitog ili nepravednog sticanja prednosti u poslovanju [6]. Menadžeri moć i autoritet mogu da koriste za realizaciju interesa akcionara, ali mogu i sprečiti zloupotrebu i prevaru [7].…”

Section: Uvodunclassified

“…Računovodstvena prevara je pogrešno prikazivanje informacija u fi nansijskim izveštajima i ima dve vrste: (1) pripremu prevarnih/lažnih fi nansijskih izveštaja i (2) neprikladna/nepropisna upotreba imovine [6]. Finansijski izveštaji preduzeća rezimiraju ekonomske posledice njegovih poslovnih aktivnosti, a koje su brojne, tako da ih nije moguće individualno prikazati eksternim stranama [18, p. 17].…”

Section: Pregled Literatureunclassified

Using Beneish M-Score and Altman Z-Score models to detect financial fraud and company failure

Knežević¹,

Špiler²,

Milašinović³

et al. 2021

Tekstilna industrija

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Bankruptcy is a risk that any company can face, regardless of its size. The importance of predicting a company's bankruptcy for years before its development is enormous, and it is important for financial sustainability. Financial reporting is an important platform for making financial decisions of investors and creditors. In recent years, the frequency of false financial reporting by firms has increased and there are concerns about investors' confidence in capital market. Academics and industry experts adopt a variety of risk management techniques to detect fraudulent financial reporting. A case study was applied in this paper. Based on publicly available financial data (disclosed financial statements) of a domestic textile company for the period 2017-2020, whose shares are listed on the stock exchange, a survey was conducted based on the application of Altman's Z-Score model and Beneish M-Score model. Financial distress is an important criterion to monitor when assessing the likelihood of fraud reporting. When a company is operating poorly, there is a greater motivation to engage in fraudulent financial reporting. The findings show that the results differ according to the applied method in terms of identifying the possibility of bankruptcy and the possibility of fraud in the financial statements of the observed company. The results of the study can be important to investors, auditors, regulators, bankers, tax and other government bodies.

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Detecting and Analyzing Fraudulent Patterns of Financial Statement for Open Innovation Using Discretization and Association Rule Mining

Cited by 8 publications

References 26 publications

Effect of Computer Assisted Audit Tools on Corporate Sustainability

Effect of Computer Assisted Audit Tools on Corporate Sustainability

Association Rules Mining for Hospital Readmission: A Case Study

Using Beneish M-Score and Altman Z-Score models to detect financial fraud and company failure

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