Combined Algorithm for Detection of Manipulation in Financial Statements

Pustylnick, Igor

doi:10.2139/ssrn.1422693

Cited by 17 publications

(16 citation statements)

References 12 publications

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“…99;ISA No. 240;Perols and Lougee, 2011;Franceschetti and Koschtial, 2012;Sarwoko and Agoes, 2014 (Pustylnick, 2011;Fanceschetti and Koschtial, 2012;Nia, 2015;Mahama, 2015 (Pustylnick, 2011;Nia, 2015;Mahama, 2015) . Lennox et al, 2014;Ettredge et al, 2014;Noor et al, 2015;Ching et al, 2015) ‫ج (Johnstone et al, 2014;Kwon et al, 2014;Ball et al, 2015;Omid, 2015) (Saladrigues and Grano, 2014;Wudu, 2014;Tyokoso and Tsegba, 2015;Birjandi et al,2015;Caskey and Laux, 2015) .…”

Section: ‫البعض‬ ‫اتفق‬ ‫فقد‬ ‫اجعة‬ ‫المر‬ ‫جودة‬ ‫قياس‬ ‫كيفية‬ ‫بشmentioning

confidence: 99%

دراسة واختبار العلاقة بین جودة المراجعة الخارجیة وخلو القوائم المالیة للشرکات المقیدة بالبورصة المصریة من الغش

على¹

2017

مجلة الاسکندریة للبحوث المحاسبیة

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 1 -‫ال‬ ‫مقدمة:‬ ‫نتيجة‬ ‫أدت‬ ‫التي‬ ‫و‬ ‫ة،‬ ‫األخير‬ ‫اآلونة‬ ‫في‬ ‫المالية‬ ‫ائم‬ ‫بالقو‬ ‫الغش‬ ‫حاالت‬ ‫ار‬ ‫لتكر‬ ‫سوق‬ ‫في‬ ‫المصالح‬ ‫أصحاب‬ ‫ثقة‬ ‫وفقدان‬ ‫الدول،‬ ‫بعض‬ ‫فى‬ ‫الشركات‬ ‫من‬ ‫العديد‬ ‫النييار‬ ‫المال،‬ ‫أس‬ ‫ر‬ ‫الحاجة‬ ‫ادت‬ ‫ز‬ ‫عممية‬ ‫اىة‬ ‫ونز‬ ‫سالمة‬ ‫لضمان‬ ‫فاعمة‬ ‫آلية‬ ‫عمى‬ ‫لالعتماد‬ ‫عمى‬ ‫الثقة‬ ‫إضفاء‬ ‫يمكن‬ ‫حتى‬ ‫المالية،‬ ‫ائم‬ ‫القو‬ ‫إعداد‬ ‫يادة‬ ‫وز‬ ‫معمومات‬ ‫من‬ ‫تحتويو‬ ‫ما‬ ‫عمييا‬ ‫االعتماد‬ ‫إمكانية‬ (Okolie and Izedonmi, 2014; Rahimi and Amini, 2015; Goodwin and Wu, 2015) ، ‫الذي‬ ‫األمر‬ ‫وىو‬ ‫من‬ ‫تأييده‬ ‫تم‬ ‫(الصيرفي،‬ ‫اسات‬ ‫الدر‬ ‫بعض‬ ‫جانب‬ 2015 ‫المطيف،‬ ‫عبد‬ ، 2015 ‫األعمال‬ ‫بيئة‬ ‫في‬ ) ‫ية.‬ ‫المصر‬ ‫المينية‬ ‫الممارسة‬ ‫و‬

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Section: ‫البعض‬ ‫اتفق‬ ‫فقد‬ ‫اجعة‬ ‫المر‬ ‫جودة‬ ‫قياس‬ ‫كيفية‬ ‫بشmentioning

confidence: 99%

دراسة واختبار العلاقة بین جودة المراجعة الخارجیة وخلو القوائم المالیة للشرکات المقیدة بالبورصة المصریة من الغش

على¹

2017

مجلة الاسکندریة للبحوث المحاسبیة

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“…Particularly, applicability of Altman Z score is reflected in other research studies. According to Pustylnick (2009), Altman Z score clearly shows the financial position of the firm in terms of its robustness and solvency. Nandi and Choudhary (2011) conducted a research with six years' data of Indian Banks and used Altman Z score model to design an internal credit rating by the banks so as to predict their future defaults.…”

Section: Literature Reviewmentioning

confidence: 99%

Prediction of Financial Distress of Non-Bank Financial Institutions of Bangladesh using Altman’s Z Score Model

Hamid¹,

Akter²,

Rab³

2016

IJBM

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The Non-Bank Financial Institutions (NBFIs) comprise a rapidly growing segment of the financial system in Bangladesh. They are gaining increased popularity in recent times. They play a vital role in the economy. This study attempts to predict the financial health of 15 publicly traded NBFIsof Bangladesh over five years ranging from 2011 to 2015 using Altman's Z Score Model (1965). The results show that most of the sampled NBFIs are in 'Distress' zone, Some of sample NBFIs are nationally and internationally acclaimed for their outstanding performances and contributions to the industrial as well as economic development of the country, but they fail to attain the minimum score. Most of the companies are lying on the bankruptcy level. Hence, the study suggests the stakeholders, including regulatory authorities and researchers to be more watchful of the operations of NBFIs.

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“…As a result, the P-score model was created. Following Atman, Nugent and Beneish studies, Pustylnick (2009Pustylnick ( , 2011 established significant changes in time between the P-score and Z-score models. The P-score changes [ P  ] were higher than Z-score [ Z  ] in 29 cases when companies were involved in accounting scandals.…”

Section: Introductionmentioning

confidence: 98%

“…Thus, the first stage of an audit or examination begins with the detection of abnormal changes that entail deterioration in the financial position of the company. Owing to the development of computer technologies, using the data mining as an audit tool, the fraud variables based on disproportionate changes were developed in the studies by Beneish (1999), Lenard and Alam (2005), Skousen and Wright (2006) and others (Lenard & Alam, 2009;Pustylnick, 2009).…”

Section: Introductionmentioning

confidence: 99%

Z-score and P-score for bankruptcy fraud detection: a case of the construction sector in Latvia

Liodorova

Voronova

2019

Proceedings of 6th International Scientific Conference Contemporary Issues in Business, Management and Economics Engineering ‘2

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To protect investment and ensure repayment of payables, recent studies have focused on identifying the relationships between company bankruptcy and internal fraud. The P-score model that is based on the most popular Altman Z-score model has been developed to indicate the manipulation of financial statements. Purpose of the study is to determinate the accuracy and the feasibility of P-score and Z-score models to detect fraudulent bankruptcy in regional conditions, based on reports of the Latvian construction companies that failed due to fraud, and during the verification of other known data. Research methodology is based on the background studies of P-score testifying, applying this approach to the Latvian condition. The present study analyzes the behaviour of the two models in identifying distress and fraud. To testify the results of the study, the authors use the financial analysis methods, comparison, statistical and quantitative research methods. Findings have shown the possibility of using the P-score and Z-score technique for bankruptcy fraud detection at the Latvian companies, based on the construction sector samples. The accuracy of the method is above 80%. Research limitations – acquisition a large amount of data on companies that are in the process of analytical studies on the recognition of their insolvency and having signs of fraud is not possible due to the confidentiality of information. Practical implications – the results of the study may be applicable to the audit of the company, investment reliability assessment, partnership evaluation and economic examination to detect fraud. Originality/Value of the study is the first test of practical implication of P-score model in Latvia and the Baltic countries on the samples of small and medium-sized construction companies. The authors propose improving the coefficients of the P-score model taking into account the requirements for financial statements in Latvia

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Combined Algorithm for Detection of Manipulation in Financial Statements

Cited by 17 publications

References 12 publications

دراسة واختبار العلاقة بین جودة المراجعة الخارجیة وخلو القوائم المالیة للشرکات المقیدة بالبورصة المصریة من الغش

دراسة واختبار العلاقة بین جودة المراجعة الخارجیة وخلو القوائم المالیة للشرکات المقیدة بالبورصة المصریة من الغش

Prediction of Financial Distress of Non-Bank Financial Institutions of Bangladesh using Altman’s Z Score Model

Z-score and P-score for bankruptcy fraud detection: a case of the construction sector in Latvia

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