scholarly journals Improving automatic data extraction from financial statements with clustering analysis

2020 ◽  
Author(s):  
Victor Ferraz ◽  
Gabriel Olivato ◽  
Igor Magollo ◽  
Murilo Naldi

The financial statement analysis is a fundamental part of the credit risk attribution process, producing documents that are valuable sources of information about companies’ economic and financial wealth. Large volumes of that type of document demand automatic data extraction, and locators drive the tools for that task. However, due to the lack of regulation, there is not a standard layout for such documents, which originates a variety of document structures. Such variety burdens the feature extraction tools, reducing their performance. Clustering analysis overcomes such burden by finding the best document clusters, allowing the development of fine-tuned locators for each cluster based on their main characteristics, which is the main objective of this work. We applied state-of-the-art clustering techniques, RNG-HDBSCAN*, FOSC and MustaCHE, over financial statements documents to assess their clusters and main structures, separate outliers, and analyze their main features. The result allows the specialists to define proper locators for each cluster, increasing the performance of the data extraction tools.

2001 ◽  
Vol 20 (1) ◽  
pp. 137-146 ◽  
Author(s):  
W. Robert Knechel ◽  
Jeff L. Payne

The process for providing accounting information to the public has not changed much in the last century even though the extent of disclosure has increased signifi-cantly. Sundem et al. (1996) suggest that the primary benefit of audited financial statements may not be decision usefulness but the discipline imposed by timely confirmation of previously available information. In general, the value of information from the audited financial statement will decline as the audit report lag (the time period between a company's fiscal year end and the date of the audit report) increases since competitively oriented users may obtain substitute sources of information. Furthermore, the literature on earnings quality and earnings management suggests that unexpected reporting delays may be associated with lower quality information. The purpose of this paper is to extend our understanding about the determinants of audit report lag using a proprietary database containing 226 audit engagements from an international public accounting firm. We examine three previously uninvestigated audit firm factors that potentially influence audit report lag and are controllable by the auditor: (1) incremental audit effort (e.g., hours), (2) the resource allocation of audit team effort measured by rank (partner, manager, or staff), and (3) the provision of nonaudit services (MAS and tax). The results indicate that incremental audit effort, the presence of contentious tax issues, and the use of less experienced audit staff are positively correlated with audit report lag. Further, audit report lag is decreased by the potential synergistic relationship between MAS and audit services.


2019 ◽  
pp. 158-162
Author(s):  
O. Ageeva ◽  
D. Formusatii

In this article, the authors consider reasons for development of variety of accounting policies and examine influencing of selected accounting policy elements on valuation of financial statements indicators. Obviously financial statements indicators are definitely one of the most important sources of information for financial analysis and management decisions. Financial analyst should be aware, which valuation methods have been presented in this financial statement, and how they influence on formulated by him analytical conclusions. The approach presented in the article to the assessment of the impact of accounting policies on the financial statements’ indicators and the conclusions formulated by the authors as a result of the research allows to get answers to these issues.


2021 ◽  
Author(s):  
Nabila Rajab ◽  
israeni

Financial statements are an important tool to obtain information regarding the financial position and results achieved by the company. Financial statements are one of the most important sources of information for making economic decisions. Financial statement analysis includes the application of tools and techniques to financial statements and financial data in order to obtain measures and relationships that are useful in the decision-making process.


Author(s):  
Nguyen Tien Hung ◽  
Huynh Van Sau

The study was conducted to identify fraudulent financial statements at listed companies (DNNY) on the Ho Chi Minh City Stock Exchange (HOSE) through the Triangular Fraud Platform This is a test of VSA 240. At the same time, the conformity assessment of this model in the Vietnamese market. The results show that the model is based on two factors: the ratio of sales to total assets and return on assets; an Opportunity Factor (Education Level); and two factors Attitude (change of independent auditors and opinion of independent auditors). This model is capable of accurately forecasting more than 78% of surveyed sample businesses and nearly 72% forecasts for non-research firms.  Keywords Triangle fraud, financial fraud report, VSA 240 References Nguyễn Tiến Hùng & Võ Hồng Đức (2017), “Nhận diện gian lận báo cáo tài chính: Bằng chứng thực nghiệm tại các doanh nghiệp niêm yết ở Việt Nam”, Tạp chí Công Nghệ Ngân Hàng, số 132 (5), tr. 58-72.[2]. Hà Thị Thúy Vân (2016), “Thủ thuật gian lận trong lập báo cáo tài chính của các công ty niêm yết”, Tạp chí tài chính, kỳ 1, tháng 4/2016 (630). [3]. Cressey, D. R. (1953). Other people's money; a study of the social psychology of embezzlement. New York, NY, US: Free Press.[4]. Bộ Tài Chính Việt Nam, (2012). Chuẩn mực kiểm toán Việt Nam số 240 – Trách nhiệm của kiểm toán viên đối với gian lận trong kiểm toán báo cáo tài chính. [5]. Jensen, M. C., & Meckling, W. H. (1976). Theory of the firm: Managerial behavior, agency costs and ownership structure. Journal of financial economics, 3(4), 305-360.[6]. Võ Hồng Đức & Phan Bùi Gia Thủy (2014), Quản trị công ty: Lý thuyết và cơ chế kiểm soát, Ấn bản lần 1, Tp.HCM, Nxb Thanh Niên.[7]. Freeman, R. E. (1984). Strategic management: A stakeholder approach. Boston: Pitman independence on corporate fraud. Managerial Finance 26 (11): 55-67.[9]. Skousen, C. J., Smith, K. R., & Wright, C. J. (2009). Detecting and predicting financial statement fraud: The effectiveness of the fraud triangle and SAS No. 99. Available at SSRN 1295494.[10]. Lou, Y. I., & Wang, M. L. (2011). Fraud risk factor of the fraud triangle assessing the likelihood of fraudulent financial reporting. Journal of Business and Economics Research (JBER), 7(2).[11]. Perols, J. L., & Lougee, B. A. (2011). The relation between earnings management and financial statement fraud. Advances in Accounting, 27(1), 39-53.[12]. Trần Thị Giang Tân, Nguyễn Trí Tri, Đinh Ngọc Tú, Hoàng Trọng Hiệp và Nguyễn Đinh Hoàng Uyên (2014), “Đánh giá rủi ro gian lận báo cáo tài chính của các công ty niêm yết tại Việt Nam”, Tạp chí Phát triển kinh tế, số 26 (1) tr.74-94.[13]. Kirkos, E., Spathis, C., & Manolopoulos, Y. (2007). Data mining techniques for the detection of fraudulent financial statements. Expert Systems with Applications, 32(4), 995-1003.[14]. Amara, I., Amar, A. B., & Jarboui, A. (2013). Detection of Fraud in Financial Statements: French Companies as a Case Study. International Journal of Academic Research in Accounting, Finance and Management Sciences, 3(3), 40-51.[15]. Beasley, M. S. (1996). An empirical analysis of the relation between the board of director composition and financial statement fraud. Accounting Review, 443-465.[16]. Beneish, M. D. (1999). The detection of earnings manipulation. Financial Analysts Journal, 55(5), 24-36.[17]. Persons, O. S. (1995). Using financial statement data to identify factors associated with fraudulent financial reporting. Journal of Applied Business Research (JABR), 11(3), 38-46.[18]. Summers, S. L., & Sweeney, J. T. (1998). Fraudulently misstated financial statements and insider trading: An empirical analysis. Accounting Review, 131-146.[19]. Dechow, P. M., Sloan, R. G., & Sweeney, A. P. (1996). Causes and consequences of earnings manipulation: An analysis of firms subject to enforcement actions by the SEC. Contemporary accounting research, 13(1), 1-36.[20]. Loebbecke, J. K., Eining, M. M., & Willingham, J. J. (1989). Auditors experience with material irregularities – Frequency, nature, and detectability. Auditing – A journal of practice and Theory, 9(1), 1-28. [21]. Abbott, L. J., Park, Y., & Parker, S. (2000). The effects of audit committee activity and independence on corporate fraud. Managerial Finance, 26(11), 55-68.[22]. Farber, D. B. (2005). Restoring trust after fraud: Does corporate governance matter?. The Accounting Review, 80(2), 539-561.[23]. Stice, J. D. (1991). Using financial and market information to identify pre-engagement factors associated with lawsuits against auditors. Accounting Review, 516-533.[24]. Beasley, M. S., Carcello, J. V., & Hermanson, D. R. (1999). COSO's new fraud study: What it means for CPAs. Journal of Accountancy, 187(5), 12.[25]. Neter, J., Wasserman, W., & Kutner, M. H. (1990). Applied statistical models.Richard D. Irwin, Inc., Burr Ridge, IL.[26]. Gujarati, D. N. (2009). Basic econometrics. Tata McGraw-Hill Education.[27]. McFadden, D. (1974). Conditional Logit Analysis of Qualita-tive Choice Behavior," in Frontiers in Econometrics, P. Zarenm-bka, ed. New York: Academic Press, 105-42.(1989). A Method of Simulated Moments for Estimation of Discrete Response Models Without Numerical Integration," Econometrica, 54(3), 1027-1058.[28]. DA Cohen, ADey, TZ Lys. (2008), “Accrual-Based Earnings Management in the Pre-and Post-Sarbanes-Oxley Periods”. The accounting review.


2020 ◽  
Vol 25 (1) ◽  
pp. 29-44
Author(s):  
Mariati ◽  
Emmy Indrayani

Company’s financial condition reflected in the financial statements. However, there are many loopholes in the financial statements which can become a chance for the management and certain parties to commit fraud on the financial statements. This study aims to detect financial statement fraud as measured using fraud score model that occurred in issuers entered into the LQ-45 index in 2014-2016 with the use of six independent variables are financial stability, external pressure, financial target, nature of industry, ineffective monitoring and rationalization. This study using 27 emiten of LQ-45 index during 2014-2016. However, there are some data outlier that shall be removed, thus sample results obtained 66 data from 25 companies. Multiple linear regression analysis were used in this study. The results showed that the financial stability variables (SATA), nature of industry (RECEIVBLE), ineffective monitoring (IND) and rationalization (ITRENDLB) proved to be influential or have the capability to detect financial statement fraud. While the external pressure variables (DER) and financial target (ROA) are not able to detect the existence of financial statement fraud. Simultaneously all variables in this study were able to detect significantly financial statement fraud.


2018 ◽  
Vol 23 (1) ◽  
pp. 72-85
Author(s):  
Lasminisih ◽  
Emmy Indrayani

Company financial statement can be used to monitor the performance of a company. Financial statements are also used as a means for decision making so that the company can anticipate future plans. The purpose of this study was to find out the effect of Capital Adequacy Ratio (CAR), Loan to Deposit Ratio (LDR) and Return on Assets (ROA) on profit changes percentage of Banking Companies. The number of sample companies used in this study was 27 Banks listed in the Indonesia Stock Exchange with observation periods from 2007 to 2008. The method used in this study was multiple regression. The results of this study have indicated that CAR, LDR, and ROA gave significant effects on changes in Banks profit so that Banking Companies performances can be measured. Keywords: CAR, LDR, ROA, Profit


2014 ◽  
Vol 90 (2) ◽  
pp. 641-674 ◽  
Author(s):  
Pepa Kraft

ABSTRACT I examine a dataset of both quantitative (hard) adjustments to firms' reported U.S. GAAP financial statement numbers and qualitative (soft) adjustments to firms' credit ratings that Moody's develops and uses in its credit rating process. I first document differences between firms' reported and Moody's adjusted numbers that are both large and frequent across firms. For example, primarily because of upward adjustments to interest expense and debt attributable to firms' off-balance sheet debt, on average, adjusted coverage (cash flow-to-debt) ratios are 27 percent (8 percent) lower and adjusted leverage ratios are 70 percent higher than the corresponding U.S. GAAP ratios. I then find that Moody's hard and soft rating adjustments are associated with significantly higher credit spreads and flatter credit spread term structures. Overall, the results indicate that Moody's quantitative adjustments to financial statement numbers and qualitative adjustments to credit ratings enable it to better capture default risk, consistent with it effectively processing both hard and soft information.


2014 ◽  
Vol 89 (6) ◽  
pp. 2115-2149 ◽  
Author(s):  
Keith Czerney ◽  
Jaime J. Schmidt ◽  
Anne M. Thompson

ABSTRACT According to auditing standards, explanatory language added at the auditor's discretion to unqualified audit reports should not indicate increased financial misstatement risk. However, an auditor is unlikely to add language that would strain the auditor-client relationship absent concerns about the client's financial statements. Using a sample of 30,825 financial statements issued with unqualified audit opinions during 2000–2009, we find that financial statements with audit reports containing explanatory language are significantly more likely to be subsequently restated than financial statements without such language. We find that this positive association is driven by language that references the division of responsibility for performance of the audit, adoption of new accounting principles, and previous restatements. In addition, we find that (1) “emphasis of matter” language that discusses mergers, related-party transactions, and management's use of estimates predicts restatements related to these matters, and that (2) the financial statement accounts noted in the explanatory language typically correspond to the accounts subsequently restated. In sum, our results suggest that present-day audit reports communicate some information about financial reporting quality.


Author(s):  
Yi-Hung Lin ◽  
Hua-Wei (Solomon) Huang ◽  
Mark E. Riley ◽  
Chih-Chen Lee

We find a negative relationship between aggregate CSR scores and the probability that firms restated financial statements over the period 1991-2012. We then break that period into three sub-periods in order to determine whether the relationship holds for all three sub-periods. During the sub-periods of 1991-2001 and 2002-2005, the negative CSR score - restatement probability relationship holds. The negative relationship disappears in the 2006-2012 sub-period. Additional analyses indicate CSR scores are significantly higher in the 2006-2012 sub-period, suggesting the disappearance of the relationship between aggregate CSR scores and financial statement quality may relate to changes in CSR assessments and the CSR reporting environment. Our findings update the literature linking CSR scores and financial reporting quality and identify the need for further research as to the reasons the link between these constructs disappeared.


2020 ◽  
Vol 34 (3) ◽  
pp. 87-112
Author(s):  
Bei Dong ◽  
Stefanie L. Tate ◽  
Le Emily Xu

SYNOPSIS Regulations implemented by the SEC in 2003 and 2004 simultaneously shortened the financial statement filing deadlines and increased the time required for both the preparation of financial statements and the related audit of accelerated filers (AFs). However, there were indirect, unintended negative consequences for companies not subject to the regulations, namely, non-accelerated filers (NAFs). The new regulations imposed strains on auditor resources requiring auditors to make resource allocation decisions that negatively affected NAFs. We find that NAFs with an auditor who had a high proportion of AF clients (high-AF) had longer audit delays after the regulations were implemented than NAFs of an auditor with a low proportion of AF clients (low-AF). Further, we document that NAFs with high-AF auditors were more likely to change auditors than NAFs with low-AF auditors. Finally, NAFs that switched to auditors with less AFs experienced shorter audit delays after the auditor change. JEL Classifications: M42; M48.


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