Benford's Law

La Ley de Benford y sus Variantes es una Técnica de Análisis de Datos, Auditoría, Minería de Datos, Monitoreo de Generadores BigData y Seguimiento de Procesos; que en base a los datos permite establecer si sus valores cumplen un comportamiento cercano a la "normalidad" según la naturaleza de la fuente (empresarial, industrial, financiero, comercial, de servicios, gubernamental, redes sociales); así como determinar % de distorsión en Datos NO Estructurados (Imagenes, Audios, Videos) mediante conversion a Series de Fourier Especializada XFS.

This quantitative study combined the Altman z, Zmijewski x and Beneish m models targeted at the 2009 to 2016 secondary data of the twenty-six listed non-financial firms on the Ghana Stock Exchange to explore warning signals of bankruptcy and fraud reporting. The rationale was to enable Ghana bank managers reduce the risks in the lending decision process in the hype of the 2017/18 Ghana banking crisis that led to collapse of seven banks over this period. Both the z and x models bankruptcy predictions provided statistically significant results when moderated with the m fraud model. The study rejects the null hypothesis that there is no statistically significant relationship between the Altman z and Beneish m scores prediction of bankruptcy and fraud events on the listed non-financial firms on the GSE. Also, the study rejects the null hypothesis that there is no statistically significant relationship between the Zmijewski x and Beneish m scores prediction of bankruptcy and fraud events on the listed non-financial firms on the GSE. In addition, the study rejects the null hypothesis that, there is no statistically significant contradiction between the Altman and Zmijewski models moderated prediction of bankruptcy events on the listed non-financial firms on the GSE. The contradiction in the bankruptcy results had a strictly distress prediction focus for the Altman model and vice versa for the Zmijewski model.

The fraud reporting and data manipulation is discussed across the various scientific fieldsin economy, finance, sociology and many others. Particularly, the economic and finance data are under the strong scrutiny. In literature we can find extensive discussion on the creative accounting, which is considered as the source of the intensive data manipulation. It is pointed on the fact that the managers may adopt various methods to manipulate the financial statements of their firms to show their higher/better performance and to receive the higher managerial earnings. The Benford law as a statistical tool is illustrated as a possible tool in detecting this problem.

This paper explores the influence of regulatory frameworks and environmental factors on the accounting practices of companies in Ghana. It emphasizes the critical role of a robust regulatory environment, maintained by bodies such as the Institute of Chartered Accountants, Ghana (ICAG), and the Securities and Ex

Benford Yasası, doğal veri kümelerinde başlangıç rakamlarının belirli bir düzeni takip ettiğini ifade eden bir istatistik prensibidir. Finansal denetim sürecinde Benford Yasası kullanılarak finansal tablo verilerinde oluşabilecek potansiyel düzensizlik, hata ve hileler belirlenebilmektedir. Konaklama işletmeleri; mevsimsel talep değişiklikleri, maliyet yapısı, varlık değerlemesi gibi konularda diğer işletmelerden farklılık göstermektedir. Bu araştırmada, Borsa İstanbul’da faaliyet gösteren konaklama işletmelerinin dönen varlıklar, duran varlıklar, aktif toplam, uzun vadeli yükümlülükler, kısa vadeli yükümlülükler, özkaynaklar, satış gelirleri, satışların maliyeti, brüt kar, faaliyet karı, vergi öncesi kar, amortisman giderleri, işletme-yatırım-finansman faaliyetlerinden sağlanan nakit akışları ile nakit ve nakit benzerlerindeki net artış veya azalış kalemlerinin Benford Yasası’na uygunluğunun tespit edilmesi amaçlanmıştır. Bu amaç doğrultusunda konaklama işletmelerinin söz konusu finansal tablo kalemlerinin Haziran 2016 – Haziran 2023 dönemindeki rakamsal dağılımları Ki-Kare testi ile analiz edilmiştir. Yapılan analiz, dönen varlıklar, duran varlıklar, aktif toplam, uzun vadeli yükümlülükler ve
özkaynaklar kalemlerinin Benford Yasası’na uymadığını gösterse de diğer kalemlerin uygunluk gösterdiğini ortaya koymaktadır.

Benford’s law is understudied in financial markets and almost entirely unstudied in relation to stock prices. This study identifies some general patterns of Benford behaviour specific to closing stock prices based on the individual datasets of 1,254 companies over their complete lifetimes as at the date of writing: the S&P 500, German companies traded on the Frankfurt Stock Exchange and an American OTC population (control group). The results provide strong empirical evidence that stock prices can be expected to follow the Benford distribution provided that trading volumes are taken into account together with price. The results also indicate that there may be a serious price integrity problem in the American public capital markets as the S&P 500 is observed to exhibit mirror-opposite patterns to the OTC control population and the German population, which both closely follow the expectations of the Benford theory. The empirical results are presented against the relevant regulatory background in order to highlight the potential practical implications.

Resumen
Se presenta un análisis mediante la Ley de Benford, o Ley de los Primeros Dígitos, establece que, en muchos conjuntos de datos naturales, los dígitos no aparecen con igual frecuencia; el dígito 1 es el más frecuente como primer dígito, con una proporción teórica de aproximadamente 30.1%, mientras que el dígito 9 aparece alrededor del 4.6% del tiempo. Esta ley se aplica en el análisis de datos electorales para verificar si los resultados siguen la distribución esperada o si hay anomalías. El análisis implica extraer los primeros dígitos de los números de votos, contar las frecuencias y compararlas con las proporciones teóricas. En MATLAB, un programa para este análisis incluye la definición de datos, extracción de primeros dígitos, conteo de frecuencias, comparación con la teoría y visualización. La coincidencia con la teoría sugiere datos naturales, mientras que desviaciones significativas pueden indicar irregularidades que necesitan investigación. Las desviaciones pueden deberse a errores en la recopilación, manipulación o peculiaridades en el reporte. Aunque la Ley de Benford es útil, no es infalible y debe ser interpretada en contexto.

We report positive correlations between letter frequency and symmetry (more symmetric symbols are more frequent) in English and Russian languages and in four types of numerals (Western, Roman, Arabic, and Chinese) with the coefficients of determination of 2 = 0.899 (English), 2 = 0.693 (Russian) and 2 = 0.740 (numerals). For comparison, we studied "symbol-like" 2D colloidal clusters and found negative correlations between frequency and symmetry (2 = 0.814 and 2 = 0.994). While in human-made systems the frequency of using of a symbol is the driving force which leads to symbols simplification and symmetrizing, in natural system, symmetry leads to lower frequency of occurrence because there are fewer ways of building symmetric clusters than asymmetric ones. We interpret these results as a correlation between the symbol as a type and as a token and we attribute this correlation to the inherent iconicity of symbols

In recent decades, predicting company bankruptcies and financial troubles has become a major concern for various stakeholders. Furthermore, because financially sustainable businesses are affected by numerous highly complex factors, both internal and external, the situation is even more complex. This paper applies Altman’s Z-score models; more precisely, the paper applies the initial Z-score model (a model for manufacturing companies), the Z′-score model (for companies operating in emerging markets), and the Z-score bankruptcy probability calculation. Therefore, this paper offers the results of the application of different Z-score models and the calculation of bankruptcy probability on a sample of agricultural companies listed on the Belgrade Stock Exchange in the period 2015–2019. In addition, different Z-score models are used for the same sample so that the difference between their results and application can be determined. In addition, the validity of the data published in the fin...

Nowadays, money laundering has become a serious threat to the world economy. Traditional methods of Anti Money Laundering (AML) are costly and inefficient. Recently, data mining techniques have been developed and have been considered as appropriate methods to detect money laundering activities. The purpose of this research is to detect money laundering suspicious cases which might need more detailed scrutiny using data mining algorithms with real banking transaction datasets. CRISP-DM would be used as the research methodology, the statistical population would be the banking transactions and samples would be the transactions of one of the bank branches. For this purpose, two main approaches are used. In the first approach, using the k-means algorithm, financial transactions of banking accounts are clustered. Then, using anomaly detection techniques, abnormal transactions that might be suspicious of money laundering and need to be scrutinized in more detail have been detected. In the second approach, a novel technique using Benford’s law and GANs algorithm has been introduced. It can detect financial accounts that used concocted amounts in their transactions and might be suspicious of financial fraud and money laundering. The first approach can identify accounts with outliers in their transactions with an accuracy of about 93%, and the second approach can identify suspicious accounts that do not use professional methods to hide fake figures in their transactions with an accuracy of about 60%. to recognize correctly.

Economic growth is closely linked with the financial system of the country. As a financial institution, banking sector contribute a lot to the economic development. Our banking system has shown a fabulous growth since nationalisation and even after reforms of 1991 but has also faced decline in profitability on the other side due to sudden hike in the non-performing assets of the banks. In spite of due care, many loan and advances are turning into bad debts due to failure of recovery mechanism and becoming non-performing assets. The present study aims to examine the position of NPAs of the Schedule Commercial banks of the India over a period of 7 years from the year 2014-15 to 2020-21. The secondary data were used to conduct the study. The statistical tools such as mean, Standard deviation and chi-square test were applied. For estimating expected trend of NPAs, least square technique of the time series analysis was used. The study revealed that there is no significance association in position of gross NPAs, Net NPAs and NPA Provisions over a period of time. It was concluded that RBI and government should implement innovative and strict policy for reducing NPAs.

Corporate Financial Reporting is one of the petal issues in corporate financial existence. It provides an insight into the viability of a company's corporate existence. Corporate financial reporting is aided by proper auditing practices, hence the need to address the challenges facing the auditing practice such as lack of auditors independence. Ninety four copies of questionnaire were administered on branch managers, auditors, investors and financial analysts within Delta State but only 82 were retrieved. Likert attitudinal form ranging from 1-5scale was used. Pearson Product Moment Correlation Coefficient statistical tool and the t-test at 0.05 was adopted for the analysis. The paper discovered that there are significant differences between IFRS financial reports and those prepared under Nigeria Generally Accepted Accounting Principles (GAAP). The adoption of IFRS is a right set in the right direction. The study recommends that the Financial Reporting Council in Nigeria should be on the alert to the best international accounting practice (IFRS) to guide them in the establishment of highly improved practices in Nigeria.

Cartilla de apropiación social del conocimiento de la "Estrategia de conservación, uso y manejo de la biodiversidad a partir de la Estructura Ecológica Principal y la Restauración Ecológica para la jurisdicción de la CDMB" donde se cuenta el desarrollo metodológico, principales resultados de la caracterización y el plan de gestión para la conservación, manejo y uso sostenible de la biodiversidad.

IFRS adoption's effect and board governance on accounting quality from Ghanaian perspective was examined using OLS technique between a sevenyear periods (2013-2019). From the study, IFRS adoption negatively impacts accounting quality in an insignificant manner. The insignificant nexus was due to lax implementation of regulations by institutions with IFRS and incentive-performance tied schemes presented to managers. Additionally, all but profitability and institutional ownership have positively significant impact on accounting quality whilst board governance negatively affect accounting quality though not statistically significant. Finally, moderating the role of board governance on IFRS-accounting quality relation, evidence established from the regression is that board governance does not moderate relationship between IFRS adoption and accounting quality using discretionary accruals. Our study captured effective corporate governance practices using composite board governance index to moderate effect of IFRS on the nexus between board governance and accounting quality serving as central motivation to contribute to literature.

This paper examined corporate governance and financial statements manipulation in Nigeria, using the Beneish model. To this end, the Beneish Model was employed to predict the likelihood of financial statements manipulation among the companies in Nigeria while the role of corporate governance variables to this manipulation was examined, using logistic regression analysis. In specific terms, the corporate governance variables of Board Composition, Board Gender Composition, Audit Committee Composition, and Board Dominance were examined as determinants. The data used were extracted from sixty-five (65) quoted companies in the Nigeria Stock Exchange for a 6-year period of 2009-2014. This period a near-crash in the Nigerian stock market with the consequential low ebb in economic activities in Nigeria. Preliminary analysis reveals that most of the companies quoted in the Nigeria Stock Exchange and sampled for this study, based on the Beneish Model, have the probability of manipulating their annual financial statements. Furthermore, results revealed that an increase in the Board Composition defined in the proportion of the Non-Executive Director (NED) on the Board, will increase the likelihood of detecting, preventing and investigating financial statements manipulation in the quoted companies in Nigeria. In addition, it was discovered that, in the Board Gender Composition, an increase in the proportion of female gender in the entire board will increase the likelihood of detecting, preventing and investigating financial statements manipulation. Meanwhile, it was revealed that an increase in the effectiveness and efficiency of the composition of the audit committee may reduce the likelihood of financial statements manipulation in Nigeria companies. Lastly, it was discovered that a decrease in Board Dominance will increase the likelihood of detecting, preventing and investigating misstatements in the annual financial statements of Nigeria companies. It is recommended. in the meantime, to use the Beneish model as a norm to assess the possibility of financial statements manipulation. More stringent measures, such as whistleblowing, ethics, value system, zero tolerance to fraud, just to mention a few, are to be effectively enforced by external regulatory authorities (such as Central Bank of Nigeria, Securities and Exchange Commission and the Nigerian Stock Exchange) to control the activities of the company's board of directors, as well as the application of Beneish model, would aid the detection of financial statements manipulation.

Benford's law is often used as a support to critical decisions related to data quality or the presence of data manipulations or even fraud. However, many authors argue that conventional statistical tests will reject the null of data "Benford-ness" if applied in samples of the typical size in this kind of applications, even in the presence of tiny and practically unimportant deviations from Benford's law. Therefore, they suggest using alternative criteria that, however, lack solid statistical foundations. This paper contributes to the debate on the "large n" (or "excess power") problem in the context of Benford's law testing. This issue is discussed in relation with the notion of severity testing for goodness of fit tests, with a specific focus on tests for conformity with Benford's law. To do so, we also derive the asymptotic distribution of the mean absolute deviation (M AD) statistic as well as an asymptotic standard normal test. Finally, the severity testing principle is applied to six controversial data sets to assess their "Benford-ness".

Application of Benford's Law in the field of financial analysis is very rarely covered. In this paper it is researched possibility of usage of this law in analysis of stock prices and stock turnover in Zagreb stock exchange. On the basis of online available and public data, sets of input numbers are prepared. These sets are checked against Benford's Law. Results show that sets partially fit to this law. Stock turnover data conforms to Benford's Law, while daily closing stock prices do not. Probably, psychological factors significantly influence daily closing stock prices, so these values do not conform to Benford's distribution. S a ž e t a k O primjeni Benfordovog zakona u području financijskih analiza u literaturi postoji malo izvora. U ovom radu se istražuje mogućnost primjene ovog zakona u analizi kretanja cijena i prometa dionica na burzi, i to na primjeru Zagrebačke burze. Temeljem online raspoloživih podataka, oblikovani su skupovi ulaznih nizova na koje je primijenjen Benfordov zakon. Dobiveni rezultati ukazuju da je ovaj zakon djelomično primjenljiv i za takvu problematiku. Potpuno je primjenljiv za analize i procjene ukupnog dnevnog promete dionica, ali nije primjenljiv za analize i procjene zadnjih dnevnih cijena dionica. Vjerojatno na ove cijene na tržištu značajno utječu psihološki čimbenici, pa stoga ova pojava ne slijedi Benfordovu distribuciju.

Instead of presenting the data as it is, financial statement editors may display it as what it should be. Therefore there is a need to know the truthfulness, quality, reliability, and trustworthiness of reported and presented financial data. Thus, the main objective of this study is to identify the possibility of suspicion in the financial data of selected listed companies of Adani group. To meet this objective the collected financial data of selected companies has been analyzed using first digit, second digit, third digit, and fourth digit test of digital analysis of Benford's law. From the digital analysis it is found that there is somewhat deviation in actual financial data as compared to natural number distribution given in Benford's law. The deviation percentages highlight potential areas that may need more scrutiny to identify if there are any issues or discrepancies in the data. Further investigation is required to pinpoint the exact reasons behind these deviations and determine if they indicate fraudulent activities or other irregularities.

This study aims to analyze the role of leverage which moderates the effect of business intelligence, intellectual capital, and financial performance on firm value and is controlled by the variable firm size and sales growth in manufacturing industry companies on the IDX in 2013-2021. This study uses secondary data and panel data, a sample of 420 manufacturing industry companies in 2013-2021. The results of the first model study before moderation show that the independent variables of business intelligence, intellectual capital and company performance have a positive effect on firm value. However, for the leverage variable it has a negative effect on firm value, which shows that the higher the debt owned, the lower the company's value. The application of business intelligence can be done through the improvement of a good integrated system. Companies should optimize their intellectual capital. The use of debt to finance a company can increase the value of the company, this increas...

The growing convolution of industries and the need for corporate business survival has created a cognizance dilemma on the nexus of earnings management and managerial compensation paradigm, especially in developing nations. Hence, this paper sought to examine the nexus of earnings management and managerial compensation in Nigerian manufacturing firms. The study collected panel data from audited annual financial reports of six selected manufacturing firms listed in the Nigeria Stock Exchange, covering the period from, 2012-2019. The data were analyzed using descriptive statistics, correlation and Panel Regression Model. The findings indicate that earnings management is a significant determinant of managerial remuneration. Therefore, the study concludes that managing earnings of firms has a positive significant relationship with executive remuneration, and as such compensation should be tied to performance of the firm in real values.

This study investigates the implications of the gap between International Financial Reporting Standards (IFRS) and New Zealand International Financial Reporting Standards (NZIFRS) on financial reporting transparency, accountability and corporate fraud. Content analysis of IFRS and NZIFRS was carried out to determine if there are differences between IFRS and NZIFRS. Four IFRS, namely IAS 12, IFRS 13, IFRS 15, IAS 17 and IFRS 16 were analysed on the basis of adoption concessions and Reduced Disclosure Regime (RDR) for tier 1 and 2 entities. The findings from these standards led to a review of the associated IFRS to further understand the implications of the standards on financial reporting transparency and decline in incidences of corporate fraud. We found that the difference between IFRS and NZIFRS lies in the financial reporting framework for tier 2 entities. However, we did not find a difference between IFRS and NZIFRS for entities in tier 1 but we identified a decline in incidences of corporate fraud after IFRS was adopted. We further identified the presence of information asymmetry for tier 2 which is capable of retaining Generally Accepted Accounting Principles (GAAPs). These differences may increase the incidence of corporate fraud among the entities in tier 2 of External Reporting Framework. This is due to an excessive concession from IFRS implementation in New Zealand.

The aim of this study is to determine whether the earthquake magnitude data comply with Benford's Law. To this end, magnitude data of 14.565 earthquakes that occurred in Turkey between January 1, 2023, and February 27, 2023, were analyzed by comparing them with the numerical distribution of Benford's Law. According to the results obtained from the analysis, it has been determined that the earthquake magnitude digits conform to Benford's Law and closely follow Benford's Law with very small deviations. These small deviations are thought to arise from the rounding of magnitude data to a single decimal place, the inability to detect very small magnitude earthquakes occurring deeper than a certain depth, or very small measurement errors in the existing data. Therefore, it can be said that earthquake occurrences occur as a result of natural processes and earthquake magnitudes are determined correctly.

The Euro changeover distorted previously well-formed nominal price patterns. Food retailers may have reacted by adjusting prices to reintroduce psychological prices as before the Euro changeover. We employ a detailed data set of German food retail prices before and after the Euro changeover to test three different benchmarks indicating potential adjustments of prices. However, none of these benchmarks do adequately reflect the actual distribution of prices. We find that prices of signpost items follow best a conversion at the official rate. Also, signpost items show a slower price adjustment. Occasional goods' prices indicate a reestablishment of psychological price patterns, in particular for the ending digits; price distributions are adjusted faster. Further, price inflation is about zero for both goods, but prices in particular for signpost items have been significantly raised just before the Euro changeover. These different pricing patterns may be explained by consumer behavior. Consumers react more sensitive to price changes of frequently purchased goods (signpost items), and thus, retailers convert prices at the official rate and postpone price adjustments for these items after the Euro changeover. [JEL Classifications: D40, L66, Q13]. C 2015 Wiley Periodicals, Inc. 1 We follow a definition proposed by El Sehity, Hoelzl & Kirchler (2005). Psychological prices indicate a nine at the second or third (last) digit. In general "psychological pricing is the practice of setting prices slightly lower than rounded numbers, in the belief that customers do not round up these prices, and so will treat them as lower prices than they really are" (see http://www.accountingtools.com/psychological-pricing/07.05.2014).

Financial statement fraud has had the most significant monetary impact on companies compared to the other categories of fraud. Over half of the financial statement frauds were committed through improper revenue recognition. According to a survey of 652 companies, revenue provides the greatest risk and impact to financial statements. The revenue recognition rules published by IFRS will not alleviate this concern. The purpose of this study is to analyze whether two analytical procedures described in fraud examination textbooks correctly identify known earnings manipulators.

The growing use of internet and the existence of vulnerable points in networks have made the use of intrusion detection systems as one of the most important security elements. Intrusion detection is essentially a classification problem and it is the identification of effective features such as important issues in the classification This paper presents a novel method for selecting effective features in network intrusion detection based on an estimation of distribution algorithm that uses a probabilistic dependency tree to identify important interactions between features. To evaluate the performance of the proposed method, the NSLKDD dataset is used, in which the packets are divided into five normal types and intrusive types of DOS, U2R, R2L and Prob. The performance of the proposed algorithm has been compared alone and in combination with other feature selection algorithms such as forward selection, backward selection and genetic algorithm. Moreover, the effect of algorithm parameter...

The aim of this article is to answer the question whether the unreliability of the Altman bankruptcy prediction model may be caused by manipulations in financial statements. Our study was carried out on a group of 369 bankrupt Polish companies, with the research period covering the years 2011–2020. In the study, we divided the companies into two groups: those correctly classified by Altman’s model as at risk of bankruptcy, and companies for which the model did not indicate a significant bankruptcy risk. Using a logit model, we tested whether the probability of companies being correctly classified as failed depends on the risk of a manipulation of financial statements. We use Benford’s law to measure the risk of a manipulation of financial statements. We also repeated our study using panel data models. Our analyses show that the manipulation of financial statements is not the cause of the inaccurate predictions of the Altman model. On the contrary, the results of the analyses indicat...

Business landscape is becoming increasingly competitive and more intense each day and as such, every company, owners and management strives to better their performance and this has created tendencies geared to realizing a premeditated target through any means possible within the acceptable accounting standards either from real activities or accruals and/or both. This study, as a result, intends to investigate whether corporate profitability level, corporation magnitude, and corporate board magnitude have significant influence on determinants of a holistic earnings management practices among the sampled non financial firms for years 2011-2021. Ex-post facto research design was employed and data extracts obtaind were analysed using the multiple regression. Findings made showed that Corporate Profitability level, and Corporate Board Magnitude exert significantly but negative influence on efforts targeted at Holistic Earnings Management (p-values 0.019 and 0.000 < 0.05; z-statistics-1.31 and =3.61 respectively) while Corporation Magnitude does not exert statistically significant influence on efforts targeted at Holistic Earnings Management (p-value 0.295 > 0.05) though it maintained a strong but negative influence (z-statistics-1.05). The study therefore concludes that an increase in corporate profitability level; corporation magnitude; corporate board magnitude and revenue growth leads equivalently to the non-likelihood of sampled firms engaging in holistic earnings management. This implies that where corporate board magnitude is not sufficiently large and equipped to effectively implement management team control, corporate firms already suffering from market capitalization dwindling or fluctuating profitability levels, are exposed to the risk of managing earnings holistically. The study therefore recommends among others that the historical performances of the firms be critically examined especially as it determines the current and future quality of its financial reports.

Fraud in bids occurs by trying to thwart their competitive nature, causing overbilling, and favoring a specific group. This research aims to verify which set of indicators and algorithms has better properties and greater assertiveness in identifying potential fraudsters among public administration suppliers in the hiring processes of the State Government of Rio de Janeiro. The research is relevant since it can be used by government control bodies and private companies to identify these acts in the hiring process. The results obtained were satisfactory for the classification of sanctioned suppliers. As part of the methodology, the Newcomb-Benford Law was applied initially to the contract data published on the Transparency Portal of the Government of the State of Rio de Janeiro and demonstrated that the database was not in compliance with the law, and could be prone to having suffered manipulation of the numbers. Next, different supervised classification methods were evaluated, namely, nearest neighbor (KNN), logistic regression, support vector machine (SVM) and classification tree in order to identify fraudsters. The classification algorithm with the best result in the two evaluation metrics was the SVM, with an accuracy of 99.30%, and a false positive in the base-test verification. The attributes surveyed through the databases were also relevant in the model's
result.

In this paper, we examine the economic, political, and legal systems as well as the institutional factors that influence the accounting and disclosure practices in Ghana. The impact of International Financial Reporting Standards (IFRS) on disclosure is also investigated, as Ghana has recently completed full adoption. We find that the accounting and reporting practices are significantly influenced by legal, political, institutional, and economic factors and that the regulatory environment is neither effective nor efficient due to the weak monitoring and enforcement of compliance. Although there has been some recent progress, the Companies' Code, which is the corporate legal framework of Ghana, must be updated to reflect the dynamic nature of world operations. This study advances the course of standards setters, regulators, accounting practitioners, and policymakers to improve the corporate reporting and accounting practices. Urgent measures need to be undertaken to reform and build the capacities of institutions charged with the responsibility of regulating and monitoring Ghanaian accounting and reporting practices to ensure best practices and build investors' confidence.

Considering the burning problem of corruption and non-transparency of public enterprises in the Federation of Bosnia and Herzegovina (FBiH), the paper aims to investigate whether the Beneish M-score model can be used to predict inaccurate financial statements. Where, the cause of inaccurate financial statements are intentional or unintentional errors. On a sample of 200 financial statements of public enterprises and related audit reports issued by the Audit Office of the Institutions in FBiH, we made a link between the Beneish M score model with its partial indicators (DSRI, GMI, AQI, SGI, DEPI, SGAI, LVGI, TATA) and four types of opinions: positive, opinion with distraction, negative and refraining from giving opinions. The research was conducted using descriptive statistics and an artificial neural network with the “scaled conjugate gradient backpropagation (trainscg)” algorithm for pattern recognition and classification. The research results show that it is possible on the basis ...

In recent decades, predicting company bankruptcies and financial troubles has become a major concern for various stakeholders. Furthermore, because financially sustainable businesses are affected by numerous highly complex factors, both internal and external, the situation is even more complex. This paper applies Altman’s Z-score models; more precisely, the paper applies the initial Z-score model (a model for manufacturing companies), the Z′-score model (for companies operating in emerging markets), and the Z-score bankruptcy probability calculation. Therefore, this paper offers the results of the application of different Z-score models and the calculation of bankruptcy probability on a sample of agricultural companies listed on the Belgrade Stock Exchange in the period 2015–2019. In addition, different Z-score models are used for the same sample so that the difference between their results and application can be determined. In addition, the validity of the data published in the fin...

Improving the accuracy of the Benford algorithm via Monte Carlo simulation for sample size determination Research Aim: Bedford's Law can be used to detect fraud. Previous research has highlighted a weakness of the algorithm, though: a high number of false positives. For auditors, false positives have become a strong deterrent to using the algorithm. This thesis aimed to decrease the false positive rate and, ultimately, increase the overall accuracy of Bedford's algorithm. Research Hypotheses: To the best of our knowledge, no study has focused on estimating the sample size required for Benford's Law. The first research hypothesis was that we could determine the required sample size for a Benford sample, at a given confidence level. The second research hypothesis was, given the required sample, whether we can improve the Benford algorithm's accuracy at a statistically significant level. Research Methodology: We do not know how fraudsters invent numbers. Our best assumption is that fraudsters invent numbers by randomizing data. This approach's advantage is that we can test our hypotheses objectively against other research papers. In order to test both hypotheses, we created a synthetic dataset of 100 vendors with a total of almost one million invoices and five datasets were randomized (i.e., fraud).

Fraud is an illegal activity that does not discriminate. It affects the global economy as well as all types of organizations. Surveys and reports by ACFE, Deloitte, KPMG and NFA confirmed that the public sector is more vulnerable to fraud compared to the private sector. Comments in the Auditor General’s (AG) Report 2012 concluded the same findings. Thus, with respect to fraud, detection, investigation, and preventive measures are extremely important. While anomalies or red flags act as indicators for the auditor, management and other responsible parties to investigate whether there is real fraud, auditing and statistics remain the two primary strategies for detecting fraud. Taking this perspective, Benford’s Law is an advanced digital analysis useful in uncovering anomalies. This paper evaluates 500 accounting data from public sector agencies in Malaysia using theFirst-Digit, Second-Digit, First-Two Digit, First-Three Digit and Last-Two Digit tests. Results show that Benford’s analy...

Cryptocurrencies have become a global phenomenon and its trading volume has been increasing since 2017 Aloosh and Li (2019). However, cryptocurrencies have been accused of market manipulation in the past. Benford's law is widely used for detecting probability of frauds and manipulation in various fields. This study applied Benford's law on trade volume of cryptocurrencies. Chi-square statistics revealed that except for Cardano and USDT all the other cryptocurrencies did not conform to the distribution and reveals the dataset could have been manipulated. This method may be used as the prerequisite before doing fine-grain screening such as machine learning and graph-based searching.

This paper presents the findings of an empirical study on the benefits, prospects and challenges of adoption of International Financial Reporting Standards (IFRS) in some African countries. A questionnaire was administered to gather data from respondents made up of users and preparers of accounting information using the Twitter social network. The objective was to find out the perception of users and preparers about what the benefits, prospects and challenges of IFRS adoption are in African countries. The results of the study indicate that IFRS adoption in Africa will have the potential to be beneficial to a wide range of stakeholders. The benefits notwithstanding, there are however, a number of challenges to be faced in the process of adoption of the new standard including the ethical environment in Africa. The study recommends among others that a rigorous IFRS capacity building programme should be embarked upon by all regulatory bodies, firms and training institutions in order to provide the needed manpower for IFRS implementation, monitoring and compliance.

Despite the increase in the level of awareness and general knowledge of the beneficiaries of financial affairs, the main issue in investing decisions is the high reliance on accounting report numbers (especially accounting profit as one of the main performance appraisal criteria) that creates many motivations for managers to manipulate (manage) these numbers in their favor. This study is an attempt to examine the extent of profit manipulation by considering the role of non-executive managers and the risk of stock price falls using Benford’s law and financial information of 1248 years of the listed companies during the years 2013-2020  in Tehran Stock Exchange. The results showed that the profit (loss) rate of the companies at risk of falling stock prices do not comply with Benford's law. However, the profit (loss) rate of companies without the risk of falling stock prices follow this law. The results also indicated that in companies with the risk of falling stock prices, differences with Benford's law were lower in cases where  the present proportion of non-executive managers was higher.

This research aims to investigate the overall and detailed financial disclosure status of Ethiopian companies against the IAS/IFRS standards. For the sake of achieving the objectives of this study, the detailed disclosure index has been adopted and analyzed using descriptive statistical methods. The disclosure index filled from a sample of 75 banking, insurance and ECX member companies&#39; annual financial reports of 2013/2014 GC (2006 EC). These 75 annual financial reports were selected from 20% from each of the 19 banks, 17 insurance and 343 ECX member companies using a simple random sampling technique. The literature analysis outlined the role of various local and international standards and regulatory bodies into the status of financial disclosure practices in Ethiopia. Various empirical studies have also been analyzed at the developed, developing and Ethiopian contexts. Therefore, the overall findings show that all the seventy five sampled companies have not fully complied wit...

Retail managers use psychological pricing to make the prices of goods appear to be just below a round number. The euro introduction in 2002, with its various exchange rates, distorted existing nominal price patterns while at the same time retaining real prices. We studied consumer prices before and after the introduction of the euro by using Benford's Law as a benchmark for price adjustments. Results indicate the usefulness of this benchmark for detecting irregularities in prices, and a clear trend towards psychological pricing after the nominal shock of the euro introduction. In addition, the tendency towards psychological prices results in different inflation rates in dependence of the price pattern.

h i g h l i g h t s • The Benford distribution is a particular case of a more general mathematical statement. • The exact Benford distribution is valid for the exponential function only. • Explicit expressions for frequencies are obtained for the power, logarithmic, and tangent functions. • The kinematic experiment illustrating proposed distributions is reported. • Analysis of leading digits frequencies in thermal conductivities of liquids data is presented.

This research is motivated by the application of countercyclical policy, such as credit restructuring, by banking companies during the COVID-19 pandemic. The credit restructuring that the banks carried out had the potential to affect their financial performance and increase the tendency of financial statement manipulations. The purpose of this study is to review the significance of the changes in banks’ financial performance before and after the implementation of the credit restructuring, as well as its relationship to the potential for fraudulent financial statements. The population in this study was the financial sector companies listed on the Indonesia Stock Exchange in 2020, a total of 105 companies. The 96 samples consisted of 32 banking companies in the commercial banking category that have implemented countercyclical policies in the form of credit restructuring during the COVID-19 pandemic. The research method was a quantitative method using secondary data obtained from the o...

Artificial neural networks and statistical techniques like decision trees, discriminant analysis, logistic regression and survival analysis play a crucial role in Business Intelligence. These predictive analytical tools exploit patterns found in historical data to make predictions about future events. In this paper we have shown some recent developments of a few of these techniques in financial and business intelligence applications like fraud detection, bankruptcy prediction and credit rating scoring.

This study analyzes the effect of bonus compensation on real earnings management, with the audit committee effectiveness as a moderating variable in manufacturing companies in Indonesia. The sample of this research is manufacturing companies listed on the Indonesia Stock Exchange from 2018 to 2020. The research sample was selected by the purposive sampling method. Hypothesis testing is done by using panel data regression and Moderated Regression Analysis (MRA). The results showed that bonus compensation had a positive effect on real earnings management, while the effectiveness of the audit committee did not weaken the effect of bonus compensation on real earnings management. The findings of this study provide an overview to the company's stakeholders that bonus compensation is one of the factors that motivates company management to practice earnings management, especially earnings management related to the company's real activities. In addition, this study also provides an overview of the effectiveness of the implementation of corporate governance mechanisms in the sample companies, in particular the ineffectiveness of the supervisory function related to earnings management practices carried out by the audit committee.

Corporate governance disclosure has become the buzz word for countries in developing economies, with the spate of corporate governance failures and the need to prevent a continuation of this trend. There has been the call for developing countries to enhance and improve on corporate governance disclosure practices. This study examines corporate governance disclosure in Ghanaian and Nigerian Banks using the un-weighted disclosure index technique. This research analyses corporate governance disclosure practices in the annual reports of 10 listed banks in Ghanaian and Nigerian banks in the year 2014. The findings of the research reveal that Ghanaian and Nigerian banks comply with several codes and principles of corporate governance disclosure: with Ghanaian banks having a lower level of disclosure than their Nigerian counterparts. On closer inspection, both Ghanaian and Nigerian banks have poor scores in voluntary corporate governance disclosure. Ghanaian banks tend to be worse off, as ...

The frequency of the first digits of numbers drawn from an exponential probability density oscillate around the Benford frequencies. Analysis, simulations and empirical evidence show that datasets must have at least 10,000 entries for these oscillations to emerge from finite-sample noise. Anecdotal evidence from population data is provided.