DATA QUALITY IN FINANCIAL PLANNING - AN EMPIRICAL ASSESSMENT BASED ON BENFORD\u27S LAW

Planning Processes play an important role in almost any business scenario. In particular, induced by the financial crisis, financial planning as a foundation for liquidity management is paid extraordinary attention to. Its quality and reliability is usually ensured by the use of information systems. Besides process efficiency, a key factor in liquidity management is the quality of the delivered planning data. More recently, business intelligence measures to increase data quality, for instance, realized through decision support services, find their way into the planning process. In this paper, we lay the foundation to include digital analyses of reported financial planning numbers into automated decision support services. In this vein, our contribution is twofold: First, based on a large and representative data set from a renowned, multinational enterprise, we empirically prove that financial planning numbers exhibit a certain, characteristic digit distribution, namely, Benford\u27s Law. Second, we investigate whether decision support services that incorporate intelligence based on Benford\u27s Law are appropriate to increase financial planning data quality. This question is tackled via analyses that relate detailed properties of the delivered data to Benford\u27s Law as a prerequisite for the integration of automated decision support services into business intelligence systems

Auditing Symposium XIII: Proceedings of the 1996 Deloitte & Touche/University of Kansas Symposium on Auditing Problems

Meeting the challenge of technological change -- A standard setter\u27s perspective / James M. Sylph, Gregory P. Shields; Technological change -- A glass half empty or a glass half full: Discussion of Meeting the challenge of technological change, and Business and auditing impacts of new technologies / Urton Anderson; Opportunities for assurance services in the 21st century: A progress report of the Special Committee on Assurance Services / Richard Lea; Model of errors and irregularities as a general framework for risk-based audit planning / Jere R. Francis, Richard A. Grimlund; Discussion of A Model of errors and irregularities as a general framework for risk-based audit planning / Timothy B. Bell; Framing effects and output interference in a concurring partner review context: Theory and exploratory analysis / Karla M. Johnstone, Stanley F. Biggs, Jean C. Bedard; Discussant\u27s comments on Framing effects and output interference in a concurring partner review context: Theory and exploratory analysis / David Plumlee; Implementation and acceptance of expert systems by auditors / Maureen McGowan; Discussion of Opportunities for assurance services in the 21st century: A progress report of the Special Committee on Assurance Services / Katherine Schipper; CPAS/CCM experiences: Perspectives for AI/ES research in accounting / Miklos A. Vasarhelyi; Discussant comments on The CPAS/CCM experiences: Perspectives for AI/ES research in accounting / Eric Denna; Digital analysis and the reduction of auditor litigation risk / Mark Nigrini; Discussion of Digital analysis and the reduction of auditor litigation risk / James E. Searing; Institute of Internal Auditors: Business and auditing impacts of new technologies / Charles H. Le Grandhttps://egrove.olemiss.edu/dl_proceedings/1012/thumbnail.jp

Effective methods for detecting fraudulent financial reporting: practical insights from Big 4 auditors

Purpose Using a qualitative grounded theory approach, this study explores the methods experienced external auditors use to detect fraudulent financial reporting (FFR) during standard audits. Design/methodology/approach Semi-structured interviews were conducted with 24 experienced external auditors to explore the methods they used to detect FFR successfully during standard external audits. Findings The authors find 58 methods used for FFR detection, out of which the following methods are frequently used and help in detecting more than one type of FFR: (1) specific analytical procedures, (2) positive confirmation, (3) understanding of the client's business and industry, (4) the inspection of specific documents, (5) a detailed analysis of the audit client's anti-fraud controls and (6) investigating tip-offs from suppliers, employees and customers. Research limitations/implications Based on the grounded theory approach, the authors theorise that auditors must return to the basics and focus on specific audit procedures highlighted in this study for effective fraud detection. Practical implications The study provides practical guidance, including 58 methods used in audit practice to detect FFR. This knowledge can improve auditors' skills in detecting material misstatements due to fraud. Besides, analytical procedures and positive confirmation helped external auditors in this study detect all forms of FFR, yet they are overlooked in the external audit practice. Therefore, audit firms should emphasise the significance of these audit procedures in their professional audit training programmes. Audit regulators should advise auditors to consider positive confirmation instead of negative confirmation in financial audits to increase the likelihood of FFR detection. Moreover, audit standards (ISA 240 and SAS 99) should explicitly require auditors to conduct a detailed analysis of the client's anti-fraud controls. Originality/value This is the first study to identify actual, effective methods used by external auditors in detecting FFR during the ordinary course of an audit

The Usefulness Of Analytical Procedures, Other Than Ratio And Trend Analysis, For Auditor Decisions

The International Standards on Auditing require of the external auditor to perform analytical procedures during audits. Analytical procedures range from simple to advanced, but available literature focuses on ratio and trend analysis for use in audits. This study therefore aims to analyse and compare the objective, advantages and disadvantages of selected analytical procedures other than ratio and trend analysis (Du Pont, Economic Value AddedTM (EVA), Altman’s Z-score and Benford’s Law) in an external auditing context by means of a qualitative literature analysis. Findings indicate that further analytical procedures significantly compliment ratio and trend analysis during audits, specifically during going concern evaluations and identifying error and fraud. Du Pont, Altman’s Z-score and Benford’s Law is found to be of particular value to the auditor, due to its cost benefit. EVA is found to be impractical to utilise by the auditor if not implemented by the entity. The study is an important contribution to the literature on analytical procedures as it is the first of its kind to analyse the objective, advantages and disadvantages of analytical procedures other than ratio and trend analysis in an external auditing context

A conceptual model for proactive detection of potential fraud enterprise systems: exploiting SAP audit trails to detect asset misappropriation

Fraud costs the Australian economy approximately $3 billion annually, and its frequency and financial impact continues to grow. Many organisations are poorly prepared to prevent and detect fraud. Fraud prevention is not perfect therefore fraud detection is crucial. Fraud detection strategies are intended to quickly and efficiently identify frauds that circumvent preventative measures so that an organisation can take appropriate corrective action. Enhancing the ability of organisations to detect potential fraud may have a positive impact on the economy. An effective model that facilitates proactive detection of potential fraud may potentially save costs and reduce the propensity of future fraud by early detection of suspicious user activities. Enterprise systems generate millions of transactions annually. While most of these are legal and routine transactions, a small number may be fraudulent. The enormous number of transactions makes it difficult to find these few instances among legitimate transactions. Without the availability of proactive fraud detection tools, investigating suspicious activities becomes overwhelming. This study explores and develops innovative methods for proactive detection of potential fraud in enterprise systems. The intention is to build a model for detection of potential fraud based on analysis of patterns or signatures building on theories and concepts of continuous fraud detection. This objective is addressed by answering the main question; can a generalised model for proactive detection of potential fraud in enterprise systems be developed? The study proposes a methodology for proactive detection of potential fraud that exploits audit trails in enterprise systems. The concept of proactive detection of otential fraud is demonstrated by developing a prototype. The prototype is a near real-time web based application that uses SAS for its analytics processes. The aim of the prototype is to confirm the feasibility of implementing proactive detection of potential fraud in practice. Verification of the prototype is achieved by performing a series of tests involving simulated activity, followed by a full scale case study with a large international manufacturing company. Validation is achieved by obtaining independent reviews from the case study senior staff, auditing practitioners and a panel of experts. Timing experiments confirm that the prototype is able to handle real data volumes from a real organisation without difficulty thereby providing evidence in support of enhancement of auditor productivity. This study makes a number of contributions to both the literature and auditing practice

Tax evasion by small and medium sized enterprises (SMEs) and the role of forensic accounting : the Malaysian perspective

The aim of this research is to identify and define the characteristic behaviour of and factors that influence taxpayers in small and medium-sized enterprises (SMEs) when they either evade tax or comply with tax law. The study also attempts to assess the extent of tax evasion by SMEs in Malaysia. In addition, another concern is also to explore both the actual and potential role of forensic accounting with the focus on improving current enforcement strategies for deterring tax evasion by SMEs. The research findings will contribute to the current limited literature on the tax compliance of SMEs and forensic accounting, especially with respect to Malaysia. Using a multi-method approach, the results of this thesis suggest that the extent of tax evasion by SMEs in Malaysia is both widespread and frequent. The findings also indicate that the offences tend to be deliberate evasion without any sophisticated tax-planning scheme. Understatement of gross profit and overstatement of expenses other than the cost of goods sold are the most frequently used methods. The fact that most taxpayers are unlikely to be detected and penalised by the tax authority is also another factor shaping tax evasion by SMEs. Most SMEs are heavily reliant on tax practitioners to guide them to comply with their income tax matters and will remain with the same tax practitioner in general; however, there is a tendency for some to switch tax practitioner for whatever reason they think fit. Forensic accounting is a field that encapsulates all other areas in the use of accounting for investigative purposes. Forensic accounting is a relatively new discipline in Malaysia; however, the awareness of forensic accounting by tax practitioners and IRB (Inland Revenue Board Malaysia) personnel is strong. The techniques used in forensic accounting are not new to the IRB; however, the IRB personnel need further exposure to and training in these techniques. The finding indicates a lack of sophisticated planning in tax evasion by SMýs in Malaysia. Despite this, forensic accounting technique could be added to the existing tools necessary to bring about the successful investigation and prosecution of those involved. The study was carried out at a time of change for the IR

Do better-performing nongovernmental organizations report more accurately? Evidence from financial accounts in Uganda

We use Benford’s Law to investigate inaccurate financial reports of a representative sample of Ugandan nongovernmental organizations (NGOs). We find that 25% of the sample provided information that did not conform to the Benford distribution, suggesting potential misreporting. NGOs with better ratings from their beneficiaries are more likely to submit credible information. This contradicts the belief that upward accountability demands crowd out serving the client community. The decision to withhold requested information is unrelated to the decision to report inaccurately, with the latter attributed to limited capacity and skills. Policies should provide larger roles for beneficiary-based assessments and increased support for bookkeeping activities

Computer-assisted audit tools and techniques use: Determinants for individual acceptance

During the last fifteen years, several studies on the research topic of Individual Technology Acceptance have been developed, and several new models have been proposed. All these models aim to understand and define determinant contributions for the acceptance of technologies and what the drivers leading to successful adoption are. This dissertation’s main emphasis is to gain an understanding of individual acceptance of Computer-assisted Audit Tools and Techniques (CAATTs) in the context of Portuguese Statutory Auditors. Previous research in other countries, utilizing several and distinct research universes, has informed this work and the definition of the main objectives of the present research. This dissertation has as its main objectives: 1) understanding the tasks in which CAATTs are used; 2) to identify the adoption drivers of CAATTs; 3) to explore the current usage of CAATTs among statutory auditors and 4) to develop a CAATTs adoption model. To reach the objectives two studies were conducted: a qualitative study, supported by interviews to experts, and a quantitative study operationalized by a questionnaire to 110 Portuguese statutory auditors. This latter study was the cornerstone, which allowed testing the CAATTs acceptance model. This dissertation presents significant contributions impacting the various stakeholders: individual Statutory Auditors, Statutory Auditors Firms, The Portuguese Institute of Statutory Auditors, Software houses and higher education.Nos últimos 15 anos, vários estudos de investigação foram desenvolvidos abordando a temática da aceitação individual de tecnologia, tendo sido apresentados novos modelos. Esses modelos têm como objetivo compreender e identificar os determinantes sobre a aceitação de tecnologias que levem a uma adoção bem-sucedida. A principal ênfase da tese é compreender a aceitação individual de “Tecnologias de Informação para Auditoria”, também designadas, em Português, por “Ferramentas Informáticas de Suporte à Auditoria” ou “Técnicas de Auditoria Assistidas por Computador” (CAATT), no contexto dos Revisores Oficiais de Contas em Portugal. Investigações anteriores realizadas em diferentes países, com distintos universos de investigação, inspiraram este trabalho na definição dos principais objetivos da presente pesquisa. A presente dissertação tem como principais objetivos compreender as tarefas em que as CAATT são utilizadas; identificar os fatores de adoção de CAATT; explorar o atual uso de CAATT entre Revisores Oficiais de Contas e desenvolver um modelo de adoção de CAATT. Para alcançar estes objetivos foram realizados dois estudos: um estudo qualitativo e exploratório, apoiado por entrevistas com peritos, e um estudo quantitativo operacionalizado através de um questionário a 110 Revisores Oficiais de Contas portugueses. Este estudo foi a pedra angular que permitiu testar o modelo de aceitação de CAATT. Esta dissertação apresenta contribuições significativas com impactos para os principais stakeholders: Revisores Oficiais de Contas, empresas, Ordem dos Revisores Oficiais de Contas, software houses e instituições de ensino superior

Detection of fraudulent financial papers by picking a collection of characteristics using optimization algorithms and classification techniques based on squirrels

To produce important investment decisions, investors require financial records and economic information. However, most companies manipulate investors and financial institutions by inflating their financial statements. Fraudulent Financial Activities exist in any monetary or financial transaction scenario, whether physical or electronic. A challenging problem that arises in this domain is the issue that affects and troubles individuals and institutions. This problem has attracted more attention in the field in part owing to the prevalence of financial fraud and the paucity of previous research. For this purpose, in this study, the main approach to solve this problem, an anomaly detection-based approach based on a combination of feature selection based on squirrel optimization pattern and classification methods have been used. The aim is to develop this method to provide a model for detecting anomalies in financial statements using a combination of selected features with the nearest neighbor classifications, neural networks, support vector machine, and Bayesian. Anomaly samples are then analyzed and compared to recommended techniques using assessment criteria. Squirrel optimization's meta-exploratory capability, along with the approach's ability to identify abnormalities in financial data, has been shown to be effective in implementing the suggested strategy. They discovered fake financial statements because of their expertise