The evolutionary dynamics of audit

A critical issue in auditing is provisioning of reasonable assurance that the financial reports are free from material misstatements. The auditing detection problem can be viewed as a two-player game between the auditor and the auditee where the auditor aims at eliminating misstatements, reducing at the same time his audit efforts, while the auditee aims at benefiting from fraudulent financial reporting and defalcation.In this paper, the auditing/fraud detection problem is modeled employing evolutionary game theory. It is proved that, given that the players have accurate information for the parameters involved in the problem, the auditing/fraud detection game is stable but not asymptotically stable. The case of the auditor being partially informed about the auditee firm is also studied and it is concluded that if the auditor is partially informed about the auditee firm, a more comprehensive audit is necessary to guarantee quality of audit. Finally, analytical results are derived concerning the impact of audit tenure on audit quality.     

A benchmark-learning roadmap for the Military Finance Center

This paper aims to explore the operating efficiency and the benchmark-learning roadmap of military financial units for the finance center under the supervision of the Comptroller Bureau. A benchmarking managerial framework is developed and illustrated through application to the finance center. The framework encompasses a performance pyramid which embodies multiple perspectives of the organization under a balanced scorecard, data envelopment analysis, and cluster analysis. This assessment can assist the Comptroller Bureau to enhance the operational management of the finance center and to help military financial units deliver more efficient services, including the Armed Forces’ financial management, the audit of personnel-related expenditure, and the supervision and evaluation of the operation and financial management process. This paper highlights the potential applications and strengths of the methods used in assessing the military financial units.     

Multicriteria decision support methodologies for auditing decisions: The case of qualified audit reports in the UK

All UK companies are required by company law to prepare financial statements that must comply with law and accounting standards. With the exception of very small companies, financial accounts must then be audited by UK registered auditors who must express an opinion on whether these statements are free from material misstatements, and have been prepared in accordance with legislation and relevant accounting standards (unqualified opinion) or not (qualified opinion). The objective of the present study is to explore the potentials of developing multicriteria decision aid models for reproducing, as accurately as possible, the auditors’ opinion on the financial statements of the firms. A sample of 625 company audited years with qualified statements and 625 ones with unqualified financial statements over the period 1998–2003 from 823 manufacturing private and public companies is being used in contrast to most of the previous works in the UK that have mainly focused on very small or very large public companies. Furthermore, the models are being developed and tested using the walk-forward approach as opposed to previous studies that employ simple holdout tests or resampling techniques. Discriminant analysis and logit analysis are also used for comparison purposes. The out-of-time and out-of-sample testing results indicate that the two multicriteria decision aid techniques achieve almost equal classification accuracies and are both more efficient than discriminant and logit analysis.     

Defensive financial decisions support for retailers in Greek pharmaceutical industry

In this paper, we present a decisions support solution designed for Greek pharmacies comprising a cash flow management system for early warning of financial distress and a financial advisor based on a neural network. The cash flow monitoring system integrates accounting elements with real time transactions and a predictive linear regression model while the decision support module is developed with the help of a neural network. For any given business unit the system associates accounting entries with information about credit times to reflect the precise instants of cash flows and using inflows/outflows equations monthly, eventually build its liquidity curve and cash flow balance over time. Alongside, a linear regression module is introduced to estimate future cash reserves based on past profitability ratios. Lastly, combining the power of artificial neural networks with expertise in this sector of pharmaceutical business, the financial decision support tool focuses on the retailers that face financial difficulties and suggests alternative solutions for escaping from distress and insolvency. The model has an ambitious and useful purpose, to inform and consult the owners of the business units and other members of the pharmaceutical chain, thus reduce financial risk for the chain.     

A multi-criteria model for auditing a Predictive Maintenance Programme

Auditing tools can play a key role in the continuous improvement of maintenance policies, in particular to enhance predictive maintenance (PM). This paper proposes a multi-criteria model for auditing a Predictive Maintenance Programme (PMP) developed and implemented in the General Hospital of Ciudad Real (GHCR) in Spain. The model has a two-level structure, with top level auditing areas specified by second level auditing criteria on which the performance of the PMP should be appraised. This structure resulted from the analysis and discussion of an internal questionnaire to the management, technical and consulting staff of GHCR. This also guided the association of a performance scale with each criterion, describing several reference levels of accomplishment. Using the MACBETH (Measuring Attractiveness by a Categorical Based Evaluation Technique) approach, a hierarchical additive value model was constructed, with criteria weights and value scales derived from staff judgments of comparison of different reference levels and profiles of performance. This model enables managers to measure the performance of the PMP and its added value for the hospital, not only against each audit criterion individually, but also on each area and in overall terms. Integrated in a management “tableau de bord”, the model outputs permit the identification of PMP deficiencies requiring urgent intervention and corrective measures for its continuous improvement.     

审计意见、高管财务背景与内部控制缺陷修正

文章运用2010~2014年度沪深两市A股上市公司的相关数据,首先检验了审计意见与内部控制缺陷修正之间的相关性,结果表明上年收到“不清洁”审计意见的企业在当年更有可能进行内控缺陷的整改与修正;进一步通过分组回归发现,高管中具有财务背景特征的成员比例越高,进行缺陷整改的概率更大,一方面表明外部审计非标准审计意见对内部控制治理效用可能赖于管理层的配合,另一方面也折射出高管人力资源有效配置的重要性。而对披露缺陷修正信息的企业进行跟踪研究,发现这类企业在后续年度仍然会收到“不清洁”的审计意见,反映出这些上市公司的缺陷整改可能浮于表面,并不是实施有效的。     

A Minimum-Cost Analysts Assignment Model for Asset Evaluation of Insolvent Saving and Loan Institutions

Audit staff planning has been a challenging problem for accounting, auditing and real estate firms. This paper presents a mathematical model and a solution methodology for determining the minimum-cost analysts assignment, when analysts should travel from geographically dispersed locations to evaluate assets of an insolvent Saving and Loan institution. Computational experiments with the solution algorithm on 27 randomly generated projects show (a) that the solution methodology efficiently generates an optimal solution, and (b) provides the decision maker with alternative next best plans through ex post sensitivity analysis. Although specific, variations of the model and algorithm presented here can be applied to a variety of audit staff assignment problems in accounting and real estate firms.     

Linking customer satisfaction, employee appraisal, and business performance: an evaluation methodology in the banking sector

The linkage among customer satisfaction, employee evaluation, and business performance data is very important in modern business organizations. Several previous research efforts have studied this linkage, focusing mainly on the financial or business performance in order to analyze the efficiency of an organization. However, recent studies have tried to consider other important performance indicators, which are able to affect business operations and future growth (e.g., external and internal customer satisfaction). In the case of the banking industry, studying the relations among the aforementioned variables is able to give insight in the performance evaluation of bank branches and the viability analysis of the banking organization. This paper presents a real-world study for measuring the relative efficiency of a set of bank branches using a Data Envelopment Analysis (DEA) approach. In particular, a multistage DEA network model is proposed, using a set of performance indicators that combine customer satisfaction, employee evaluation, and business performance indices. The main aim of the presented study is to evaluate the relative efficiency of each customer service delivery step, in the environment of a bank branch. The results are also able to estimate the contribution of the assessed performance indicators to the branch’s overall efficiency, and to determine potential improvement actions.     

公司盈余质量:董事会微观治理绩效之考察——来自我国独立董事制度强制性变迁的经验证据

本文选用我国上市公司董事会结构变迁背景下的经验数据,系统地考察了董事会特征对公司盈余信息披露质量的治理效应问题.研究结果表明,董事会的独立性、专业性特征是影响我国上市公司财务呈报质量的重要因素,即:公司拥有更高比例的独立董事、拥有财务独立董事、或者设立审计委员会,均能更好地抑制公司的盈余管理行为;但作为表征董事会行为特征的变量,如董事会持股水平、董事会年度会议频率和兼任控股股东职务等,却与公司盈余质量之间没有显著关系;而且,在认同审计委员会与独立董事制度能够发挥财务报告监督作用的同时,亦要避免其形式上的装饰现象。     

Explanation of exceptional values in multi-dimensional business databases

In this paper, we describe an extension of the OnLine Analytical Processing (OLAP) framework with causal explanation, offering the possibility to automatically generate explanations for exceptional cell values. This functionality can be built into conventional OLAP databases using a generic explanation formalism, which supports the work of managers in diagnostic processes. The central goal is the identification of specific knowledge structures and reasoning methods required to construct computerized explanations from multi-dimensional data and business models. The methodology was tested on a case study involving the comparison of financial figures of a firm’s business units. The findings suggest improved decision-making by managers because the current tedious and error-prone manual analysis process is enhanced by automated problem identification and explanation generation. It is also noted that this novel methodology has general utility for decision-support systems, for example, for automated diagnosis in the financial and accountancy domain.     

Proactive data envelopment analysis: Effective production and capacity expansion in stochastic environments

Demand fluctuations that cause variations in output levels will affect a firm’s technical inefficiency. To assess this demand effect, a demand-truncated production function is developed and an “effectiveness” measure is proposed. Often a firm can adjust some input resources influencing the output level in an attempt to match demand. We propose a short-run capacity planning method, termed proactive data envelopment analysis, which quantifies the effectiveness of a firm’s production system under demand uncertainty. Using a stochastic programming DEA approach, we improve upon short-run capacity expansion planning models by accounting for the decreasing marginal benefit of inputs and estimating the expected value of effectiveness, given demand. The law of diminishing marginal returns is an important property of production function; however, constant marginal productivity is usually assumed for capacity expansion problems resulting in biased capacity estimates. Applying the proposed model in an empirical study of convenience stores in Japan demonstrates the actionable advice the model provides about the levels of variable inputs in uncertain demand environments. We conclude that the method is most suitable for characterizing production systems with perishable goods or service systems that cannot store inventories.     

Sequential sampling schemes and other statistical techniques in quality of service business surveys

While there is a general consensus in the business community regarding the importance of quality service surveys in improving the company's business results, relatively little attention was devoted to the theoretical aspects of data analysis and modelling which can increase substantially the effectiveness of those surveys. Using the data from a real‐life project, we present here the developments and improvements achieved in the three stages that ultimately yield the conclusions from the survey: the analysis of the historical data, the design of the sampling method for the current survey and the development of specific indices for differentiating among the units of the financial institution. The statistical techniques fitted to historical data helped both in assessing the relative contributions of the various aspects of service, the overall perceived quality of service, as well as in providing the theoretical grounds for reducing the size of the questionnaire and thus increasing the reliability of the received replies. The sequential sampling scheme designed for this survey was particularly suitable to address the managements concerns. Finally, the classes of quality service based on the quality indices developed in the project contributed substantially to the ability of the management to rank and reward differentially the branches of the financial institution. Copyright © 2002 John Wiley & Sons, Ltd.     

Evaluating business performance of wealth management banks

This study applies the balanced scorecard method to build a performance evaluation framework for wealth management (WM) banks. Next, the study builds a framework for dealing with sub-criteria using the Delphi method and finally, the article evaluates the business performance of WM banks in Taiwan by applying the analytical hierarchy process (AHP) and grey relational analysis (GRA). Importantly, the proposed model can benefit the banking sector in assessing the business performance of WM banks, making it highly applicable for bank managers and financial sector analysts.     

A preference disaggregation decision support system for financial classification problems

Classification is one of the most extensively studied problems in the fields of multivariate statistical analysis, operations research and artificial intelligence. Decisions involving a classification of the alternative solutions are of major interest in finance, since several financial decision problems are best studied by classifying a set of alternative solutions (firms, loan applications, investment projects, etc.) in predefined classes. This paper proposes an alternative approach to the classical statistical methodologies that have been extensively used for the study of financial classification problems. The proposed methodology combines the preference disaggregation approach (a multicriteria decision aid method) with decision support systems. More specifically, the FINancial CLASsification (FINCLAS) multicriteria decision support system is presented. The system incorporates a plethora of financial modeling tools, along with powerful preference disaggregation methods that lead to the development of additive utility models for the classification of the considered alternatives into predefined classes. An application in credit granting is used to illustrate the capabilities of the system.     

A quantitative model of accelerated vehicle-retirement induced by subsidy

A number of accelerated vehicle-retirement programs have been implemented by private companies and public agents to reduce pollution and promote environment friendly technology. Our paper examines subsidy programs for the acquisition of a new low-pollution vehicle, provided that an old technology unit is retired. A model is developed to determine the appropriate subsidy level that induces the replacement of a specified number of existing old technology units within a given time period. Alternatively, given the subsidy level, the model allows the determination of the required time period to achieve a desired replacement target. In this way, the proposed method could be used to assess the effectiveness of a subsidy-based policy of accelerated vehicle-retirement in reaching a targeted number of scraped vehicles within a specified time framework.     

Statutory financial reporting for variable annuity guaranteed death benefits: Market practice,mathematical modeling and computation

As more regulatory reporting requirements for equity-linked insurance move towards dependence on stochastic approaches, insurance companies are experiencing increasing difficulty with detailed forecasting and more accurate risk assessment based on Monte Carlo simulations. While there is vast literature on pricing and valuations of various equity-linked insurance products, very few have focused on the challenges of financial reporting for regulatory requirement and internal risk management. Most insurers use either simulation-based spreadsheet calculations or employ third-party vendor software packages. We intend to use a basic variable annuity death benefit as a model example to decipher the common mathematical structure of US statutory financial reporting. We shall demonstrate that alternative deterministic algorithms such as partial differential equation (PDE) methods can also be used in financial reporting, and that a fully quantified model allows us to compare alternatives of risk metrics for financial reporting.     

Does cooperation in auditing matter? A comparison of a non-cooperative and a cooperative game model of auditing

A game model of auditing including internal control investigation and substantive testing is analysed as a non-cooperative game. It is shown that in order for the presumed socially desirable outcome of high and honest effort by all to be obtained, it is necessary to adjust the cost structure to ameliorate the costs of not-qualifying erroneous accounts if the auditor can prove he or she has worked hard. Comparison with a cooperative game analysis of the model shows that there is a region of parameters where both cooperative and non-cooperative versions of the game lead to this socially desirable outcome. The significance of this result is that whilst society expects an ‘independent’ auditor not to cooperate with the auditee, the practical realities of auditing require a considerable degree of cooperation. This leads to an ‘expectations gap’ between what society expects and what actually happens, except in those cost regions where both the cooperative and non-cooperative versions of the audit game lead to the same solution.     

Analysing the impact of the implementation of lean manufacturing strategies on profitability

Under standard cost accounting systems, reductions in inventories lead to falling reported profits. Rapid reductions in inventories intensify the impact to the bottom line. When a company embarks on an improvement programme such as lean manufacturing, a likely result will be an initial drop in reported profits due to the leaning out of inventories. This paper examines the impact of the adoption of such strategies on the key external financial performance measure of net profit as reported by the GAAP and SEC approved financial accounting methods and others. ANOVA analysis of data generated using a simulated manufacturing environment that includes a discrete event model of a manufacturing operation and a Microsoft Excel-based ERP system are discussed. The paper analyses both the magnitude of the reduction in reported profits and the span of reporting periods affected under three inventory reduction scenarios. This research was not concerned with finding justification for lean manufacturing strategies. Rather, it evaluates the inadequacies of standard financial reporting methods to accurately reflect operational improvements through the early stages of a lean programme.     

A hybrid multiple-criteria decision analysis framework for corporate social responsibility implementation applied to an extractive industry case study

Integration of corporate social responsibility (CSR) into a company’s mainstream strategy is a complex task. Practical implementation of CSR requires analysis of both the external and internal environments to determine the prospects and challenges significantly influencing integration of sustainability into business strategy. In order to overcome limitations of single multiple-criteria decision analysis models, this paper proposes a hybrid integrated framework combining cognitive mapping and analytic networks process (ANP) to determine, prioritise and select CSR programmes for implementation. The strategic cognitive map serves as a foundation to build the ANP network and identify the importance of CSR programmes. A knapsack optimisation method is then used to optimally assign resources to CSR alternatives. We demonstrate the usefulness of the framework through a case study in the extractive sector. The framework was empirically tested with 61 respondents using postal and online surveys, MBA workshops, and conference networking.     

Hedging mortality/longevity risks of insurance portfolios for life insurer/annuity provider and financial intermediary

In this paper, we propose two risk hedge schemes in which a life insurer (an annuity provider) can transfer mortality (longevity) risk of a portfolio of life (annuity) exposures to a financial intermediary by paying the hedging premium of a mortality-linked security. The optimal units of the mortality-linked security which maximize hedge effectiveness for a life insurer (an annuity provider) can be derived as closed-form formulas under the risk hedge schemes. Numerical illustrations show that the risk hedge schemes can significantly hedge the downside risk of loss due to mortality (longevity) risk for the life insurer (annuity provider) under some stochastic mortality models. Besides, finding an optimal weight of a portfolio of life and annuity business, the financial intermediary can reduce the sensitivity to mortality rates but the model risk; a security loading may be imposed on the hedge premium for a higher probability of gain to compensate the financial intermediary for the inevitable model risk.