University of Macau / Faculty of Social Sciences and Humanities / Department of Government and Public Administration

增長層級式自我組織映射網路(GHSOM)屬於一種非監督式類神經網路，為自我組織映射網路(SOM)的延伸，擅長於對樣本分群，以輔助分析樣本族群裡的共同特徵，並且可以透過族群間存在的空間關係假設來建立分類器，進而辨別出異常的資料。 因此本研究提出一個創新的對偶方法(即為一個建立決策支援系統架構的方法)分別對舞弊與非舞弊樣本分群，首先兩類別之群組會被配對，即辨識某一特定無弊群體的非舞弊群體對照組，針對這些配對族群，套用基於不同空間假設所設立的分類規則以檢測舞弊與非舞弊群體中是否有存在某種程度的空間關係，此外並對於舞弊樣本的分群結果加入特徵萃取機制。分類績效最好的分類規則會被用來偵測受測樣本是否有舞弊的嫌疑，萃取機制的結果則會用來標示有舞弊嫌疑之受測樣本的舞弊行為特徵以及相關的輸入變數，以做為後續的決策輔助。 更明確地說，本研究分別透過非舞弊樣本與舞弊樣本建立一個非舞弊GHSOM樹以及舞弊GHSOM樹，且針對每一對GHSOM群組建立分類規則，其相應的非舞弊/舞弊為中心規則會適應性地依循決策者的風險偏好最佳化調整規則界線，整體而言較優的規則會被決定為分類規則。非舞弊為中心的規則象徵絕大多數的舞弊樣本傾向分布於非舞弊樣本的周圍，而舞弊為中心的規則象徵絕大多數的非舞弊樣本傾向分布於舞弊樣本的周圍。 此外本研究加入了一個特徵萃取機制來發掘舞弊樣本分群結果中各群組之樣本資料的共同特質，其包含輸入變數的特徵以及舞弊行為模式，這些資訊將能輔助決策者(如資本提供者)評估受測樣本的誠實性，輔助決策者從分析結果裡做出更進一步的分析來達到審慎的信用決策。 本研究將所提出的方法套用至財報舞弊領域(屬於財務舞弊偵測的子領域)進行實證，實驗結果證實樣本之間存在特定的空間關係，且相較於其他方法如SVM、SOM+LDA和GHSOM+LDA皆具有更佳的分類績效。因此顯示本研究所提出的機制可輔助驗證財務相關數據的可靠性。此外，根據SOM的特質，即任何受測樣本歸類到某特定族群時，該族群訓練樣本的舞弊行為特徵將可以代表此受測樣本的特徵推論。這樣的原則可以用來協助判斷受測樣本的可靠性，並可供持續累積成一個舞弊知識庫，做為進一步分析以及制定相關信用決策的參考。本研究所提出之基於對偶方法的決策支援系統架構可以被套用到其他使用財務數據為資料來源的財務舞弊偵測情境中，作為輔助決策的基礎。 / The Growing Hierarchical Self-Organizing Map (GHSOM) is extended from the Self-Organizing Map (SOM). The GHSOM’s unsupervised learning nature such as the adaptive group size as well as the hierarchy structure renders its availability to discover the statistical salient features from the clustered groups, and could be used to set up a classifier for distinguishing abnormal data from regular ones based on spatial relationships between them. Therefore, this study utilizes the advantage of the GHSOM and pioneers a novel dual approach (i.e., a proposal of a DSS architecture) with two GHSOMs, which starts from identifying the counterparts within the clustered groups. Then, the classification rules are formed based on a certain spatial hypothesis, and a feature extraction mechanism is applied to extract features from the fraud clustered groups. The dominant classification rule is adapted to identify suspected samples, and the results of feature extraction mechanism are used to pinpoint their relevant input variables and potential fraud activities for further decision aid. Specifically, for the financial fraud detection (FFD) domain, a non-fraud (fraud) GHSOM tree is constructed via clustering the non-fraud (fraud) samples, and a non-fraud-central (fraud-central) rule is then tuned via inputting all the training samples to determine the optimal discrimination boundary within each leaf node of the non-fraud (fraud) GHSOM tree. The optimization renders an adjustable and effective rule for classifying fraud and non-fraud samples. Following the implementation of the DSS architecture based on the proposed dual approach, the decision makers can objectively set their weightings of type I and type II errors. The classification rule that dominates another is adopted for analyzing samples. The dominance of the non-fraud-central rule leads to an implication that most of fraud samples cluster around the non-fraud counterpart, meanwhile the dominance of fraud-central rule leads to an implication that most of non-fraud samples cluster around the fraud counterpart. Besides, a feature extraction mechanism is developed to uncover the regularity of input variables and fraud categories based on the training samples of each leaf node of a fraud GHSOM tree. The feature extraction mechanism involves extracting the variable features and fraud patterns to explore the characteristics of fraud samples within the same leaf node. Thus can help decision makers such as the capital providers evaluate the integrity of the investigated samples, and facilitate further analysis to reach prudent credit decisions. The experimental results of detecting fraudulent financial reporting (FFR), a sub-field of FFD, confirm the spatial relationship among fraud and non-fraud samples. The outcomes given by the implemented DSS architecture based on the proposed dual approach have better classification performance than the SVM, SOM+LDA, GHSOM+LDA, SOM, BPNN and DT methods, and therefore show its applicability to evaluate the reliability of the financial numbers based decisions. Besides, following the SOM theories, the extracted relevant input variables and the fraud categories from the GHSOM are applicable to all samples classified into the same leaf nodes. This principle makes that the extracted pre-warning signal can be applied to assess the reliability of the investigated samples and to form a knowledge base for further analysis to reach a prudent decision. The DSS architecture based on the proposed dual approach could be applied to other FFD scenarios that rely on financial numbers as a basis for decision making.

在美國，會計師界多主張受到不公平的法律對待，一直到現在，他們對於未偵測到的重大財務報表誤述，多需負起「連帶賠償」的責任，因此近二十年來會計師團體一直極力爭取更為寬鬆的「比例賠償」制度，終於在最近幾年得到逐步地改善；但另一方面，投資人則擔心「比例賠償」制度的實施，將會使得投資人在面臨被告經理人沒有能力償還賠償時，無法從被告會計師身上取得補償而降低對其之保護。有鑑於此項議題之爭議不斷，本研究欲藉由檢視會計師法律責任會如何影響經理人的舞弊行為以及會計師的查核努力，以釐清會計師法律責任對審計失敗的影響。 本研究修正Patterson and Wright (2003)的分析模型，進一步以經理人策略性選擇舞弊金額的情況加入賽局模型，探討在審計品質只受會計師查核努力與其同時受到會計師查核努力和經理人舞弊金額的兩種審計情境下，不同會計師法律賠償責任對於會計師最適查核努力和經理人舞弊金額選擇之影響。 □ 本研究發現，無論在何種審計情境下，若會計師被裁定應負擔法律賠償比率與其早先的查核努力水準間有相當程度之敏感性時，則在比例賠償制度下，會計師的查核努力水準將會大於連帶賠償制度下所投入的水準，如此將使得財務報表的查核品質提升，增加對投資人事前的保護。本研究之結果希冀能提供國內主管機關在制訂會計師法律賠償責任時的參考依據。 / In America, the audit profession contends legal practices treat auditors unfairly. Until recently, they have been held jointly and severally liable for undetected material misstatements and have had to pay their own legal fees whether or not they prevail in court. Hence, they have asked for proportionate liability regime in decades and have got some success. A primary concern about proportionate liability is its potential effects on stockholders. Opponents claim that proportionate liability would decrease investor protection when managers are bankrupt due to the reduction in compensatory payments from auditors. Until now, this controversy still exists. To understand how auditor’s legal liability affects audit failure, this study focuses on the impacts of auditor’s legal liability on management fraud and audit effort. Based on Patterson and Wright (2003) analytical model, this study investigates the effectiveness of proportionate liability in reducing the amount of management fraud and the audit failure rate relative to joint and several liability in two strategic audit settings: one that audit quality is affected by audit effort and one that audit quality is affected by both audit effort and the amount of management fraud. My results show that a proportionate liability rule with large marginal liability relief for audit quality can effectively decrease the amount of management fraud and the audit failure rate relative to joint and several liability in both strategic audit settings. This result would provide valuable reference in auditor’s legal liability determination for policy-makers and regulators.

本研究將財務危機分為『經營不善型財務危機』以及『舞弊型財務危機』兩種類型，運用離散時間涉險方法，探討何種公司治理與財務資訊最有可能發生舞弊型的財務危機。同時本研究也探討財務危機對負債比率的敏感性如何受到公司治理中介變數的影響。 實證結果發現當公司治理機制情形不好，但財務報表資訊良好時，發生舞弊型財務危機的可能性將大於經營不善型的財務危機。而財務危機對負債比率的敏感度會受到公司治理中介變數的影響。 / With financial distress being classified as operating-failure financial distress and fraud financial distress, this study employs discrete-time survival model to characterize the fraud financial distress by corporate governance and financial performance. It also investigates the moderate effect of corporate governance on the sensitivity of financial distress to debt ratio. The empirical results indicate that companies with weak corporate governance and good financial performance are more likely to encounter fraud financial distress than operating-failure financial distress. In addition, corporate governance positively moderates the sensitivity of financial distress to debt ratio.

Financial reporting fraud leads to not only significant investment risks for external stockholders, but also financial crises for the capital market. Although the issue of fraudulent financial reporting has drawn much attention, relevant research is much less than issues of predicting financial distress or bankruptcy. Furthermore, one purpose of exploring the financial reporting fraud with various forms is to obtain a better understand of the corporate through investigating its financial and corporate governance indicators. This study addresses the challenge with proposing an approach with the following four phases: (1) to identify a set of financial and corporate governance indicators that are significantly correlated with the financial reporting fraud; (2) to use the Growing Hierarchical Self-Organizing Map (GHSOM) to cluster the normal and fraud listed corporate data; (3) to extract knowledge about the financial reporting fraud through observing the hierarchical relationship displayed in the trained GHSOM; and (4) to make the justification of the extracted knowledge. The proposed approach is feasible because researchers claim that the GHSOM can discover the hidden hierarchical relationship from data with high dimensionality.

University of Macau / Faculty of Social Sciences and Humanities / Department of Government and Public Administration

近年來海內外企業舞弊的新聞層出不窮，面對公司不斷發生的舞弊案件，必須思考、研究如何改變傳統稽核方法與工具，消極目的在協助董監事評估內控制度是否持續有效，積極目的在於執行舞弊專案稽核，進而強化公司之控制環境，逐步達到事前分析舞弊行為徵兆之可能。 本研究擬就資料倉儲之導入，建構個案集團公司內部稽核專屬資料倉儲，及藉由資料採礦分析軟體運用分析研究，挖掘出有價值的稽核元件知識；進一步完善持續性稽核的運作環境；為本研究動機所在。本研究將以跨全球經營之個案電子業集團公司為研究對象，從資料倉儲及資料採礦導入工作執行過程及內部稽核作業實際程序及分析結果加以研究，以下列議題進行相關分析探討： 議題一、個案電子業集團公司資料倉儲導入過程探討及成果分析 議題二、個案電子業集團公司導入資料採礦於內部稽核作業之運用分析 本研究較傳統單一議題或產業研究更具廣度，進而對更多在多面向內控舞弊查核議題上有興趣更深入探討的研究者，提供一個參考意見與研究方向。而以個案集團公司導入資料倉儲及資料採礦對內控循環作業中所涉及之集團內常見舞弊高風險交易作業(如：圍標、拆單等)的成果分析，廣泛運用於集團眾多事業群處及作業系統資料庫，是為本研究較為特殊之貢獻。 本個案研究係採取實地稽核作業實施方式，驗證資料倉儲及資料採礦導入分析結果。並歸納出多面向內控循環作業之舞弊查核、形成以風險評估為基礎之稽核計畫、專案舞弊查核結果再強化資料倉儲及資料採礦元件技術等研究結論。 / There is a competitive circumstance for all companies to face how to survive in the world, it includes the opening the marketing, competing with others, preventing from the internal fraud …and so on. Here is a study for the board of directors to focus on how to execute the internal auditing program to make everything perfect under control. To review lots of the prevailing fraud cases in past, a company must have its own opinions to adjust the suitable auditing program and to adopt the accurate detecting processing in order to strengthen the controlling power and narrow down the risk in advance. This study is how to establish the data input and then retrieve the useful information for further analysis based on the mega data bank in the prevailing system of one of public electronic companies in Taiwan. A company engages in the research and development of products, they can, pursuant to their need, add the research and development circle, including the control operation for the basic research, the design of products, the research of technology, the making and testing of products, the research/ development information, and the recording and storage of information in system. There are two main factor issues for further discussion and break it down as the following--- (1) The investigation on the practical data input and the analysis by the result (2) How to retrieve the data for the internal auditing purposes This subject study is different from the same case of the past in the electronic industry in Taiwan. If you scrutinize the details of this report, you will find out lots of fraud cases in the company and the accurate auditing program taken for each of them. There are very interesting and ambitious directions for the public people to consider and investigate in order to fit it in their own industries in future. There are lots of frauds happened in the progressing of the global biding or local biding. You are able to detect the fraud by the internal control points through the data analysis from the prevailing computer system. The result in group biding or separating biding, those activities are existed under controlled by the certain people for benefit themselves. This is a true case happened in Taiwan. The internal auditor of this company would adopt the appropriate auditing progressing by verifying the data warehousing and data mining. A service enterprise’s internal audit unit shall, based on the results of the fraud detecting, the risk assessment, to renew the auditing plan stipulated and designed by the subjected factor into the book.

財政透明度為建立一個良好政府治理的基礎。近年來隨著中國大陸高速的經濟發展，中央政府相關單位亦注意到財政公開的重要性。然而，目前中國財政資訊仍處於不透明的狀態。另一方面，中國大陸貪腐現象無所不在，內部腐敗行為更是日益猖獗，因此如何打擊貪腐、提升中國地方政府的財政透明度，就成為迫在眉睫的問題。 因此，本文的研究目的主要探討中國貪腐程度對地方政府財政透明度的影響：第一，瞭解當今社會對於財政透明度的提倡與國際規範；第二，考量貪汙與財政透明度之間可能存在非線性關係，建構一個追蹤平滑轉換迴歸模型（Panel Smooth Transition Regression Model，PSTR），瞭解中國大陸財政資訊的公開情形是否因各地區貪腐程度的不同而有所差異；最後，對於中國大陸嚴重的貪腐與財政透明度的關聯做深入探討，以期能為中國大陸財政不透明與不重視情況提出政策建議。

財務危機模型的研究一般納入財務正常公司與財務危機公司兩者當樣本，探討區分危機與正常公司的因素，本研究則進一步以財務危機公司為樣本，探討在財務危機公司中區分舞弊公司與正常經營公司的基本因素。 本研究從財務危機公司中，分出財務舞弊公司與正常經營公司，因此研究樣本包含發生舞弊的財務危機公司與正常經營而發生財務危機的公司。研究變數則從文獻篩選23個財務解釋變數，以及13個公司治理解釋變數，運用羅吉斯迴歸法進行實證，結果顯示3個財務變數和1個公司治理變數在區分財務危機公司中的財務舞弊公司與正常經營公司有顯著的區別能力，公司治理變數的董監事持股比率尤其顯著。 / Financial distress prediction is usually based on both financial distressed firms and non-distressed firms. Based on financial distressed firms, this study further investigates the factors distinguishing financial fraud firms from non-fraud firms. The sample includes fraud and no-fraud firms while both are financial distressed. Twenty-three financial and thirteen corporate governance variables are surveyed from literature. The empirical result of logit regression shows that three financial variables and one corporate governance variable are significant factors in distinguishing fraud from no-fraud firms in distressed companies. Especially, the percentage of holding stocks of board of directors is the most significant variable.

由於各國地雷股事件層出不窮，致使投資人財富遭受巨大損失，若是能事先察覺地雷股的存在，便能使投資人財富有更大的保障。本研究以四家國內外大型的舞弊個案－安隆、世界通訊、博達、力霸作為研究樣本，透過四家公司之財務資訊深入剖析各個案公司之舞弊手法。本研究歸納整理出21個預警指標，以作為未來投資人的評估基礎，以發現危機的早期徵兆，能及早避開地雷股。 研究發現即便是有進行窗飾財務報表的財務危機公司，仍能透過財務報導資訊中發現其端倪，四家個案公司在獲利性指標、流動性指標、安全性指標都有出現至少一項的紅旗警訊。研究結果顯示在下列指標上有較多家公司同時符合：(1) 獲利性指標。當資產報酬率以及股東權益報酬率過低或逐年下滑；(2)流動性指標。現金流量比率過低或逐年下滑；(3)安全性指標。借款依存度過高或逐年增加，以及流動比率過低或逐年下滑。 / Does financial reporting information itself provide early insightful information in detecting financial distress? Window dressing in financial reporting casts doubtful questions on this issue. As with investors usually taking a look at individual firm’s financial reporting, this study utilizes case study with four cases to address this fundamental role of financial reporting. Among the four fraud cases investigated, two are from the United States and the other two are Taiwan companies, including Enron, WorldCom, Procomp, and Rebar. This study sorts out 21 warning indices to evaluate each company’s financial condition and find out the signals for financial distress. All of these four cases investigated have at least one red flag signaled in profitability, liquidity and leverage. The most prominent indices in these three dimensions include (1) Profitability---ROE or ROA decreases in trend annully, (2) Liquidity---low cash flow ratio or decreasing in trend annually and low current ratio or decreasing in trend annually, and (3) Leverage---high debt to equity ratio or increasing in trend annually.