PE-EDD:An efficient peer-effect-based financial fraud detection approach in publicly traded China firms

Financial fraud arises from the exaggeration of business interests,and an accurate detection or prediction is a useful tool for both corporate management and capital market systems.A collection of computer technologies has been made on this problem so far,and one of the most important solutions is unsupervised learning algorithms.Among them,most approaches work by analysing the internal relations in financial data and finding a new description of non-fraud firms.However,current studies focus a lot on the geometry attribute of financial data,while overlooking the obvious behaviour patterns and peer effects among firms.This has limited the accuracy of representation and furthermore the detection performance.In this work,a very general class of functions is allowed to represent firms,constraining them by peer effects between firms and presenting an error-distribution-based financial fraud firm detection approach.Experimental results have shown great performance of the proposed approach.

Financial Statements Frauds: Does Their Intensity Have a Connection with Earnings Management?

This study investigates the relationship between earnings management and financial statements frauds.We examine how earnings management practices;done in the two years before the fraud,impact the likelihood of fraud occurrence.Moreover,we introduce a new measure for the fraud intensity.Using a sample of 70 fraud and 70 no-fraud firms,we find that firms committing fraud of higher intensity have managed earnings in the two years before the fraud occurrence.This paper contributes to the literature about fraud antecedents because it is the first study measuring the relationship between earnings management and the intensity of the fraud,and it can be also useful for practitioners,because using the analysis of earnings management practices,analysts can foresee and prevent financial statements frauds.

Financial Statement Fraud: Lessons Learned from Selected U.S. Legal Cases in the past Twenty Years

The researcher analysed selected U.S.court cases of financial statement fraud from the past twenty years and concluded:(1)U.S.laws used to prosecute financial statement fraudsters include the Securities Act,Securities Exchange Act,S.E.C.Rule 10b-5,Investment Advisers Act,Private Securities Litigation Reform Act,and the Sarbanes-Oxley Act;(2)financial statement fraud schemes included use of unconsolidated special-purpose entities to conceal debt,improper revenue recognition in leasing of bandwidth in the telecom industry,improper accounting for goodwill in a merger,failure to write off a large amount of bad receivables,excessive recognition of revenue in bundled leases in the photocopier industry,use of loss contingency reserves to inflate current income,use of fictitious revenue to overstate earnings,and capitalising a project’s operating expenses to hide cost overruns;(3)to be liable for financial statement fraud,a corporate officer must have knowledge;and(4)employees discharged for reporting financial statement fraud may sue under the Sarbanes-Oxley Act.

Effectiveness of the Financial Ratios in the Determination of the Fraudulent Financial Statements＂ Turkey Practice

Large-scale accounting scandals which were reflected to the world public opinion particularly in the 2000s （such as Enron, Lucent, Xerox, and Parmalat Bank for Reconstruction） carried the matter of fraudulent financial reporting which was made to deceive the financial statement users （Fraudulent Financial Report （FFR）） to the forefront in the agenda of the academicians, operators, and regulatory authorities. As in every crime action, the most effective measure to be taken in preventing FFR events is to try to prevent the FFR before arising. In order to achieve this, in the most effective manner, FFR events should be determined in the formation process. In this study, fraudulent financial statements are tried to be determined by using financial ratios. For this, financial statements of 22 companies which transact in the textile industry in Istanbul Stock Exchange （ISE） were examined. Twenty-three financial ratios were selected for the purpose of determining the risk of fraudulence in the financial statements of the selected companies. These ratios increased in value by multiple regression analysis. The findings which were obtained in the study indicated that some financial statements had the risk of fraudulence. It was concluded that the ratios of inventory/current asset, total debt ratio, and equity turnover rate were a good indicator in the determination of fraudulent financial statements.

Study on how to elevate the discriminating ability of the discriminating model of the financial statement fraud

By summarizing the factor of the financial statement fraud in existing research outcome, the paper confirms the discriminating characteristic of the financial statement fraud and sets up a theoretic model to discriminate the financial statement fraud. Using radial basis function neural network, regarding to the swatch that the listed company that is punished by the Securities Regulatory Commission or the Ministry of Finance, and according to the clustering elements, validating across by set one aside, the paper verifies respectively the 22 characteristics and 31 characteristics of discriminating model. According to the clustering elements, validating across by set one aside, the paper verifies respectively the 31 characteristics and 8 characteristics selected by Fisher-ratio of discriminating model. The research outcome indicates the discriminating ability of the model including 8 characteristics is better elevated than the traditional model including 31 characteristics by comparing the disciplinary error and the forecast precision.

Positive Research on the Financial Statement Fraud Factors of Listed Companies in China

This paper studied the ＂pressure＂ and ＂opportunity＂ factors that caused financial statement fraud on the basis of the data of 41 A-share listed companies （1999-2004） in China which had been forfeited by China Securities Regulatory Commission （SRC） because of accounting irregularities. The author found that avoiding ＂ST＂ and ＂PT＂ was the primary pressure, and the opportunities mainly came from the higher top 10 shareholders＇ ownership concentration, the lower proportion of independent directors, the fewer number of directorate meetings and shares owned by the directorate members, board chairman and CEO held by one person and the ineffective supervisor boards. We also found that the companies involved financial statement fraud had the lower first majority shareholder＇s share proportion and they changed CPA firm more frequently.

Luckin Coffee:A Study of the Reasons for Committing Financial Fraud and Solutions for Getting Out of a Financial Crisis

Luckin Coffee grew rapidly in the past few years and it was the fastest Chinese Concept company go public in NASDAQ.However,its stock price plunged in 2020 due to financial fraud.It is crucial for Luckin Coffee to think about how to recover from the financial fraud and become a business representative of the“new retail”under the Internet model again.To recover from the financial crisis caused and gain profit,Luckin could improve its existing business model by improving product development,strengthening capital management in both marketing and expansion.The internal structure can also be adjusted by diversifying equity and replacing the manager team.Taking Luckin Coffee as an example,this paper analyzes the causes of financial fraud,propose solutions to recover from it,and evaluate the effectiveness of solutions in the context of reality.

Toshiba and Luckin Coffee: A Study of the Reasons for Committing Financial Fraud

Financial fraud,which has become a global issue,is a subject of discussion,surpassing time.Financial fraud significantly undermines investors’confidence and affects the health of capital markets.Hence,it is valuable to explore the reasons for committing financial fraud and propose solutions to this issue.This paper focuses on two financial fraud cases in recent years,Toshiba in 2015 and Luckin Coffee in 2020,analyzes and compares the reasons for the financial fraud in terms of pressure and opportunity factors,as well as proposes comprehensive suggestions for dealing with the corporate financial fraud issue.

Review of Financial Pressure

Different from foreign capital markets,china’s domestic capital markets are special,which also determines that the research on financial pressure starts from the reform of state-owned enterprises,and draws lessons from the relevant theories of financial risk and financial fraud,thus gradually forming a more diversified research results.

Application Technologies and Challenges of Big Data Analytics in Anti-Money Laundering and Financial Fraud Detection

As financial criminal methods become increasingly sophisticated, traditional anti-money laundering and fraud detection approaches face significant challenges. This study focuses on the application technologies and challenges of big data analytics in anti-money laundering and financial fraud detection. The research begins by outlining the evolutionary trends of financial crimes and highlighting the new characteristics of the big data era. Subsequently, it systematically analyzes the application of big data analytics technologies in this field, including machine learning, network analysis, and real-time stream processing. Through case studies, the research demonstrates how these technologies enhance the accuracy and efficiency of anomalous transaction detection. However, the study also identifies challenges faced by big data analytics, such as data quality issues, algorithmic bias, and privacy protection concerns. To address these challenges, the research proposes solutions from both technological and managerial perspectives, including the application of privacy-preserving technologies like federated learning. Finally, the study discusses the development prospects of Regulatory Technology (RegTech), emphasizing the importance of synergy between technological innovation and regulatory policies. This research provides guidance for financial institutions and regulatory bodies in optimizing their anti-money laundering and fraud detection strategies.

Principal Model Analysis Based on Bagging PLS and PCA and Its Application in Financial Statement Fraud

Motivated by the Bagging Partial Least Squares(Bagging PLS)and Principal Component Analysis(PCA)algorithms,a novel approach known as Principal Model Analysis(PMA)method is introduced in this paper.In the proposed PMA algorithm,the PCA and the Bagging PLS are combined.In this method,multiple PLS models are trained on sub-training sets,derived from the training set using the random sampling with replacement approach.The regression coefficients of all the sub-PLS models are fused in a joint regression coefficient matrix.The final projection direction is then estimated by performing the PCA on the joint regression coefficient matrix.Subsequently,the proposed PMA method is compared with other traditional dimension reduction methods,such as PLS,Bagging PLS,Linear discriminant analysis(LDA)and PLS-LDA.Experimental results on six public datasets demonstrate that our proposed method consistently outperforms other approaches in terms of classification performance and exhibits greater stability.Additionally,it is employed in the application of financial statement fraud identification.PMA and other five algorithms are utilized to financial statement fraud which concerned by the academic community,and the results indicate that the classification of PMA surpassed that of the other methods.

Fraud Identification of Chinese Listed Companies——an Improvement Based on M-Score

To evaluate the applicability of the M-score model in the Chinese capital market,this research observed 190 financial fraud samples punished by the China Securities Regulatory Commission(CSRC)in the years from 2014 to 2018.The test results indicate that two types of errors are high,which means that the applicability of the M-score is unacceptable.Therefore,in this paper,a 9-index model is constructed by Wald's backward stepwise regression method,and the optimal threshold is set by the Beneish expected cost method(ECM).The accuracy of the modified M-score is significantly improved,especially the Type I error rate of is reduced from 70.37%to 19.75%.The receiver operating characteristic(ROC)curve test also proves the superior identification effect of the modified M-score applied in the Chinese market.Finally,variables such as current ratio,fixed asset index,and equity concentration in the modified model could represent the fraud characteristics of Chinese listed companies.

Fraud Prevention Mechanisms of Malaysian Government-Linked Companies： An Assessment of Existence and Effectiveness

Understanding the root causes of fraud and learning about the most effective fraud prevention mechanisms are critical in reducing the incidence of financial fraud. Therefore, this study solicits the views of fraud investigators on the existence and effectiveness of fraud prevention mechanisms within Government-Linked Companies （GLCs）. Specifically, effective fraud prevention mechanisms （FPM） should be undertaken by five critical groups, namely the board of directors, audit committees, external auditors, internal auditors, and anti-fraud specialists. A total of 147 questionnaires were distributed to fraud investigators of all public listed GLCs in Malaysia. Out of those, a total of 45 usable responses were received, which represents an effective response rate of 30.6%. In terms of existence, the respondents ranked ＂management review of internal controls＂ and ＂external audits of financial statements＂ as the top-most FPMs. This was followed by other mechanisms such as operational audits, internal audits and internal control review/improvements by departments. Out of the 27 fraud prevention mechanisms, fraud investigators perceiyed surprise audits, fraud hotline, fraud prevention program and training, anti-fraud policy, fraud vulnerability reviews, operational audits, whistle-blowing policy, internal audit or fraud examination department, and, imposing penalty and disciplinary action as more effective than the others. Overall, this study provides important insights to practitioners and organizations in identifying fraud prevention mechanisms that are most effective.

Accountability Simulacra: Fraud Cases from South and North America

Cases of corporate frauds with financial instruments count on simulacra of accountability.Based on grounded research,this study considered cases that were conducted for years without being detected causing billionaire injury to investors.The objective was to present how they bypassed internal controls,corporate governance,and all regulatory apparatus using substantive and symbolic resources at organization level analysis.An extensive analysis allowed perceive a common modus operandi that is described here organized by objectives.This paper also suggests a direction for accountability improvement.

金融素养、金融监管与金融欺诈

近年来,频发的金融欺诈扰乱了金融秩序,危害了参与者的利益,金融反欺诈已迫在眉睫,而金融素养、金融监管是金融反欺诈的重要手段。该文构建了金融素养抑制金融欺诈的理论框架,利用CHFS数据测度居民金融素养综合指数,通过构建静态与动态面板模型探讨了金融素养与金融欺诈之间的关系以及金融监管在其中的调节作用,并对不同群体的异质性进行分析。研究表明:居民金融素养的提高以及地方金融监管的加强均能有效抑制金融欺诈事件的发生,且金融监管在其中具有正向调节作用;不同群体的金融素养对金融欺诈的抑制效果具有差异性,如学历较高的人群可能存在过度自信的心理特征,但可通过提高自身金融素养来防范金融欺诈事件的发生。

数字普惠金融对电信网络诈骗影响的实证研究

电信网络诈骗活动日益频繁,严重影响经济和社会稳定,侵害了广大人民群众的利益。将2015年中国家庭金融调查(CHFS)中的诈骗模块数据与中国数字普惠金融指数相结合,考察数字普惠金融对家庭成为诈骗目标的风险、实际受骗风险和受骗损失的影响。研究表明:数字普惠金融增加了家庭成为电信网络诈骗目标的概率,但能帮助家庭在成为诈骗目标时降低受骗风险,减少经济损失;异质性分析方面,数字普惠金融抑制电信网络诈骗的积极效果在农村和东部地区更加显著,当家庭成员属于数字鸿沟中的优势群体时,数字普惠金融会对其产生更好的降低受骗风险并减少损失的效果;作用机制方面,数字普惠金融主要通过增加家庭的金融可得性、缓解融资约束以及提高家庭成员对金融经济信息关注度来降低居民实际受骗风险,减少损失;进一步分析发现,金融监管、家庭成员金融素养提升和社区宣传教育能增强数字普惠金融对电信网络诈骗的抑制效果。

ESG表现会抑制企业财务舞弊吗?——来自A股上市企业的经验证据

在企业日益关注社会责任与可持续发展的大背景下,ESG(环境、社会和公司治理)表现成为评估企业综合价值的重要指标。基于2013—2022年中国A股上市企业数据,考察ESG表现对企业财务舞弊的影响。研究结果表明,ESG表现能够抑制企业财务舞弊行为,包括降低舞弊发生概率和严重程度。机制研究表明,ESG表现通过降低信息不对称程度、缓解融资约束和降低代理成本进而抑制企业财务舞弊。异质性分析表明,ESG表现抑制企业财务舞弊的作用在内部控制质量差、非国有以及法制环境程度高的样本中更加显著。经济后果检验发现,ESG表现通过抑制企业财务舞弊促进财务绩效的提升、降低企业的经营风险。

业绩期望落差与审计质量——基于A股上市公司的经验数据

以2010—2022年A股上市公司为样本实证检验业绩期望落差对审计质量的影响。研究发现,业绩期望落差与审计质量显著负相关,稳健性检验没有改变结论。机制分析显示,业绩期望落差增大了企业的财务舞弊风险,降低了审计质量。异质性分析表明审计师具有较强的独立性和行业专长有助于提升审计质量;进一步地,新冠疫情前的“四大”审计能够更好发挥外部治理作用,同时业绩期望落差对低质量审计的持续性具有显著的正向影响。研究结论拓展了业绩期望落差的审计后果,同时为推动企业和资本市场高质量发展提供了丰富的经验证据。

立德树人视域下电信诈骗防范路径研究

互联网已成为电信诈骗的主要载体,受骗者以20岁以下的青年群体居多,给青年成长、社会安稳造成巨大伤害。该文归纳了近5年来高校电信诈骗的常见类型,从中分析出大学生受骗的四大因素,并基于思想政治教育的德育引导和财经素养教育对防范电信诈骗提出四项对策,通过树立正确的财富观、健康的消费观、牢固的价值观,提升青年学生的危机规避力、风险防范力。

基于深度学习和文本情感的上市公司财务舞弊识别方法

上市公司财务舞弊是指采用不当手段使会计信息失真的恶劣失信行为,对公司经营、经济发展和社会利益产生负面影响。目前,更多研究关注于金融数字数据,对文本信息和深度学习算法的研究较少,因此提出了一种基于深度学习并融合文本情感特征的上市公司财务舞弊识别方法。该方法首先对财务指标进行预处理,并使用BiLSTM提取股评文本的情感特征。然后使用RCC(residual-cross-convolutional)并行网络进行财务舞弊识别,其采取残差网络、交叉网络、卷积网络和长短期记忆网络并行的方式提取财务舞弊特征,并使用批标准化和全连接得到最终的识别结果。实验结果表明,该方法在识别上市公司财务舞弊的任务上较其他模型取得了更好的效果,召回率和AUC分别达到了88.46%和82.06%。