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Article
Publication date: 9 March 2020

Wanting Lu and Xiaokang Zhao

The purpose of this paper is to start with the background of the construction of the M-score model, find the variables that can represent the fraud characteristics of…

Abstract

Purpose

The purpose of this paper is to start with the background of the construction of the M-score model, find the variables that can represent the fraud characteristics of Chinese companies, and use the data of Chinese A-share listed companies to modify the M-score model.

Design/methodology/approach

In this paper, the fraud behavior of Chinese enterprises that M-score cannot detect is summarized as the basis of adding variables. Then, based on the data of Chinese listed companies, a modified M-score model including nine variables is constructed by the logistic regression method based on Wald.

Findings

Based on the original 8 variables of M-score, this paper adds 10 new variables that can represent the fraud characteristics of Chinese listed companies, and finally, constructs a modified M-score model with 9 variables. Results indicated that indexes such as gross profit margin, fixed assets depreciation rate, equity concentration and audit opinion can characterize the financial fraud of Chinese listed companies.

Practical implications

The modified M-score model based on the characteristics of Chinese enterprises’ fraud is more suitable for Chinese market, which can help investors avoid fraud risks, protect their own rights and interests and reduce losses.

Originality/value

Starting from the background of the model, this paper looks for variables that can characterize the characteristics of fraud in Chinese listed companies. Then, subdivides the research samples into specific fiscal years in which fraud occurs, so that the modified M-score model can be more suitable for the Chinese market.

Details

Journal of Financial Crime, vol. 28 no. 2
Type: Research Article
ISSN: 1359-0790

Keywords

Article
Publication date: 8 February 2022

Neha Chhabra Roy and Sreeleakha Prabhakaran

This paper aims to focus on the different types of insider-led cyber frauds that gained mainstream attention in recent large-scale fraud events involving prominent Indian…

Abstract

Purpose

This paper aims to focus on the different types of insider-led cyber frauds that gained mainstream attention in recent large-scale fraud events involving prominent Indian banking institutions. In addition to identifying and classifying cyber fraud, the study maps them on a severity scale for optimal mitigation planning.

Design/methodology/approach

The methodology used for identification and classification is an analysis of a detailed literature review, a focus group discussion with risk and vigilance officers and cyber cell experts, as well as secondary data of cyber fraud losses. Through machine learning-based random forest, the authors predicted the future of insider-led cyber frauds in the Indian banking business and prioritized and predicted the same. The projected future reveals the dominance of a few specific cyber frauds, which will make it easier to develop a fraud mitigation model based on a victim-centric approach.

Findings

The paper concludes with a conceptual framework that can be used to ensure a sustainable cyber fraud mitigation ecosystem within the scope of the study. By using the findings of this research, policymakers and fraud investigators will be able to create a more robust environment for banks through timely detection of cyber fraud and prevent it appropriately before it happens.

Research limitations/implications

The study focuses on fraud, risk and mitigation from a victim-centric perspective and does not address it from the fraudster’s perspective. Data availability was a challenge. Banks are recommended to compile data that can be used for analysis both by themselves and other policymakers.

Practical implications

The structured, sustainable cyber fraud mitigation suggested in the study will provide an agile, quick, proactive, stakeholder-specific plan that helps to safeguard banks, employees, regulatory authorities, customers and the economy. It saves resources, cost and time for bank authorities and policymakers. The mitigation measures will also help improve the reputational status of the Indian banking business and prolong the banks’ sustenance.

Originality/value

The innovative cyber fraud mitigation approach contributes to the sustainability of a bank’s ecosystem quickly, proactively and effectively.

Details

Journal of Financial Crime, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1359-0790

Keywords

Article
Publication date: 12 August 2022

Neha Chhabra Roy and Sreeleakha Prabhakaran

The study aims to overview the different types of internal-led cyber fraud that have gained mainstream attention in recent major-value fraud events involving prominent…

Abstract

Purpose

The study aims to overview the different types of internal-led cyber fraud that have gained mainstream attention in recent major-value fraud events involving prominent Indian banks. The authors attempted to identify and classify cyber frauds and its drivers and correlate them for optimal mitigation planning.

Design/methodology/approach

The methodology opted for the identification and classification is through a detailed literature review and focus group discussion with risk and vigilance officers and cyber cell experts. The authors assessed the future of cyber fraud in the Indian banking business through the machine learning–based k-nearest neighbor (K-NN) approach and prioritized and predicted the future of cyber fraud. The predicted future revealing dominance of a few specific cyber frauds will help to get an appropriate fraud prevention model, using an associated parties centric (victim and offender) root-cause approach. The study uses correlation analysis and maps frauds with their respective drivers to determine the resource specific effective mitigation plan.

Findings

Finally, the paper concludes with a conceptual framework for preventing internal-led cyber fraud within the scope of the study. A cyber fraud mitigation ecosystem will be helpful for policymakers and fraud investigation officers to create a more robust environment for banks through timely and quick detection of cyber frauds and prevention of them.

Research limitations/implications

Additionally, the study supports the Reserve Bank of India and the Government of India's launched cyber security initiates and schemes which ensure protection for the banking ecosystem i.e. RBI direct scheme, integrated ombudsman scheme, cyber swachhta kendra (botnet cleaning and malware analysis centre), National Cyber Coordination Centre (NCCC) and Security Monitoring Centre (SMC).

Practical implications

Structured and effective internal-led plans for cyber fraud mitigation proposed in this study will conserve banks, employees, regulatory authorities, customers and economic resources, save bank authorities’ and policymakers’ time and money, and conserve resources. Additionally, this will enhance the reputation of the Indian banking industry and extend its lifespan.

Originality/value

The innovative insider-led cyber fraud mitigation approach quickly identifies cyber fraud, prioritizes it, identifies its prominent root causes, map frauds with respective root causes and then suggests strategies to ensure a cost-effective and time-saving bank ecosystem.

Details

Aslib Journal of Information Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2050-3806

Keywords

Article
Publication date: 7 July 2020

Oluwatoyin Esther Akinbowale, Heinz Eckart Klingelhöfer and Mulatu Fikadu Zerihun

The purpose of this study is to develop an innovative approach of combating economic crime using the forensic accounting techniques.

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Abstract

Purpose

The purpose of this study is to develop an innovative approach of combating economic crime using the forensic accounting techniques.

Design/methodology/approach

The approach considered the identification of the effective forensic accounting techniques from the available literature and also explored the anti-economic crime policy, capable of assisting in the combating of economic crime. This brought about the development of two conceptual models, which incorporate all the requirements for the implementation of forensic accounting and the integration of forensic accounting technique into the organizational control system for effective fraud mitigation.

Findings

The analysis of the literature review indicated that one of the drawbacks, which has continue to mitigate the implementation of forensic accounting as a tool for combating fraud is lack of a suitable framework. This was the major focal point of this work, which produced two simplified conceptual models suitable for effective fraud mitigation.

Research limitations/implications

This study is limited to the development of conceptual models for fraud mitigation only.

Practical implications

The simplified model can easily be adopted into the structure of an organization to provide a sustainable solution to mitigate fraud occurrences.

Originality/value

The novelty of this study lies in the development of two simplified conceptual models. The first model addressed the incorporation of forensic accounting into the organization structure while the second captured the detailed investigation and comprehensive data analysis processes of uncovering fraud. The development of conceptual models with all these peculiarities for fraud mitigation has not been widely reported by the existing literature.

Details

Journal of Financial Crime, vol. 27 no. 4
Type: Research Article
ISSN: 1359-0790

Keywords

Article
Publication date: 1 October 2007

A.C. Venter

The high occurrence of procurement fraud requires the management of an enterprise, the risk manager of the enterprise and the internal auditor to address procurement fraud

1993

Abstract

The high occurrence of procurement fraud requires the management of an enterprise, the risk manager of the enterprise and the internal auditor to address procurement fraud risks effectively within the enterprise risk management concept. The purpose of the article is to explain a procurement fraud risk management process which will serve as a comprehensive framework for enterprise risk managers and for internal auditors to limit the enterprise’s exposure to procurement fraud as far as possible. The study by Venter (2005) on which the article is based proposes a procurement fraud risk matrix which can be used to manage fraud risks within the procurement function efficiently. This matrix is based on the Committee of Supporting Organizations of the Treadway Commission’s (COSO’s) Enterprise Risk Management ‐Integrated Framework which is specifically applied to address the procurement fraud risk problem.

Details

Meditari Accountancy Research, vol. 15 no. 2
Type: Research Article
ISSN: 1022-2529

Keywords

Book part
Publication date: 18 July 2022

Yakub Kayode Saheed, Usman Ahmad Baba and Mustafa Ayobami Raji

Purpose: This chapter aims to examine machine learning (ML) models for predicting credit card fraud (CCF).Need for the study: With the advance of technology, the world is…

Abstract

Purpose: This chapter aims to examine machine learning (ML) models for predicting credit card fraud (CCF).

Need for the study: With the advance of technology, the world is increasingly relying on credit cards rather than cash in daily life. This creates a slew of new opportunities for fraudulent individuals to abuse these cards. As of December 2020, global card losses reached $28.65billion, up 2.9% from $27.85 billion in 2018, according to the Nilson 2019 research. To safeguard the safety of credit card users, the credit card issuer should include a service that protects customers from potential risks. CCF has become a severe threat as internet buying has grown. To this goal, various studies in the field of automatic and real-time fraud detection are required. Due to their advantageous properties, the most recent ones employ a variety of ML algorithms and techniques to construct a well-fitting model to detect fraudulent transactions. When it comes to recognising credit card risk is huge and high-dimensional data, feature selection (FS) is critical for improving classification accuracy and fraud detection.

Methodology/design/approach: The objectives of this chapter are to construct a new model for credit card fraud detection (CCFD) based on principal component analysis (PCA) for FS and using supervised ML techniques such as K-nearest neighbour (KNN), ridge classifier, gradient boosting, quadratic discriminant analysis, AdaBoost, and random forest for classification of fraudulent and legitimate transactions. When compared to earlier experiments, the suggested approach demonstrates a high capacity for detecting fraudulent transactions. To be more precise, our model’s resilience is constructed by integrating the power of PCA for determining the most useful predictive features. The experimental analysis was performed on German credit card and Taiwan credit card data sets.

Findings: The experimental findings revealed that the KNN achieved an accuracy of 96.29%, recall of 100%, and precision of 96.29%, which is the best performing model on the German data set. While the ridge classifier was the best performing model on Taiwan Credit data with an accuracy of 81.75%, recall of 34.89, and precision of 66.61%.

Practical implications: The poor performance of the models on the Taiwan data revealed that it is an imbalanced credit card data set. The comparison of our proposed models with state-of-the-art credit card ML models showed that our results were competitive.

Article
Publication date: 30 October 2018

Jiali Tang and Khondkar E. Karim

This paper aims to discuss the application of Big Data analytics to the brainstorming session in the current auditing standards.

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Abstract

Purpose

This paper aims to discuss the application of Big Data analytics to the brainstorming session in the current auditing standards.

Design/methodology/approach

The authors review the literature related to fraud, brainstorming sessions and Big Data, and propose a model that auditors can follow during the brainstorming sessions by applying Big Data analytics at different steps.

Findings

The existing audit practice aimed at identifying the fraud risk factors needs enhancement, due to the inefficient use of unstructured data. The brainstorming session provides a useful setting for such concern as it draws on collective wisdom and encourages idea generation. The integration of Big Data analytics into brainstorming can broaden the information size, strengthen the results from analytical procedures and facilitate auditors’ communication. In the model proposed, an audit team can use Big Data tools at every step of the brainstorming process, including initial data collection, data integration, fraud indicator identification, group meetings, conclusions and documentation.

Originality/value

The proposed model can both address the current issues contained in brainstorming (e.g. low-quality discussions and production blocking) and improve the overall effectiveness of fraud detection.

Details

Managerial Auditing Journal, vol. 34 no. 3
Type: Research Article
ISSN: 0268-6902

Keywords

Article
Publication date: 11 May 2020

Vipin Khattri, Sandeep Kumar Nayak and Deepak Kumar Singh

Currency usage either in the physical or electronic marketplace through chip-based or magnetic strip-based plastic card becoming the vulnerable point for the handlers…

Abstract

Purpose

Currency usage either in the physical or electronic marketplace through chip-based or magnetic strip-based plastic card becoming the vulnerable point for the handlers. Proper education and awareness can only thrive when concrete fraud detection techniques are being suggested together with potential mitigation possibilities. The purpose of this research study is tendering in the same direction with a suitable plan of action in developing the authentication strength metric to give weightage marks for authentication techniques.

Design/methodology/approach

In this research study, a qualitative in-depth exploration approach is being adapted for a better description, interpretation, conceptualization for attaining exhaustive insights into specific notions. A concrete method of observation is being adopted to study various time boxed reports on plastic card fraud and its possible impacts. Content and narrative analysis are being followed to interpret more qualitative and less quantitative story about existing fraud detection techniques. Moreover, an authentication strength metric is being developed on the basis of time, cost and human interactions.

Findings

The archived data narrated in various published research articles represent the local and global environment and the need for plastic card money. It gives the breathing sense and capabilities in the marketplace. The authentication strength metric gives a supporting hand for more solidification of the authentication technique with respect to the time, cost and human ease.

Practical implications

The research study is well controlled and sufficient interpretive. The empirical representation of authentication technique and fraud detection technique identification and suggestive mitigation gives this research study an implication view for the imbibing research youths. An application and metric based pathway of this research study provides a smoother way to tackle futuristic issues and challenges.

Originality/value

This research study represents comprehensive knowledge about the causes of the notion of plastic card fraud. The authentication strength metric represents the novelty of a research study which produced on the basis of rigorous documentary and classified research analysis. The creativity of the research study is rendering the profound and thoughtful reflection of the novel dimension in the same domain.

Book part
Publication date: 9 December 2020

Jeremy Lee and Alexey Nikitkov

Consumption taxes are an integral part of government revenue in countries around the world and are often subject to consumer evasion. The rapid rise of electronic commerce…

Abstract

Consumption taxes are an integral part of government revenue in countries around the world and are often subject to consumer evasion. The rapid rise of electronic commerce has exacerbated this problem as cross-border selling over the internet has enabled foreign businesses to sell and avoid collection and remittance of tax on their sales.

In this paper, we search for the solution to this problem through the analysis of three tax collection models: vendor, financial institution, and internet service provider (ISP). In addition, we examine administrative tools that enable more effective collection as well as inducements for taxpayers or collection agents to carry out their responsibility.

We conclude that the ISP collection model is not feasible at this time. On the other hand, we find that the vendor model, when supplemented with appropriate administrative tools and inducements, and the financial institution model, both represent viable options for policymakers to consider.

Article
Publication date: 2 July 2018

Vipin Khattri and Deepak Kumar Singh

This paper aims to provide information of parameters and techniques used in the automated fraud detection system during online transaction. With the increase in the use of…

Abstract

Purpose

This paper aims to provide information of parameters and techniques used in the automated fraud detection system during online transaction. With the increase in the use of online transactions, the concerns regarding data security have also increased. To tackle the frauds, lot of research has been done and plethora of papers are available on the related topics. The purpose of this paper is to provide the clear pathway for researchers to move in the direction of development of automated fraud detection system to prevent the fraud during online transaction.

Design/methodology/approach

This literature review analyses and compares the different types of techniques for detecting fraud during online transaction. An in-depth study of the most prominent journals has been done and the core methodology of the papers has been presented. This article also shed some light on different types of parameters used in fraud detection techniques during online transaction.

Findings

There are vast varieties of various fraud detection techniques, and every technique has completed task in its own way. After studying approximately 41 research papers, 14 books and four reports, in total 30 parameters have been identified and a detailed study of the parameters has been presented. The parameters are also listed with their details that how these parameters are used in the security system for detecting online transaction fraud.

Research limitations/implications

This paper provides empirical insight about the parameters and their prominence in the development of automated fraud detection security system of online transaction. This paper encourages the researchers to development of improved fraud detection system.

Practical implications

This paper will pave the way for researchers to do a focused research on the fraud detection methodologies. The analysis will help in zeroing down the most prevalent topic of research in this field. The researchers will be able to understand the internal details of parameters and techniques used in the fraud detection systems. This literature also helps the research to think in a variety of ways that how these parameters will be used in the development of fraud detection system.

Originality/value

This paper is one of the most comprehensive reviews in its field. It tries and attempts to fill a void created because of lack of compilation of the laid fraud detection parameters.

Details

Journal of Financial Crime, vol. 25 no. 3
Type: Research Article
ISSN: 1359-0790

Keywords

1 – 10 of over 4000