Bank Fraud Research Articles

Detecting Financial Fraud Using Data Mining Techniques: A Decade Review from 2004 to 2015

Objective: Financial fraud has been a big concern for many organizations across industries; billions of dollars are lost yearly because of this fraud. So businesses employ data mining techniques to address this continued and growing problem. This paper aims to review research studies conducted to detect financial fraud using data mining tools within one decade and communicate the current trends to academic scholars and industry practitioners. Method: Various combinations of keywords were used to identify the pertinent articles. The majority of the articles retrieved from Science Direct but the search spanned other online databases (e.g., Emerald, Elsevier, World Scientific, IEEE, and Routledge - Taylor and Francis Group). Our search yielded a sample of 65 relevant articles (58 peer-reviewed journal articles with 7 conference papers). One-fifth of the articles was found in Expert Systems with Applications (ESA) while about one-tenth found in Decision Support Systems (DSS). Results: 41 data mining techniques were used to detect fraud across different financial applications such as health insurance and credit card. Logistic regression model appeared to be the leading data mining tool in detecting financial fraud with a 13% of usage.In general, supervised learning tool have been used more frequently than the unsupervised ones. Financial statement fraud and bank fraud are the two largest financial applications being investigated in this area – about 63%, which corresponds to 41 articles out of the 65 reviewed articles. Also, the two primary journal outlets for this topic are ESA and DSS. Conclusion: This review provides a fast and easy-to-use source for both researchers and professionals, classifies financial fraud applications into a high-level and detailed-level framework, shows the most significant data mining techniques in this domain, and reveals the most countries exposed to financial fraud.

Role of Legislation, Need of Strong Legal Framework and Procedures to Contest Effectively with Cybercrime and Money Laundering

There is need for a robust and strong legislation to tackle white Collar-crime is stressed, which is on the rise in both the public and private sectors. The effect of immoral and unlawful actions in government, notably high-level bribes, has crippled the financial and legislative bodies in their normal functioning. Bank frauds, money laundering, and cybercrimes are also on the rise, due to the widespread use of digital gadgets and the internet. The absence of strong network-security systems especially in the banking sector has caused great losses indeed. The goal of this study is multidimensional; more about the importance of applying strong regulations as well as morality and ethical principles. It has been argued in this paper that morality and ethical norms positively influence minimizing such crimes; if morality and ethics are coupled with strong legislation, it works as a Deterrence Force. It will undoubtedly be one of the most momentous global occurrences in recent history, long-term impacting culture, government operations, crime, economics, politics, and social relationships. The major role in combating the crime depends upon the existence of strong legislation capable of causing a reduction in the crime rate, which allows the investigators vast powers and collaboration with the prosecution and safeguarding the witnesses. The criminals are very well organized and use the most modern technology and IT equipment, therefore, the police, investigators, and prosecutors must have and be highly trained and equipped, similarly. appropriate methods and algorithms are required. We create a new method, a dynamic atomic shared memory for message communication. A properly stated method is proposed for message communication and then implemented. According to this method, owners can be changed dynamically, and their access to read and write also changes.

Rain Drop Service and Biometric Verification Based Blockchain Technology for Securing the Bank Transactions from Cyber Crimes Using Weighted Fair Blockchain (WFB) Algorithm

Cybercrime is an online crime committing fraud, stealing identities, violating privacy or hacking the personal information. A high level of information security in banking can be attained through striving to achieve an integrity, confidentiality, availability, assurance, and accountability. This Pandemic situation (COVID-19) paved the way for the customers to avoid traditional ways of banking and adapt to digital transactions. This banking digitalization increases in the utilization of cashless transactions like digital money (Cryptocurrency). Cyber security is imperative to preserve sensitive information, therefore, Blockchain technology has been adapted to provide security. Transactions done via Blockchain are tested through every block, which makes transactions secure and helps the banking system to work faster. The proposed algorithm WFB is used to estimate the average queue rate and avoid unwanted block generation. Then the trapezoidal fuzzy technique optimizes the allocation of blocks. An objective of this investigation is to enhance the security in banking systems from Cybercrimes by verifying Rain Drop Service (RDS) and Fingerprint Biometric without the need of any central authority. Once the service is completed, the service is a dropout and the following new service will be provided (Hence the name RDS). For the strong authentication scheme to fight against bank fraud, RSA encryption technique has been implemented successfully. Therefore, Blockchain technology increases the need for cyber security as a part of design architecture which intends to detect the stemming attacks in real time instead of repairing the damage.

Determinan Kecurangan Laporan Keuangan pada Bank Umum Syariah Periode 2014-2019 dalam Perspektif Fraud Triangle Theory

The development of Islamic Commercial Banks in Indonesia shows good numbers. This is an opportunity for parties related to banking institutions to ensure this potential can be utilized to be developed again. However, in fact there are still Islamic banks that are caught incases fraud which can damage or disrupt the potential development of Islamic banking. This study aims to analyze the determinants of financial statement fraud in Islamic Commercial Banks registered in OJK for the 2014-2019 period with perspective Fraud Triangle Theory. This research usesmethods library and internet research. The sampling technique is a saturated sample consisting of 12 Islamic banks registered with the OJK. The analysis method is regression path analysis. The expected result of this study is an equation that can describe the influence of the independent variables, namely financial stability, financial target, external pressure, financial needs, ineffective monitoring, and rationalization. the dependent variable, namely earnings management.

An Innovative Sensing Machine Learning Technique to Detect Credit Card Frauds in Wireless Communications

There has been an increase in credit card fraud as e-commerce has become more widespread. Financial transactions are essential to our economy, so detecting bank fraud is essential. Experiments on automated and real-time fraud detection are needed here. There are numerous machine learning techniques for identifying credit card fraud, and the most prevalent are support vector machine (SVM), logic regression, and random forest. When models penalise all errors equally during training, the quality of these detection approaches becomes crucial. This paper uses an innovative sensing method to judge the classification algorithm by considering the misclassification cost and at the same time by employing SVM hyperparameter optimization using grid search cross-validation and separating the hyperplane using the theory of reproducing kernels like linear, Gaussian, and polynomial, and the robustness is maintained. Because of this, credit card fraud has been identified significantly more successful than in the past.

Creating a Nexus between Dark Triad Personalities, Non-Performing Assets, Corporate Governance and Frauds in the Indian Banking sector

PurposeThe banking sector requires a major comeback with the series of bank frauds that has shook the nation. The rising non-performing assets (NPAs) and corporate frauds find their roots in the top-level management or executive levels. The purpose of this study to analyse the behavioural component with corporate governance lapses for creating a trail and to what extent it can contribute to forensic analysis to help reduce and prevent fraud in the future.Design/methodology/approachThis study is investigative in nature. This study uses case study approach by taking into account the major Advance–NPA–Fraud cases over period of 2010–2022. RBI data for bank advances, NPAs and advances-relate frauds from 2005 to 2019 were studies and interpreted for creating a trend and pattern for the reduction and prevention of frauds.FindingsThe authors found that behavioural factors and personalities affect the systems and culture of the company, thereby giving a jolt to the corporate governance mechanisms along with various entities like depositors, consumers and shareholders.Practical implicationsAssessing the behavioural aspects for risk mitigation remains unexplored in the banking sector. The personality dimension can help in contributing to comprehending the mental aspects and the reasons behind the combination of dark triads with economic offences.Originality/valueThis study is beneficial to all the beneficiaries of the banking sector and the economy at large in understanding the implications of risks because of patterns formed by emotions and vulnerability towards economic and fugitive economic crimes.

Study on Fraud Transaction Detection System

Fraudulent transactions are very common problem in banking systems internationally, accounting for $5.1 trillion dollars every year. Many financial institutions are facing the common problem of being targeted by transactions of fraudulent nature and its becoming more and more obvious that advanced technology, such as Machine Learning (ML) is needed to counter such acts. Machine learning is the most effective technique against these complex bank frauds when approaches relying on fragmented and siloed data, rules-based approaches or traditional point-solutions are not only costly but also not as effective as needed. Complex algorithms powered by ML can be used to reduce manual investigations in Financial Institutions. Volume of these transactions is huge, lots of current solutions do not focus on big data the proposed model will work on big data with the help of ‘Apache Spark’ using latest machine learning technology. The proposed model will try to find pattern in given data set and flag the transaction as fraudulent or not with probability score and then banking system can decide further course of action. We are also going to include different machine learning algorithms used to detect fraudulent transactions and provide a comparative study between those algorithms to show which is more effective.

Does Economic Restructuring during Covid-19 in South Africa amount to Disaster Capitalism?

I explore the ANC government’s cadre-based (BBBEE/Broad-based Black economic empowerment) narrative in restructuring the economy amidst the pandemic, as an ideological vehicle to achieve an unstated nefarious purpose. The narrative that I aim to capture through the lenses of Naomi Klein’s disaster capitalism read with Reiman’s “pyrrhic defeat theory,” is built around the fictitious idea of Black economic empowerment. Ultimately it serves as a vehicle for fraudulent personal enrichment by politicians and well-connected tenderpreneurs. This double theoretical vision is meant to augment and explain the opportunity that the Covid-pandemic provided for its exploitation as an example of disaster capitalism. I traverse the events which led to the current global pandemic as well as the way or ways in which a faction within government and its institutions has generally colluded with Big Business to profit from it. I consider the South African government’s initial response to the pandemic as well as the ways in which such a response morphed into a self-enrichment scheme under the guise of BBBEE. This remains plausible even if one concedes that this purpose was not by original design or is solely driven by a faction within the ruling party. This discussion is preceded by an overview of the VBS Mutual Bank fraud scandal, foreshadowing my demonstration of how the pandemic proffers an opportunity for the RET-group within government to transform into a criminal shadow state as a going concern. In conclusion, I draw on the Covid-19 experience to suggest lessons for the future economic management of pandemics.

The Importance and Need for Forensic Audit in India to Detect Banking Frauds and Protect Investors Interest

In recent years, there has been an increase in fraudulent operations in the financial and corporate sectors as a result of technical and digital innovation. As a result, the necessity of forensic audit in the current scenario is critical in detecting such frauds and protecting the interests of shareholders. As a result, the study attempted to determine the value of forensic audit in the current situation. The purpose of this study is to emphasize the importance and use of forensic audits. A systematic review of the literature was used as the study's approach. According to the conclusions of the study, forensic auditing is crucial in mitigating and avoiding financial fraud. Forensic auditing has established itself as a strategic tool for company success.

Implementation Of Whistleblowing System To Prevent Sharia Banking Crime In Indonesia

The research made is qualitative research, where researchers look at various sources related to the whistleblowing system in Islamic banking. The object of this research is PT. Bank Syariah Indonesia (BSI) one of the largest Islamic banks in Indonesia, and targets to become the 10 largest Islamic banks in the world in the next 5 years. This research is needed to understand and see how the BSI whistleblowing system controls fraud and crime in the Indonesian banking world. Based on a survey from The Association of Certified Fraud Examiners, the level of banking fraud in Indonesia reaches 41% when compared to other sectors. This is one of the things that can be taken into account by the government, and stakeholders in banking. In addition to using qualitative methods. This study analyzes the BSI website with support from various sources related to the whistleblowing system in Islamic banking. Hopefully, in the future, there will be continued research looking at the implications of the whistleblowing system to prevent fraud in banking, especially Islamic banking, both in Indonesia but also abroad.

ANALISIS PENGARUH SHARI COMPLIANCE DAN ISLAMIC CORPORATE GOVERNANCE TERHADAP JUMLAH FRAUD BANK UMUM SYARIAH PERIODE 2015—2019

Fraud is a deviant act carried out by individuals for their own benefit but harming others. Fraud cases are still found to occur in Islamic commercial banks that run their operations based on Islamic principles. So this study aims to examine the effect of sharia compliance and Islamic corporate governance on the number of frauds in Islamic commercial banks. The independent variables used are Profit sharing ratio, Islamic income ratio, Directors-employees welfare ratio, and Islamic corporate governance. While the dependent variable used is sharia bank fraud. The research population is all Islamic commercial banks registered with the Financial Services Authority for the period 2015-2019, with a purposive sampling technique the sample used is 10 Islamic commercial banks with a study period of 5 years. The analytical method used in this research is panel data regression which is processed using Eviews 9 software. The results show that simultaneously sharia compliance and Islamic corporate governance have a significant effect on sharia commercial bank fraud. Partially, the Directors-employees welfare ratio and Islamic corporate governance have a significant positive effect on Islamic commercial bank fraud, while Profit sharing ratio and Islamic income ratio have no effect on Islamic commercial bank fraud. The results of this research have implications for practitioners and regulators in determining policies to minimize fraud.

Assessment of knowledge and practice of criminal intelligence and staff profiling for fraud prevention in Nigerian banks

The study was set to examine knowledge and practice of criminal intelligence and staff profiling for fraud prevention in Nigerian banks, the study adopted the mixed method research design of descriptive survey and key informant interview. Multistage sampling technique was used to select the sample population for the study a total of 324 respondents was sampled using the Taro Yamane formula for sample size determination. Questionnaire and key person’s interview were used as data collection instrument. The findings of the study conclude that bank staff is aware and knowledgeable of criminal intelligence and staff profiling as an effective tool for fraud prevention. Beyond the awareness, bank staff are also knowledgeable on the application of criminal intelligence and staff profiling, while they also agreed that the extent of application of criminal intelligence and staff profiling in the recruitment, placement and monitoring of staff is low. However, the study recommends that Senior management of banks should be given adequate training and this training should be regularly updated on criminal intelligence and monitoring, as well as staff profiling. This would facilitate a greater uptake of credible intelligence and the prevention of bank fraud and other criminal activities.

Effect of the Capability Component of Fraud Theory on Fraud Risk Management in Nigerian Banks

The incidence of bank fraud is a fundamental problem with diverse consequences to banks and their stakeholders. Therefore, this study examined the effect of the capability component of fraud theory on fraud risk management in Nigerian banks. The specific objectives of the study are to: examine the effect of malicious insider abuses on fraud risk management efficiency of Nigerian banking sector; evaluate the effect of internal control bypasses on fraud risk management efficiency of Nigerian banking sector; investigate the effect of information security breaches on fraud risk management efficiency of Nigerian banking sector, and ascertain the effect of fraud risk governance on fraud risk management efficiency of Nigerian banking sector. The study adopted ex-post factoresearch design. Secondary data were gathered from the quarterly report on fraud and forgeries of the Financial Institutions Training Centre (FITC) from the first quarter of 2011 to the second quarter of 2020 given a total of thirty-eight (38) observations. The dependent variable of the study was fraud risk management efficiency (FRMη) while the independent variables were malicious insider abuses (MIA), Internal Control Bypasses (ICB), Information Security Breaches (ISB), and fraud risk governance (FRG). Four hypotheses were formulated and tested using robust linear regression analysis. The study employed Stata 14.2 and SPSS 22 in data analyses. We also conducted Skewness/Kurtosis and Shapiro-Francia W’ normality tests, Variance Inflation Factor (VIF) of multicollinearity, Breusch-Pagan/Cook Weisberg test of heteroskedasticity, and Durbin-Watson test for autocorrelation. The results revealed statistically significant negative effects of internal control bypasses and information security breaches on fraud risk management efficiency. The study also found an insignificant positive effect of malicious insider threats and fraud risk governance on fraud risk management efficiency. The implication of these findings is that the Nigerian banking sector is confronted with both internal and external fraud capability challenges which require management attention and stakeholders’ education and awareness. Based on these findings, the study offers comprehensive fraud vulnerability suggestions integrating all banking stakeholders (internal and external) to improve fraud risk management efficiency in Nigerian banking sector.

A systematic literature review on frauds in banking sector

PurposeBanking industry peculiarly has become soft target for several pernicious deceptive and fraudulent activities. The purpose of this paper is to systematically review the literature published in past 20 years on bank frauds and present a holistic view on causes and consequences of bank frauds and measures to curtail this menace. Towards the end the paper provides avenues for future research.Design/methodology/approachA systematic literature review approach is used in this study and articles are selected via pre-set inclusion criteria. The literature is mapped on the basis of databases, year of publication, country of study and journal of publication. This paper is based on 70 selected articles published in four prominent databases between 2000 and 2021.FindingsThis study reveals that frauds in banking industry have become a matter of grave concern for almost all countries across the globe, causing significant financial and non-financial damages to banks, customers, other stakeholders and economy. Numerous factors such as pressure and opportunity are responsible for fraud occurrence. This study further evinced that banking institutions inevitably should have a robust fraud risk management in place to prevent, detect and respond to defalcation.Originality/valueTo the best of the authors’ knowledge, this is the only paper among 70 selected articles which systematically reviews the literature published in past 20 years and provides a comprehensive view on all aspects related to bank frauds.

Investigation of Card Skimming Cases: An Indian Perspective

Card frauds are one of the most common types of banking frauds out of which card skimming contributes the major share. Investigation and prosecution of card skimming cases are mainly dependent on digital evidence requiring trained and skilled law enforcement officers. Further, a single incident of card skimming leads to collection of information from hundreds of cards and hence the identification of all the victims is the real challenge for an investigating officer. This paper discusses different issues pertaining to card skimming providing a general overview of the modus operandi, investigation process and constraints faced by law enforcement agencies.

Analysis of the Effect of Sharia Compliance and Islamic Corporate Governance on Fraud in Islamic Banks in Indonesia 2017-2019

This study aims to analyze the factors that influence the occurrence of fraud in Islamic banks in Indonesia. Measurement of fraud in Islamic banks is based on the number of internal frauds that occur in the financial year. The population in this study is Islamic banks in Indonesia for the period 2017-2019. The sample is selected using purposive sampling method and the number of samples obtained is 24 samples. The data used in this study are secondary data in the form of financial reports and corporate governance reports. Data analysis is performed using classical assumption tests and regression analysis. The results of this study indicate that Islamic corporate governance has a significant effect on internal fraud in Islamic banks in Indonesia. Meanwhile, partially the profit sharing ratio and Islamic investment ratio do not have a significant effect on internal fraud in Islamic banks in Indonesia. Islamic banking must comply with accounting standards and Auditing Organizations for Islamic Financial Institutions (AAOIFI) to minimize fraud in operations.

Factors impacting banking frauds in India: a conceptual framework

The Indian banking sector has witnessed exponential growth and changes since liberalisation of economy in 1990-1991. Reserve Bank of India is the chief regulator of the banking sector and has done a reasonable work in close supervision. Never ending banking frauds pose a serious challenge to the government, with banking sector also the regulator. Growing challenges also fall in the realm of ethical practices, financial distress and corporate governance. This study looked at the cases of bank frauds listed by Central Vigilance Commission, in order to understand the underlying issues in frauds in various sectors, different banking instruments used to commit frauds and the regulatory lapses in the banking sector. A detailed analysis was done by using secondary data (literature review and case approach) as well as an interview-based approach, spanning across all players involved in reporting, regulating and dealing indirectly or directly in the financial misconduct. The analysis acts as an anchor to study the components of frauds and define the role of regulators in the whole game plan. The study finally proposes some recommendations to reduce future occurrence of frauds in Indian banking sector.

Big Data as a Service and Application for Indian Banking Sector

The financial world, money markets, and the growth of an economy are all powered by banks. In India's financial sector, where cashless and paperless transactions are expanding quickly, bank fraud is also rising quickly, and fraudsters are now turning to cutting-edge techniques. Fighting financial crimes has always been a priority for the banking industry. Banks’ fraud losses will diminish when they are able use analytics and emerging technologies for better fraud prevention. Data has evolved into more than simply an IT resource; it is a vital feature of the banking industry's digital transformation in the present world. The majority of contemporary risk monitoring systems, which are based on data science discipline such as big data, allow for surveillance and offer Early Warning Signals (EWS) about any kind of worsening. The study of this paper signifies that how big data as a service and application proven as a strong and innovative instrument that assists Indian banking sector not only in identifying security issues and fraudulent behavior, but also in their early prevention. The experimental results of bibliometric study conducted on Scopus and Web of Science databases using in Vos Viewer software, clearly discovered big data technology is a crucial approach to deploy in Indian banking system. Findings of this paper will contribute to knowledge and practice of researchers working in this filed by increasing their understanding related to numerous big data technologies and techniques deployment for handling banking financial risks and its role in operational banking workflow management.

ANALYSIS OF MATHEMATICAL MODELS FOR COUNTERING CYBER FRAUD IN BANKS

The article is devoted to the current topic of analysis of mathematical models for countering cyber fraud in banks. This problem is due to the security risks growth in the banking system, which are formed by fraudsters' cyberattacks and cybercrimes implementation. Therefore, the priority task for cyberbanking security is the application of modern mathematical methods to analyse the sources of cyber attacks, identify threats and losses in the banking services market, identify cyber-attacks and assess the scenario of potential cyber risk, etc. The article analyses the most widespread types of cyber fraud: social engineering, phishing, stalking, farming, DoS attacks, online fraud, potentially unwanted programs, etc. The study also considered a model of cognitive computing and detection of suspicious transactions in banking cyber-physical systems based on quantum computing in BCPS for the post-quantum era. The advantages, disadvantages and results of the model are defined. Predictive modelling is proposed to detect fraud in real-time by analysing incoming bank transactions with payment cards. Within the framework of this method, such models are used for the classification of fraud detection as logistic regression, a decision tree, and a narrower technique - a random forest decision tree. The study also considered using the harmonic search algorithm in neural networks to improve fraud detection in the banking system. It is found that although this model has the advantage of learning ability based on past behaviour, there are difficulties in the long-term processing of many neural networks. The stages of model implementation are also given. In addition, the modelling of credit card fraud detection is based on using two types of models: supervised and unsupervised. Supervised models include logistic regression, K-nearest neighbours, and extreme gradient boosting. The one-class support vector model, restricted Boltzmann model, and generative-competitive network are considered among uncontrolled generative models.

Measuring Fraud in Banking and Its Impact on the Economy: An Empirical Approach

Measuring Fraud in Banking and Its Impact on the Economy: An Empirical Approach