• The Journal of Industrial Distribution & Business
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• v.12 no.12
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• pp.1-10
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• 2021

Purpose: Cyber criminals have affected various markets and the banking system has encountered various kinds of cyberattacks. The purpose of this study is to analyze cybercrime that is an emerging threat and investigate the significant contribution of financial literacy and public awareness on cybercrimes. To understand the security issues and the need for corrective steps, the techniques and strategies used by cyber fraudsters in obtaining unauthorized access and use the financial information for purpose of fraud need to be understood. Research design, data and methodology: A sample of 123 banks employees from 12 commercial banks in Malaysia was surveyed. This study differs from previous studies as it surveyed the employees' awareness, and this approach fills in the gap in existing literature. Results: The financial literacy and public awareness have positive impact on organizational performance effectiveness to combat threat of cybercrime. Some recommendations are also proposed from research findings, for banking industry and government regulations. Conclusion: The present study focuses on banking sector so its findings cannot be generalized to other sectors. Linking these topics has created a new study in combating threat of cybercrimes generally, and specifically in Malaysia. The present study enhances the understanding of customers' role to combat the impact of cybercrimes on performances of banking industry.

• Proceedings of the Korea Information Processing Society Conference
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• 2000.10a
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• pp.277-280
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• 2000

Credit evaluation is one of the most important and difficult tasks fur credit card companies, mortgage companies, banks and other financial institutes. Incorrect credit judgement causes huge financial losses. This work describes the use of an evolutionary-fuzzy system capable of classifying suspicious and non-suspicious credit card transactions. The paper starts with the details of the system used in this work. A series of experiments are described, showing that the complete system is capable of attaining good accuracy and intelligibility levels for real data.

• The Journal of Society for e-Business Studies
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• v.23 no.4
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• pp.153-169
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• 2018

Previous e-financial anomalies analysis and detection technology collects large amounts of electronic financial transaction logs generated from electronic financial business systems into big-data-based storage space. And it detects abnormal transactions in real time using detection rules that analyze transaction pattern profiling of existing customers and various accident transactions. However, deep analysis such as attempts to access e-finance by insiders of financial institutions with large scale of damages and social ripple effects and stealing important information from e-financial users through bypass of internal control environments is not conducted. This paper analyzes the management status of e-financial security programs of financial companies and draws the possibility that they are allies in security control of insiders who exploit vulnerability in management. In order to efficiently respond to this problem, it will present a comprehensive e-financial security management environment linked to insider threat monitoring as well as the existing e-financial transaction detection system.

• Advances in environmental research
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• v.12 no.2
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• pp.113-122
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• 2023

Biometric authentication has become an essential part of modern-day security systems, especially in financial institutions like banks. A face recognition-based ATM is a biometric authentication system, that uses facial recognition technology to verify the identity of bank account holders during ATM transactions. This technology offers a secure and convenient alternative to traditional ATM transactions that rely on PIN numbers for verification. The proposed system captures users' pictures and compares it with the stored image in the bank's database to authenticate the transaction. The technology also offers additional benefits such as reducing the risk of fraud and theft, as well as speeding up the transaction process. However, privacy and data security concerns remain, and it is important for the banking sector to instrument solid security actions to protect customers' personal information. The proposed system consists of two stages: the first stage captures the user's facial image using a camera and performs pre-processing, including face detection and alignment. In the second stage, machine learning algorithms compare the pre-processed image with the stored image in the database. The results demonstrate the feasibility and effectiveness of using face recognition for ATM authentication, which can enhance the security of ATMs and reduce the risk of fraud.

• Journal of Digital Contents Society
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• v.19 no.1
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• pp.193-198
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• 2018

In Korea, the penetration rate of Internet, telephone and smart devices is reaching the highest level in the world. Cyber financial crimes that exploit such infrastructures continue to evolve. Since the first Voice Phishing crime in May 2006, ten years later, there has been a constant occurrence of Voice Phishing crime. Voice Phishing is a crime in which a victim is phoned for false information to figure out the victim's account number and password. This method of Voice Phishing evolves day by day, and it is difficult to investigate. Most of Voice Phishing is a form of international organized crime that is based in Southeast Asia such as China, and it is not easy to eradicate by international cooperation investigation. The purpose of this study is to investigate the actual situation and case analysis of Voice Phishing crime, and to propose the countermeasures against police Voice Phishing counterplan.

• Asia pacific journal of information systems
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• v.5 no.2
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• pp.79-100
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• 1995

Internal Control(IC) comprises the plan of organization and all of the coordinating methods and measures adopted in a business to safeguard its assets, check the accuracy and reliability of its accounting data, promote operational efficiency and encourage adherence to the prescribed managerial policies. If an organization's IC is not adequate, Accounting Information System (AIS) will be vulnerable to accomplish the organizations successes. Therefore, an effective and efficient IC is essential to its successes. The purpose of this study is to analyze the impact of EDP IC on the perceived usefulness of AIS. Do the general controls indirectively affect to the usefulness of AIS through th application controls? To solve these problems, a research model and a set of hypotheses were established and empirically tested. 60 financial institutions (banks, insurance companies, security companies) agreed to participate in the study. Data were gathered through structured interviews with 60 information systems managers and 537 users of accounting information of each company. Survey forms were designed and collected from financial institutions in Seoul. Information systems' managers of financial institutions responded to questionnaire(1) which consists of a series of 70 questions related to practice and perceived importance. Questionnaire (2) was received from 537 users, who responded to series of 17 questions related to the perceived usefulness. The results of analysis are summarized below. Effects of general controls are more direct on AIS's usefulness than those of application controls. Whereas, indirect effects of application controls are geater than those of general controls. Therefore, the greater the effects of application controls on general controls, the higher the perceived usefulness of AIS. In conclusion, this study supports that the perceived usefulness of AIS is affected by IC which are composed of general controls and application controls. The results of this study has significant implication to financial institution as computer fraud potential increases. Because of global competitions, financial institutions should restructure to IC and AIS in order to take advantage of the technological progress in Information System.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.807-819
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• 2021

This study aims to determine the availability of forensic accounting application factors sought by auditors' representatives of Jordanian Certified Public Accounting and auditors working in the Audit Bureau. The study identifies as well the role of these application factors in enhancing the efficiency of auditors due to the increased responsibility on them in the face of various fraud cases on the one hand, and their appearance in the courts as financial experts supporting the judiciary to adjudicate financial cases on the other hand. To achieve the objectives of the study, the researchers used the descriptive analytical method because of its suitability for the nature of the research. The population of the study consisted of 433 Jordanian certified public accountants and 520 auditors working in the Audit Bureau, from which a sample of 426 was constructed. A questionnaire was developed to collect data and the Statistical Package for Social Sciences was utilized to analyze data and test hypotheses. The study found that there is a statistical difference between the responses of the two samples of the study, and it concluded a set of recommendations, which are hoped to help legislators in strengthening and developing the forensic accounting profession in Jordan.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.7
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• pp.475-487
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• 2020

The paper aims to facilitate a discussion around how big data technologies and data from citizens can be used to help public administration, society, and policy-making to improve community's lives. This paper discusses opportunities and challenges of big data strategies for government, society, and policy-making. It employs the presentation of numerous practical examples from different parts of the world, where public-service delivery has seen transformation and where initiatives have been taken forward that have revolutionized the way governments at different levels engage with the citizens, and how governments and civil society have adopted evidence-driven policy-making through innovative and efficient use of big data analytics. The examples include the governments of the United States, China, the United Kingdom, and India, and different levels of government agencies in the public services of fraud detection, financial market analysis, healthcare and public health, government oversight, education, crime fighting, environmental protection, energy exploration, agriculture, weather forecasting, and ecosystem management. The examples also include smart cities in Korea, China, Japan, India, Canada, Singapore, the United Kingdom, and the European Union. This paper makes some recommendations about how big data strategies transform the government and public services to become more citizen-centric, responsive, accountable and transparent.

• Convergence Security Journal
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• v.10 no.3
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• pp.61-68
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• 2010

Recently a malware is increasing for leaking personal data, credit information, financial information, etc. The secondary damage is also rapidly increasing such as the illegal use of stolen name, financial fraud, etc. But when a system is infected by a malware of leaking information, the existing malware evidence collection tools do not provide evidences conveniently or sometimes cannot provide necessary evidences. So security officials have much difficulty in responding to malwares. This paper analyzes the current status and problems of the existing malware evidence collection tools and suggests new ways to improve those problems.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.303-304
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• 2021

In the 21st century, as we enter the Fourth Industrial Revolution, research in various fields utilizing big data is being conducted, and innovative and useful technologies are constantly emerging in the world. Among several technologies recently in the big data era, among various fields utilizing some algorithms of artificial intelligence, it shines in the field of finance and is used for pin tech, financial fraud detection and risk management, etc., and recently Even in the booming stock market, it is used for investment prediction and investment factor analysis using artificial intelligence algorithm models. In this paper, we plan to investigate various research cases and investigate trends in how they are used in the stock market through artificial intelligence that utilizes big data.