Genuine Customers Research Articles

Malaysian Consumer Income and Spending Behaviour During the COVID-19 Pandemic: An Insight from Maqāṣid Al-Sharīʿah

Purpose — Spending patterns changed during the COVID-19 pandemic due to the health crisis turning into an economic challenge. This study examines the Malaysian public’s awareness level and changes in their spending behaviour during COVID-19. It also aims to identify the spending patterns on different items based on the consumers’ income and establish whether the awareness level of maqāṣid al-Sharīʿah (objectives of Islamic law) on spending affects the public’s perception of future spending behaviour. Design/Methodology/Approach — Quantitative approaches were implemented through questionnaire outcomes, and further analysis was carried out through the SPSS software. The survey included 420 participants, and the results were analysed using inferential and descriptive statistics such as the Chi-Square test and regression. Findings — Important findings of this paper show that the situation following the COVID-19 pandemic led to behavioural changes in many aspects, especially in Malaysians’ spending patterns. The findings show that most items related to awareness of maqāṣid al-Sharīʿah and spending are less than 3, which means that respondents are not aware or slightly aware of the concept. Only one item related to spending more on necessities during the pandemic achieves an average of more than 3. Secondly, changes in spending behaviour are seen on all items included in the study, which means the pandemic caused various changes in the spending patterns of Malaysians. Furthermore, certain categories of items (e.g., food and groceries, meal delivery services, entertainment items, face masks/hand sanitisers/disinfectants, and internet services) have shown significant differences among income groups in this study. Finally, from the regression results, it is found that the awareness level of maqāṣid al-Sharīʿah and its impact on spending is significant for the future perception of spending. Originality/Value — The novelty of this study comes from the concept of relating spending behaviour to maqāṣid al-Sharīʿah, especially during challenging moments such as the COVID-19 pandemic. Practical Implications — This paper reflects the importance of enhancing the maqāṣid al-Sharīʿah concept in spending patterns, especially in Muslim-majority countries. The current research added to knowledge in regard to how consumer behaviour changed during the COVID-19 pandemic. The findings may be useful in developing marketing strategies, considering psychological elements to suit the feelings and demands of genuine customers.

Counterfeiting and firm survival. Do international trade activities matter?

Counterfeiting is a phenomenon that threatens global competition and economic growth, and it is well-known that the presence of illicit fake products unfairly altering competition, can affect firm profitability and even, in some cases, force owners to close their businesses or declare bankruptcy. By introducing three new complementary measures of counterfeiting, this study examines the intra- and inter-industry effects of counterfeiting on Italian firm survival taking into consideration the differing degree of a firm’s involvement in international trade activities. Overall, the results of micro-econometric analysis indicate that the probability of a genuine firm exiting the market increases when the effect flows from the “fake” sector to its upstream genuine suppliers; vice versa, it decreases when the effect flows from the “fake” sector to its downstream genuine customers. However, when classifying firms as trading and no trading firms, we found that these results are confirmed only for the latter. Our evidence, which is robust to different estimation methods, provides room for policy and manager interventions.

Detecting Denial of Service attacks using machine learning algorithms

Currently, Distributed Denial of Service Attacks are the most dangerous cyber danger. By inhibiting the server's ability to provide resources to genuine customers, the affected server's resources, such as bandwidth and buffer size, are slowed down. A mathematical model for distributed denial-of-service attacks is proposed in this study. Machine learning algorithms such as Logistic Regression and Naive Bayes, are used to detect attacks and normal scenarios. The CAIDA 2007 Dataset is used for experimental study. The machine learning algorithms are trained and tested using this dataset and the trained algorithms are validated. Weka data mining platform are used in this study for implementation and results of the same are analysed and compared. Other machine learning algorithms used with respect to denial of service attacks are compared with the existing work.

Early DDoS Detection and Prevention with Traced-Back Blocking in SDN Environment

The flow of information is a valuable asset for every company and its consumers, and Distributed Denial-of-Service (DDoS) assaults pose a substantial danger to this flow. If we do not secure security, hackers may steal information flowing across a network, posing a danger to a business and society. As a result, the most effective ways are necessary to deal with the dangers. A DDoS attack is a well-known network infrastructure assault that prevents servers from servicing genuine customers. It is necessary to identify and block a DDoS assault before it reaches the server in order to avoid being refused services. This prompted us to develop a unique way for detecting and preventing DDoS attacks at the router level in a Software-Defined Network (SDN) environment. This study demonstrates how the method efficiently integrates the first and second signatures in SDN infrastructure domains to identify and prevent DDoS attacks. It also proposes an Early DDoS Detection and Prevention (EDDDeP)-based approach for detecting and blocking malicious traffic in an SDN context. This article covers the EDDDeP, which assists in identifying and preventing DDoS in SDN to prevent malicious traffic from reaching its intended target. As a consequence, the DDoS assault is ultimately contained inside the environment, eliminating superfluous traffic in the DDoS network architecture. This method offers a unique technique to detect a DDoS assault and notify nearby neighbours in order to avert server damage.

Loan Default Identification and its Effect

Now a days banking sector is on boom everyone is applying for loan but banks have limitation that they have limited assets so they can provide loan to limited loan applications but when they provide loan, they must assure that loan is being granted to only genuine customers. So, this paper focuses on we will try to lessen the uncertainty factor and assure the loan approval to genuine customers only and save the bank assets. That is performed by way of mining the massive data of the earlier data of the human beings to whom the loan become acknowledged earlier than and on the idea of those records/reviews the machine was skilled the use of the system mastering version which provide the maximum correct result. The main focus of the paper will be on the loan to be approved of those customers only who will be able to pay it back.

Predictive analytics in fraud and AML

The common problem we are all facing in fraud risk and compliance these days is how to address the challenge of reducing false positive rates to optimise detection for fraud and, very importantly when monitoring transactions for anti-money laundering/ counter-terrorist financing (AML/CTF), how to avoid being overwhelmed by alerts. This paper aims to introduce to the reader the importance of considering the use of predictive analytics in the financial crimes prevention strategy and programme of any organisation. This paper starts by offering a detailed background of the scope of the fraud and AML/CTF problem in general, focusing on the high costs that many organisations face when trying to prevent and detect financial crimes and also protect their genuine customers from becoming victims of financial crimes. The paper goes on to describe the most common challenges that organisations face, in particular resource challenges when devising and implementing their strategies. It also encourages a collaborative approach to fraud prevention. The reader can expect to gain insightful information about how predictive analytics can be used in the prevention of financial crimes and what type of benefits it can deliver.

A COMPARISON OF IDEAL BANKING MODEL WITH MOBILE BANKING SYSTEM

A banking system acts like a financial intermediary and creates money by lending money to a borrower, thereby creating a corresponding deposit on the bank's balance sheet. Lending activities can be performed directly by loaning or indirectly through capital markets. After the advent of technology and its penetration to all business fields, the responsibility of banks is enhanced to provide better, speedy, and ubiquitous service to the customers so that it can create more money and hence profit. Banks are formulating various strategies in order to attract more deposits and lend it to genuine customers to get a better return and hence make more profit. Based on such objective of a general banking system, the ideal concept of the banking system is developed. The ideal bank is a system with ideal banking characters. In this paper, a model of the ideal banking system is proposed by considering the ideal characteristics expected under input conditions, output conditions, system requirements, and environmental conditions. The factors affecting these characteristics are identified using a qualitative data collection instrument namely focus group method. Finally, some of the possible technology supported models which support the concept of Ideal banking are identified and analyzed. It is found that electronic banking using mobile devices called mobile banking or ubiquitous banking system has characteristics close to the features of the ideal banking system.

Ideal Banking Concept and Characteristics

A bank is a financial intermediary and creates money by lending money to a borrower, thereby creating a corresponding deposit on the bank's balance sheet. Lending activities can be performed directly by loaning or indirectly through capital markets. After the advent of technology and its penetration to all business fields, the responsibility of banks is enhanced to provide better, speedy, and ubiquitous service to the customers so that it can create more money and hence profit. Banks are formulating various strategies in order to attract more deposits and lend it to genuine customers to get a better return and hence make more profit. Based on such objective of a general banking system, the ideal concept of the banking system is developed. The ideal bank is a system with ideal banking characters. In this paper, a model of the ideal banking system is proposed by considering the ideal characteristics expected under input conditions, output conditions, system requirements, and environmental conditions. The factors affecting these characteristics are identified using a qualitative data collection instrument namely focus group method.

Delivering medical abortion at scale: a study of the retail market for medical abortion in Madhya Pradesh, India.

BackgroundMedical abortion (mifepristone and misoprostol) has the potential to contribute to reduced maternal mortality but little is known about the provision or quality of advice for medical abortion through the private retail sector. We examined the availability of medical abortion and the practices of pharmacists in India, where abortion has been legal since 1972.MethodsWe interviewed 591 pharmacists in 60 local markets in city, town and rural areas of Madhya Pradesh. One month later, we returned to 359 pharmacists with undercover patients who presented themselves unannounced as genuine customers seeking a medical abortion.ResultsMedical abortion was offered to undercover patients by 256 (71.3%) pharmacists and 24 different brands were identified. Two thirds (68.5%) of pharmacists stated that abortion was illegal in India. Only 106 (38.5%) pharmacists asked clients the timing of the last menstrual period and 38 (13.8%) requested to see a doctor’s prescription – a legal requirement in India. Only 59 (21.5%) pharmacists correctly advised patients on the gestational limit for medical abortion, 97 (35.3%) provided correct information on how many and when to take the tablets in a combination pack, and 78 (28.4%) gave accurate advice on where to seek care in case of complications. Advice on post-abortion family planning was almost nonexistent.ConclusionsThe retail market for medical abortion is extensive, but the quality of advice given to patients is poor. Although the contribution of medical abortion to women’s health in India is poorly understood, there is an urgent need to improve the practices of pharmacists selling medical abortion.

Catching the fraudulent Man-in-the-Middle

There is mounting pressure on companies to detect fraud perpetrated by the new generation of cyber-fraudsters who are becoming adept at impersonating genuine customers by being the Man-in-the-Middle or the Man-in-the-Browser. However, there are technologies available now that can help to detect where fraudsters are operating in this way.

Electricity theft: Overview, issues, prevention and a smart meter based approach to control theft

Non-technical loss (NTL) during transmission of electrical energy is a major problem in developing countries and it has been very difficult for the utility companies to detect and fight the people responsible for theft. Electricity theft forms a major chunk of NTL. These losses affect quality of supply, increase load on the generating station, and affect tariff imposed on genuine customers. This paper discusses the factors that influence the consumers to steal electricity. In view of these ill effects, various methods for detection and estimation of the theft are discussed. This paper proposes an architectural design of smart meter, external control station, harmonic generator, and filter circuit. Motivation of this work is to deject illegal consumers, and conserve and effectively utilize energy. As well, smart meters are designed to provide data of various parameters related to instantaneous power consumption. NTL in the distribution feeder is computed by external control station from the sending end information of the distribution feeder. If a considerable amount of NTL is detected, harmonic generator is operated at that feeder for introducing additional harmonic component for destroying appliances of the illegal consumers. For illustration, cost–benefit analysis for implementation of the proposed system in India is presented.

Catching the fraudulent Man-in-the-Middle and Man-in-the-Browser

Virtual technologies, more successful phishing techniques and increasingly realistic imitations of genuine customers mean that prevention and detection measures need to be more effective. The first step is for businesses to understand what they are facing.