Template-based dynamic time warping credit cards’ fraud prediction model

The enormous technological development witnessed in the world in the late twentieth century, especially in the field of computer and the internet, has led to the inclusion of credit card system into the market of civil and commercial transactions. In view of the modernity of this system and the multiplicity of relations and legal problems resulting from it, it was necessary for the legislator to intervene to regulate it, and this is what the legislator did in some countries, while the regulation of this system in many countries, including Iraq, subjects to the general provisions of the law and banking traditions that may no longer be able to accommodate the provisions of this multi-relationship system and the ramifications of the provisions. This study is an attempt to illuminate the way for the Iraqi legislator in his future efforts to legislate a law regulating the issuance and use of a credit card. The study includes examining a specific aspect of the various aspects of the credit card system, namely the contract between the issuing bank and the merchant. Specifically, this study examines the obligations of issuing bank of the credit card towards the merchant in the merchant's contract within the credit card system. This study is an attempt to illuminate the way for the Iraqi legislator in his future efforts to legislate a law regulating the issuance and use of a credit card. This includes examining the various aspects of the credit card system, namely the contract between the issuing bank and the merchant. Specifically, this study examines the bank's credit card obligations towards the merchant in the merchant's contract within the credit card system. This study has reached several results regarding the concept of the merchant's contract in the credit card system and its legal adaptation. The study concluded that adapting the merchant's contract as an indefinite contract of a special nature is the more accurate adaptation. The study also concluded that there are in merchant contract multiple obligations on the issuing bank of the credit card towards the merchant, some of them are direct obligations towards the merchant, and others are indirect obligations on the issuing bank of the credit card towards the merchant not in direct deal with the merchant, but in context of dealing of the issuing bank of the credit card with credit card holder. The direct obligations of the credit card issuing bank towards the merchant are obligation to provide the merchant with the means to deal with the credit card, obligation to the informing, and obligation to provide a secure and effective system for accepting and dealing with credit card. While the indirect obligations of the issuing bank of the credit card towards the merchant are obligation to issue the credit card in accordance with the agreement with the merchant and obligation to pay the bills of the credit card holder to the merchant. The study presented several suggestions in front of the Iraqi legislator about provisions regulating the obligations of issuing bank of the credit card obligations towards the merchant in the merchant's contract within the credit card system, and the Iraqi legislator can rely on them in the drafting of any special law to be legislated in the future in regulating the issuance and use of the credit card.

In nowadays time we are on the specific education to a cashless society. Similarly, the use of credit card in developing international locations has grown to be a not unusual scenario. The world goes to be digital by means of making the availability of services to peoples together with credit score playing cards, ATM, Internet banking, and mobile banking services. With the rapid increase of the e-trade or online business the use of credit card is so common as it makes the payment easier and saves a time. There are lots of blessings of using the credit card system such as ease of purchase, preserve purchaser credit score history, protection of Purchases, and so on. As we recognize each coin has two faces so the usage of credit card has hazards too inclusive of credit score card fraud in which the hacker theft the credit card info and the misuse the credit score card by means of stealing the details of the card together with credit score card range, CVV, expiry date, etc. Fraud is intentional hypocrisy for the motive of obtaining economic profits or inflicting losses by means of implicit or express deception. However, Fraud is the violation of public law wherein the scammer profits an unauthorized advantage or causes unlawful damage.KeywordsFraudDetectionCredit cardInformationSecurity

Nowadays, in the digital era, the use of credit cards is widespread. People buy and sell goods from home. E-commerce brings a boom to the lifestyle of the people, for the working family, it is a preferable tool to purchase and pay through online mode in order to save the time and visiting hours. However, with the increasing use of credit cards, there have also been a lot of cases of credit card frauds that augmented much in the corona period. Fake credit card transactions significantly affect financial institutions, banks, and clients, whereas fraudsters try to develop new ways of committing fraud daily. To avoid credit card fraud and maintain the credibility of our clients, we need to build a model for credit card detection. There are the various machine learning tools that can be applied in detection of such frauds, these tools can be used to design an enhanced model to detect credit card frauds efficiently. In this view, the study presents a feature selection technique approach of machine learning with different classifiers. The study proposed an optimization algorithm using ‘Firefly’ for feature selection with four different classifiers: neural network, k-nearest neighbors, Support Vector Machine, and decision tree. The performance of all these four classifiers is compared on the basis of accuracy parameter.

The current research examines influence of materialism and compulsive-buying behavior on Indian consumers’ credit card use. Research in Western countries posits that materialistic values and compulsiveness influence credit card use. However, results of the research differ from earlier researches. It suggests that Indian consumers’ credit card use is influenced by materialism but not by compulsiveness. Credit cards may be acquired to represent a lifestyle and improve individual’s status. The symbolic value associated with credit card is higher than its functional attributes. Consumers associate it with material possessions that bequeath status to them.

Financial fraud is a serious threat that is expanding effects on the financial sector. The use of credit cards is growing as digitization and internet transactions advance daily. The most common issues in today's culture are credit card scams. This kind of fraud typically happens when someone uses someone else's credit card details. Credit card fraud detection uses transaction data attributes to identify credit card fraud, which can save significant financial losses and affluence the burden on the police. The detection of credit card fraud has three difficulties: uneven data, an abundance of unseen variables, and the selection of an appropriate threshold to improve the models' reliability. This study employs a modified Logistic Regression (LR) model to detect credit card fraud in order to get over the preceding difficulties. The dataset sampling strategy, variable choice, and detection methods employed all have a significant impact on the effectiveness of fraud detection in credit card transactions. The effectiveness of naive bayes, k-nearest neighbour, and logistic regression on highly skewed credit card fraud data is examined in this research. The accuracy of the logistic regression technique will be closer to 0.98%; with this accuracy, frauds may be easily detected. The fact that LR receives the highest classifier score illustrates how well LR predicts credit card theft.

This article discusses the concept of a credit card as a means of payment in Islamic law. There are two main problems studied, namely (1) the conception of Shariah credit cards (alternatives) in Sharia Banking that can accommodate the needs of the community that are appropriate and do not conflict with Islamic Sharia; (2) the opinion of the scholars regarding the use of credit cards. The two problems were studied using a library approach by using books, magazines, journals and several other scientific works as primary sources. After conducting research, the authors found that Islamic credit cards can only be accessed for transactions on goods that have been determined with halal criteria. There are several opinions of scholars regarding the law on the use of credit cards related to the problems above. There are scholars who allow and there are also those who forbid based on their respective foundations. The MUI National Sharia Council stated that the use of sharia credit cards is allowed as long as it fulfills the provisions, and if it violates these provisions, the law will become illegal.

Discriminating the number of credit cards held by college students using credit and money attitudes

Purpose: This study discussed the factors that influence the use and debt of credit cardholders in Jakarta and surrounding areas (Jakarta, Bogor, Depok, Tangerang, Bekasi) Research methodology: The dependent variable used in this study is the use of credit cards and debts on credit cards. This study's independent variables were demographic factors, credit card feature factors, and attitude towards money factors. The sample of this study was 333 respondents using the purposive sampling technique. The data analysis model used is Ordinary Least Square (OLS). Results: The results showed that there were influences from demographic factors (age, income, family size), features on credit cards (credit limits), and attitudes towards money (the main payment method with credit cards, card tenure) on the use of credit cards; also, demographic factors (gender, type of work, level of education, income) and attitude towards money (minimum payment) on credit card debt. Therefore the factors that banks need to consider to increase their income, and the government for control of public expenditure, also the public to pay more attention to spending on their credit cards so that there is no accumulation of debt that cannot be paid. Limitations: This study has several limitations of specifically only examines the people who are in Jakarta and their surroundings (Jabodetabek) and examines demographic factors, features on credit cards, and attitudes. Contribution: This study will examine demographic factors, features on cards, and attitudes towards money by uniting variables per category into a unified category. The indicators in this study are adjusted to the community in Indonesia. Keywords: Attitude towards money, Credit cards, Credit card features, Demographics

The literature documents the impact of credit card use on people’s financial well-being, including special interest in women’s credit card behavior. This chapter examines predictors of the financial well-being for female college students living in Sao Paulo City (Brazil) or New York City (United States), focusing upon behaviors regarding credit card use. The results of structural equation models, based on 784 participants, suggest that financial self-confidence and social comparison impact the respondents’ habits surrounding credit card use and, more largely, influence financial well-being. Although social comparison is more strongly predictive of credit card use among Brazilian women, credit card use behavior has a greater impact on the well-being of American women.

PurposeThe purpose of this paper is to understand the moderating influence of Multi‐item List of Value (MILOV) on credit card attributes, age, and gender in credit use among Indian customers. The research examines the impact of “lifestyle” variables (convenience, use patterns, and status) on credit card use.Design/methodology/approachData were collected through mall intercept technique in six metropolitan cities of India. A self‐administered questionnaire was distributed to customers visiting the malls.FindingsUse and convenience emerged as the major determinants of credit card use among Indian customers. Use, convenience, and status attributes were moderated by “sense of belonging” and “sense of fulfilment” dimensions of MILOV. Young customers were likely to use credit cards.Research limitations/implicationsThe study does not examine the influence of customer income, occupation, and education on credit card use, as many customers were not willing to disclose the information. These demographic factors can influence customers' perception towards credit card ownership and use.Practical implicationsThe findings can be of immense use to international and Indian banks in marketing of credit cards. The convenience attribute can be emphasized to instill confidence among consumers and motivate them to use credit cards.Originality/valueThere is no previous research on Indian credit cards which examines the influence of “lifestyle” and values on its use among Indian customers.

The development in the economic sector is influencing the development of banking products. One of the many products that is commonly used is credit card. In this context, The use of credit cards practically bring some problems that are reflected in the Islamic Law Perspective, especially because it does not specifically manage the credit cards according to Islam. It is different from the conventional credit cards that already have legal instruments clearly. Therefore, this study examines the legal implications in financing cards based on murabahah contract. This research is a normative legal research by analyzing the management of the Financing Card Based on Murabahah Contract. In order to help the analyses, this study uses the theory of Mаqаsid аl-syаri'аh and the theory of expediency (utility). The results that found related to the legal implications in financing cards based on murabahah contract can be reviewed from the relevancy to the theory of usefulness (utility). Credit cards as a modern means of payment, provide many conveniences and benefits in the midst of the rapid development of the business world. In addition, to address the use of credit cards based on usury, the Syariah Bank issued a Syariah Credit Card or Financing Card, this product must be based on the National Syariah Council Decision (Fatwa Majelis Ulama Indonesia) No.54 / DSN-MUI / 2006 on Syariah Card. Then in order to avoid legal implications that are not in accordance with syariah principles, from the aspect of the term that is used in Syariah, it is more appropriate to use the financing card term instead of credit card.

Credit card transactions have increased significantly every year. Along with the increasing use of credit cards, the risk of fraud by irresponsible people also increases. Credit card fraud can be detected with the help of machine learning. The main problem that often encountered is the transaction data has very large dimensions, unbalanced classes, and requires a detection process with a short computation time. Therefore we need a model that can produce good performance with short computation time using the support vector machine (SVM) method with grid search and genetic algorithm optimization. From the three models built, it was found that the SVM model using an initial dataset which was balanced using ADASYN and searching for the best parameters using grid search as a hyperparameter optimization technique was able to carry out good detection and short computing time. This model is able to detect fraudulent transactions with 99% sensitivity and 99% specificity and the shortest model training time among the other two models.

With the continuous development of the economy, the widespread use of credit cards shows a growing trend. However, simultaneously, the risk of credit card fraud still exists and cannot be ignored. This article utilizes bank card data for model training, with a particular focus on addressing the high dimensionality and imbalance of data in credit card transactions. In terms of model construction, it introduces a reinforcement learning-based Long Short-Term Memory (LSTM) network. Additionally, to improve the classification and recognition performance of the model, ensemble learning algorithms and convolutional neural networks are employed for enhancement. The research results indicate that, compared to other methods, the approach proposed in this article demonstrates a higher level of performance in the AUC (Area Under the Curve) metric of 0.92, effectively preventing financial risks, and providing a more reliable solution for credit card fraud detection. In conclusion, after comparing numerous models, it is evident that LSTM is an effective algorithm choice, particularly suitable for credit card fraud detection tasks.

The widespread use of credit cards has led to an increase in fraud. Credit card fraud detection involves identifying and preventing fraudulent transactions, either in real-time or post-occurrence. This paper seeks to create an advanced credit card fraud detection model via data mining. The proposed method comprises four essential steps: data acquisition, preprocessing, feature selection, and fraud detection. A recent balanced dataset is acquired, containing 28 anonymized features about the credit card transactions, along with the transaction amount and the transaction label (normal or fraud). The dataset is then explored to clean it and ensure its integrity. Feature selection is executed via the Energy Valley Optimization (EVO) metaheuristic method, employing the accuracy value of the Light Gradient Boosting Machine (LGBM) as the fitness function. This results in a 30% reduction in features. The reduced dataset is then input into the classification step, where an ensemble soft voting model is applied. This model encompasses Extra Trees, eXtreme Gradient Boosting (XGBoost), and Categorical Boosting (CatBoost) classifiers. The proposed model averages the probability of the three classifiers for each label and outputs the label with the highest average probability. The proposed method is assessed using recall, precision, accuracy, and F1-score, attaining 99.89%, 99.58%, 99.74%, and 99.74%, respectively. The proposed approach is evaluated against existing machine learning classifiers and relevant studies using the same dataset, showcasing enhanced performance and confirming its efficacy in identifying credit card fraud.

Due to a rapid advancement in the electronic commerce technology, the use of credit cards has dramatically increased. As credit card becomes the most popular mode of payment for both online as well as regular purchase, cases of fraud associated with it are also rising. In this paper, we model the sequence of operations in credit card transaction processing using a hidden Markov model (HMM) and show how it can be used for the detection of frauds. An HMM is initially trained with the normal behavior of a cardholder. If an incoming credit card transaction is not accepted by the trained HMM with sufficiently high probability, it is considered to be fraudulent. At the same time, we try to ensure that genuine transactions are not rejected. We present detailed experimental results to show the effectiveness of our approach and compare it with other techniques available in the literature.