scholarly journals A Performance Analysis of Detecting Credit Card Fraud by using CT18 Method

2019 ◽  
Vol 8 (4) ◽  
pp. 7257-7260
Keyword(s):  
Performance Analysis ◽  
Everyday Life ◽  
Unsupervised Learning ◽  
Credit Card ◽  
Online Shopping ◽  
Credit Cards ◽  
Significant Component ◽  
Grouping Problem ◽  
Illegal Activities ◽  
Day By Day

Credit cards are a significant component of everyday life. Whether purchasing gas and supermarket stores or reserving a hotel and lease a car for the next holiday. Credit cards are a pleasant and safe type of client payment. Advantages that differ from harm security on payments to the convenience of disputing suspect fees or suspicious activity make credit cards such an appealing form of transaction. It takes an hour for any time activities, online shopping, and paperless system. As the amount of credit card customers rises day by day, significant illegal activities eventually enhance. CT18 technique is the procedure for categorizing information directed at reformatting observations into CT18, whereby each observation belongs to the closest mean cluster. This is one of the simplest unsupervised learning algorithms that solve the well-known grouping problem

scholarly journals Analisis Persepsi Bendahara Pengeluaran Atas Aspek Kepentingan dan Kinerja Pengguna dan Mitra Perbankan Dalam Penerapan Kartu Kredit Pemerintah

2021 ◽  
Vol 2 (1) ◽  
pp. 17-34
Author(s):  
Ali Said ◽  
Sutiono Sutiono
Keyword(s):  
Performance Analysis ◽  
Customer Service ◽  
Credit Card ◽  
Credit Cards ◽  
Training Center ◽  
Online Questionnaire ◽  
Customer Complaint ◽  
Government Credit ◽  
And Performance ◽  
And Training

Abstract The Indonesian government has implemented government credit card since July 2019. This research provides importance and performance analysis of implementing government credit cards in ministries/agencies of Indonesia. This study collected empirical data from an online questionnaire which was distributed to alumni of the expenditure treasurer training organized by the Budget and Treasury Education and Training Center. The selected samples from 222 respondents, was processed using importance and performance analysis. The results of this empirical research shows the performance of KKP holders and the customer service of KKP issuing banks was still below expectations according to the perception of spending treasurers. KKP holders must be provided with intensive socialization on the use of KKP and customer complaint services at KKP issuing banks must be improved. Other results based on non implementing KKP treasurer perceptions, there are still some obstacles faced by ministries/agencies at the implementation of government credit cards. The results of this study cannot be generalized to the implementation of KKP in Indonesia, because of limited number of respondent samples. Abstrak Pemerintah Indonesia telah menerapkan metode pembayaran tagihan dari rekanan pemerintah menggunakan uang persediaan kartu kredit pemerintah mulai bulan Juli tahun 2019. Penelitian ini bertujuan untuk menganalisis kepentingan dan kinerja atas penerapan kartu kredit pemerintah pada kementerian/lembaga. Data penelitian diperoleh melalui kuesioner online yang disebar melalui media sosial whatsapp. Responden penelitian merupakan alumni pelatihan bendahara pengeluaran yang diselenggarakan oleh Pusdiklat Anggaran dan Perbendaharaan. Sebagian sampel penelitian yang berjumlah 222 responden diolah menggunakan analisis kepentingan dan kinerja. Hasil penelitian menunjukkan bahwa kinerja pemegang KKP dan layanan bank penerbit KKP masih di bawah harapan menurut persepsi bendahara pengeluaran. Pemegang KKP harus diberikan sosialisasi penggunaan KKP yang memadai dan layanan keluhan pelanggan pada bank penerbit KKP harus ditingkatkan. Selain itu masih ditemukan beberapa kendala yang dihadapi oleh kementerian/lembaga pada saat penerapan kartu kredit pemerintah. Dengan keterbatasan jumlah sampel responden, maka hasil penelitian ini tidak dapat digeneralisasi untuk penerapan KKP di Indonesia.

scholarly journals The Impact of Behavioral Finance on Credit Card Users in Chennai City

2019 ◽  
Vol 8 (4S3) ◽  
pp. 5-9
Keyword(s):  
Behavioral Finance ◽  
Credit Card ◽  
Online Shopping ◽  
Credit Cards ◽  
Key Factors ◽  
Frequent Change ◽  
Bank Marketing ◽  
Credit Card Usage ◽  
Chennai City ◽  
The Impact

The frequent change in the technology has given rise to many new innovative things in our country. And one among them is the debit and credit cards which people prefer using it for many things. This study aims at identifying the key factors determining the credit card usage like appearance of the card, credit limit, image of the issuer bank, marketing campaign, co-branding offerand also the reasons for using the credit cards like avoidance of risk, prestige power, immediate payment, cash withdrawal facility, safe online shopping by the customers in Chennai city. The factors like convenience, immediate payment, universal acceptance; fraud protection has the higher impact on the customers having credit cards.The study is restricted toChennai city with samples of 100 has been taken for the study by using simple random method.The concluding observation is that there is noted relationship between income of the users of credit cards and the variables determining the choice of credit cards.

Analysis of Various Credit Card Fraud Detection Techniques

2021 ◽  
pp. PP. 13-20
Author(s):  
admin admin ◽  
Keyword(s):  
Data Mining ◽  
Performance Analysis ◽  
Credit Card ◽  
Credit Cards ◽  
Fraud Detection ◽  
Classification Algorithms ◽  
Credit Card Fraud ◽  
Prediction Analysis ◽  
Detection Techniques

Data mining is a technique that is applied to mine valuable information from the rough data. A prediction analysis is an approach that has the potential for forecasting future possibilities based on the recent data. The CCFD is the challenge of prediction in which fraudulent transactions are predicted based on certain rules. There are several stages included in the detection of fraud in credit cards. Various classification algorithms are reviewed with respect to the performance analysis in order to detect fraud in the credit card. The performance is measured with regard to precision.

scholarly journals Fraud prediction for credit card using classification method

2018 ◽  
Vol 7 (3) ◽  
pp. 1083 ◽  
Author(s):  
Er Monika ◽  
Er Amarpreet Kaur
Keyword(s):  
Data Mining ◽  
Credit Card ◽  
Credit Cards ◽  
Insurance Premium ◽  
Mobile Banking ◽  
Classification Methods ◽  
Bayes Method ◽  
Online Exchange ◽  
Fraud Prediction ◽  
Day By Day

With the improvement of innovation like credit cards, debit cards, mobile banking, Internet managing an account is the mainstream medium to exchange the cash starting with one record then onto the next. Credit card is picking up fame day by day which expands the online exchange with the expansion in online shopping, online charge payment, insurance premium and different charges so the extortion cases identified with this are likewise expanding and it puts an extraordinary anxiety on the economy, affecting the two clients and budgetary bodies. It costs cash as well as an awesome measure of time to reestablish the damage done. In this paper, we look whether data mining procedures are valuable to estimate and categorize the client's credit risk score (normal/fraud) to beat the future dangers. The reason for existing is to keep the clients from online exchange by utilizing particular Data mining classification methods. The fakes are ascertained by Naïve Bayes method way to deal with break down the exchange is actual or fake. The exploratory outcome demonstrates that our model has great classification accuracy, recall and precision. 

scholarly journals Predictive Analytics with Machine Learning for Fraud Detection

2021 ◽  
Vol 9 (11) ◽  
pp. 1518-1520
Author(s):  
A Sampath Abhishek
Keyword(s):  
Machine Learning ◽  
Logistic Regression ◽  
Random Forest ◽  
Credit Card ◽  
World Wide ◽  
Online Shopping ◽  
Predictive Analytics ◽  
Fraud Detection ◽  
Digital Transactions ◽  
Day By Day

Abstract: The popularity of online shopping is growing day by day. In financial year 2021, over 40 billion digital transactions worth more than a quadrillion Indian rupees were recorded across the country. As the number of credit card users rise world- wide, the opportunities for attackers to steal credit card details and subsequently, commit fraud are also increasing. Since humans tend to exhibit specific behavioristic profiles, every cardholder can be represented by a set of patterns containing information about the typical purchase category, the time since the last purchase, the amount of money spent etc. So these frauds can be detected through various algorithms mainly random forest and logistic regression. To enhance the boost and build model with much more efficiency adaboost is also added. Keywords: Fraud detection, behavioristic profile, random forest, logistic regression, adaboost

Consumers‟ Acceptance of „Halal‟ Credit Card Services: An Empirical Analysis

2015 ◽  
Vol 3 (1) ◽  
pp. 51 ◽  
Author(s):  
Zaimy Johana Johan ◽  
Lennora Putit
Keyword(s):  
Perceived Control ◽  
Credit Card ◽  
Credit Cards ◽  
Product Knowledge ◽  
Key Factors ◽  
Developing Nation ◽  
Business Transactions ◽  
Factors Influencing ◽  
Financial Credit ◽  
Survey Questionnaires

Many past researches have been carried out in an attempt to continuously understand individuals‟ consumption behaviour. This study was conducted to investigate key factors influencing consumers‟ potential acceptance of halal (or permissible) financial credit card services. Specifically, it anticipated the influence of attitude, social influences and perceived control on consumers‟ behavioural intention to accept such services. In addition, factors such as religiosity and product knowledge were also postulated to affect consumers‟ attitude towards the act of using halal credit cards for any retail or business transactions. Using non-probability sampling approach, a total of 500 survey questionnaires was distributed to targeted respondents in a developing nation but only 220 usable feedbacks were received for subsequent data analysis. Regression results revealed that religiosity and product knowledge significantly influence consumers‟ attitude toward using halal credit card services.  Attitude in turn, subsequently has a significant impact on consumers‟ intention to accept halal financial credit card services. Several theoretical and managerial contributions were observed in this study.   

Design, Development and Comparison of Heuristic Driven Algorithms Based on the Crossed Domain Products’ Reviews for User’s Summarization

2020 ◽  
Vol 13 (5) ◽  
pp. 884-892
Author(s):  
Sartaj Ahmad ◽  
Ashutosh Gupta ◽  
Neeraj Kumar Gupta
Keyword(s):  
Decision Making ◽  
Online Shopping ◽  
Recent Time ◽  
Design Development ◽  
Different Types ◽  
Feature Based ◽  
Use Of Internet ◽  
Day By Day ◽  
Better Than

Background: In recent time, people love online shopping but before any shopping feedbacks or reviews always required. These feedbacks help customers in decision making for buying any product or availing any service. In the country like India this trend of online shopping is increasing very rapidly because awareness and the use of internet which is increasing day by day. As result numbers of customers and their feedbacks are also increasing. It is creating a problem that how to read all reviews manually. So there should be some computerized mechanism that provides customers a summary without spending time in reading feedbacks. Besides big number of reviews another problem is that reviews are not structured. Objective: In this paper, we try to design, implement and compare two algorithms with manual approach for the crossed domain Product’s reviews. Methods: Lexicon based model is used and different types of reviews are tested and analyzed to check the performance of these algorithms. Results: Algorithm based on opinions and feature based opinions are designed, implemented, applied and compared with the manual results and it is found that algorithm # 2 is performing better than algorithm # 1 and near to manual results. Conclusion: Algorithm # 2 is found better on the different product’s reviews and still to be applied on other product’s reviews to enhance its scope. Finally, it will be helpful to automate existing manual process.

scholarly journals Neural mechanisms of credit card spending

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sachin Banker ◽  
Derek Dunfield ◽  
Alex Huang ◽  
Drazen Prelec
Keyword(s):  
Credit Card ◽  
Credit Cards ◽  
Purchase Behavior ◽  
Facilitation Effect ◽  
Product Price ◽  
Personal Credit ◽  
Psychological Mechanisms ◽  
Network Activation ◽  
Payment Instruments ◽  
Reward Network

AbstractCredit cards have often been blamed for consumer overspending and for the growth in household debt. Indeed, laboratory studies of purchase behavior have shown that credit cards can facilitate spending in ways that are difficult to justify on purely financial grounds. However, the psychological mechanisms behind this spending facilitation effect remain conjectural. A leading hypothesis is that credit cards reduce the pain of payment and so ‘release the brakes’ that hold expenditures in check. Alternatively, credit cards could provide a ‘step on the gas,’ increasing motivation to spend. Here we present the first evidence of differences in brain activation in the presence of real credit and cash purchase opportunities. In an fMRI shopping task, participants purchased items tailored to their interests, either by using a personal credit card or their own cash. Credit card purchases were associated with strong activation in the striatum, which coincided with onset of the credit card cue and was not related to product price. In contrast, reward network activation weakly predicted cash purchases, and only among relatively cheaper items. The presence of reward network activation differences highlights the potential neural impact of novel payment instruments in stimulating spending—these fundamental reward mechanisms could be exploited by new payment methods as we transition to a purely cashless society.

scholarly journals Does the visual salience of credit card features affect choice?

2021 ◽  
pp. 1-18
Author(s):  
Matthew D. Hilchey ◽  
Matthew Osborne ◽  
Dilip Soman
Keyword(s):  
Interest Rates ◽  
Random Sample ◽  
Credit Card ◽  
Credit Cards ◽  
Salient Feature ◽  
The Other ◽  
Visual Salience ◽  
Product Features ◽  
Hypothetical Scenario

Abstract Regulators require lenders to display a subset of credit card features in summary tables before customers finalize a credit card choice. Some jurisdictions require some features to be displayed more prominently than others to help ensure that consumers are made aware of them. This approach could lead to untoward effects on choice, such that relevant but nonprominent product features do not factor in as significantly. To test this possibility, we instructed a random sample of 1615 adults to choose between two hypothetical credit cards whose features were shown side by side in tables. The sample was instructed to select the card that would result in the lowest financial charges, given a hypothetical scenario. Critically, we randomly varied whether the annual interest rates and fees were made visually salient by making one, both, or neither brighter than other features. The findings show that even among credit-savvy individuals, choice tends strongly toward the product that outperforms the other on a salient feature. As a result, we encourage regulators to consider not only whether a key feature should be made more salient, but also the guidelines regarding when a key feature should be displayed prominently during credit card acquisition.

Money growth variability and output: evidence with credit card-augmented Divisia monetary aggregates

2020 ◽  
Vol 24 (5) ◽  
Author(s):  
Jinan Liu ◽  
Apostolos Serletis
Keyword(s):  
Financial Stability ◽  
Credit Card ◽  
Negative Impact ◽  
Balance Sheet ◽  
Credit Cards ◽  
Money Growth ◽  
Monetary Policies ◽  
Growth Variability ◽  
Significant Negative Impact ◽  
Growth Volatility

Abstract We reexamine the effects of the variability of money growth on output, raised by Mascaro and Meltzer (1983), in the era of the increasing use of alternative payments, such as credit cards. Using a bivariate VARMA, GARCH-in-Mean, asymmetric BEKK model, we find that the volatility of the credit card-augmented Divisia M4 monetary aggregate has a statistically significant negative impact on output from 2006:7 to 2019:3. However, there is no effect of the traditional Divisia M4 growth volatility on real economic activity. We conclude that the balance sheet targeting monetary policies after the financial crisis in 2007–2009 should pay more attention on the broad credit card-augmented Divisia M4 aggregate to address economic and financial stability.

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