scholarly journals Prospects and challenges in the investigation of credit card fraud in Vall Region of the Gauteng Province, South Africa

2022 ◽  
Vol 27 ◽  
pp. 959-967
Author(s):  
Morero Motseki
Keyword(s):  
Credit Card ◽  
Justice System ◽  
Phenomenological Approach ◽  
Research Approach ◽  
Sampling Techniques ◽  
Snowball Sampling ◽  
Gauteng Province ◽  
Credit Card Fraud ◽  
Online Transactions ◽  
And Training

Today use of Credit Card even in developing countries has become a common scenario. People use it to shop, pay bills and for online transactions. But with increase in number of Credit Card users, the cases of fraud in Credit Card have also been on rise. Credit Card related frauds cause globally a loss of billions of Rands. Credit Card fraud can be done in numerous ways. The article begins with an examination of the extent of the challenge and response by the relevant stakeholders, especially the Criminal Justice System (CJS). This study was carried out utilising a qualitative research approach with a convenience, purposive and snowball sampling techniques. Thirtynine (39) interviews were conducted to solicit the views of the participants and police investigators from Vanderbijlpark, Sebokeng, Sharpeville and Vereeniging police stations, members of the community, and victims of credit card fraud were interviewed. These interviews were analysed according to the phenomenological approach, aided with the inductive Thematic Content Analysis (TCA) to identify the participants’ responses and themes. The findings indicated that the extent of credit card fraud in Vaal region is reaching alarming rates. Based on the findings, the authors provided recommendations such as: police investigators being taken for regular workshops and training on how to investigate sophisticated methods used by perpetrators such as technology, awareness in the society about credit card fraud should be prioritised and enhanced. This study recommends that the CCTV cameras should be installed in the ATM, where cases of credit card are taking place. In addition, the police be visible in the areas which are most prevalent to credit card fraud.

scholarly journals Credit Card Fraud Detection using Deep Learning based on Neural Network and Auto-encoder

2020 ◽  
Vol 9 (5) ◽  
pp. 1140-1143
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Credit Card ◽  
Online Media ◽  
Credit Card Fraud ◽  
Online Transactions ◽  
The Past ◽  
Past Behavior ◽  
The Neural Network ◽  
The Comparative Study

Credit card fraud is an event problem and fraud detecting techniques getting more sophisticated each day. Mainly internet is becoming more common in almost every domain. Online transactions, shopping, and e-commerce are expanding step by step. Due to which in the online payment system, fraudulent activities have also increased. It has cost banks and their customers a loss of billions of rupees. The techniques used now a day detects the anomaly only after the fraud transaction takes place. The intruders have found ways to crack the system loopholes and defeat the security. These frauds are not consistent in their actions, they constantly alter. Thus, Artificial Intelligent (AI) algorithms are used to detect the behavior of such activity by learning the past behavior of the transaction of the users. An unsupervised algorithm is used to detect online transactions, as fraudsters commit fraud once by online media and then move on to other techniques. This paper discusses the performance analysis and the comparative study of the two Deep Learning algorithms which include auto-encoder and the neural network. In this paper accuracy, precision, recall, and AUC curve are considered as a model evaluation factor.

scholarly journals Insights into the Skill Development Issues of Management Jobs: A Study on RMG and Textile Sectors of Bangladesh

2018 ◽  
Vol 14 (12) ◽  
pp. 56
Author(s):  
Saiful Islam ◽  
Tasneem Nabila Islam
Keyword(s):  
Skill Development ◽  
Leadership Skills ◽  
Research Approach ◽  
Development Programs ◽  
Snowball Sampling ◽  
Breach Of Contract ◽  
Managerial Skills ◽  
Hr Managers ◽  
Depth Interviews ◽  
And Training

The purpose of this study is to provide an insight into the skill development and training related issues of the management jobs of textile and garments sector of Bangladesh which includes the skills requirements, differences in the skills of domestic managers and expatriates, local training facilities and barriers companies confront while sending their staffs abroad for training. A qualitative research approach has been adopted in this study where data has been collected through 30 in-depth interviews based on convenient and snowball sampling. The findings indicate that certain skills of domestic managers are quite poor like English proficiency, presentation skills, leadership skills, decision making skills. The RMG and textile firms send their employees to Germany, China, UK, USA, Japan and other countries for training but they encounter barriers like visa issues, breach of contract by the employees etc. in this attempt. Government, RMG and textile industries and various trade bodies, educational and training institutions should step up to organize training, develop skill-oriented curriculum to eliminate the reasons of hiring expats. The outcome of this study can be a source material through which HR managers can identify the scarce managerial skills and devise training and skill development programs accordingly not only in Bangladesh, but also in similar developing countries.

scholarly journals Multifactor Authentication over Credit Card Fraud Detection and Prevention

2020 ◽  
Vol 9 (9) ◽  
pp. 680-685
Keyword(s):  
Face Recognition ◽  
Credit Card ◽  
Fraud Detection ◽  
Online Banking ◽  
Scanning System ◽  
User Friendliness ◽  
Credit Card Fraud ◽  
Online Transactions ◽  
Multifactor Authentication ◽  
Online Methods

Online banking becomes most used method for banking transaction now days. Now the trend is turning towards digitization and so is the population going towards the same thing. People often go to the credit/debit card, Net Banking, etc. online methods. Confidentiality may be hacked during online transactions. To reduced, fraud online activities so, as to secure the data by a two-step authentication method. The primary step of authentication is to verifying OTP. Once the OTP is verified, face recognition will be done. The data is analyzed and the results for both the valid and invalid transactions are sent to the Bank. A new card scanning system has important factor such as most safety, user-friendliness, etc. The application's importance is to mitigate credit card fraud through Face device awareness. The customers get both most usable and highly secure online banking application.

scholarly journals Artificial Intelligence based Credit Card Fraud Identification using Fusion Method

2019 ◽  
Vol 8 (4) ◽  
pp. 4876-4878
Keyword(s):  
Artificial Intelligence ◽  
Credit Card ◽  
Credit Card Fraud ◽  
Online Transactions ◽  
Detection Algorithms ◽  
Improve Accuracy ◽  
Multiple Detection ◽  
Low Probability ◽  
Verification Process ◽  
Design Ideas

Increase of online transactions has given a greater scope for increasing of credit card frauds. In this work we develop a general framework with Artificial Intelligence based Hadoop. Also that fuses multiple detection algorithms to improve accuracy, reliability. Further to support large amount of transactions storage. The workflow satisfies the design ideas of current credit card fraud identification systems. The verification process for all the transactions is implemented. If incoming transaction that passed through trained model with low probability then it is rejected.

scholarly journals Effect of COVID-19 on acquisition of employable skills among national service personnel in Ghana

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Moses Segbenya ◽  
Sally Abena Baafi-Frimpong ◽  
Nana Yaw Oppong
Keyword(s):  
Online Teaching ◽  
Survey Design ◽  
Sampling Techniques ◽  
National Service ◽  
Snowball Sampling ◽  
Cross Sectional ◽  
Content Type ◽  
Service Personnel ◽  
Job Opportunities ◽  
And Training

PurposeThis study examined the effect of COVID-19 on the acquisition of employable skills among national service personnel in Ghana.Design/methodology/approachThe study adopted the cross-sectional descriptive survey design from the positivist paradigm to collect data from a sample of 2,263 out of a population of 77,962 trainees (national service personnel) posted to the public (85.1%) and the private (14.9%) sectors for the 2019/2020 service year. Sampling techniques were simple random, stratify and snowball sampling techniques and Google form softcopy questionnaire was used for data collection.FindingsThe study found that COVID-19 had made workplaces and work schedules very risky for trainees' acquiring employable skills in Ghana because their employers/trainers' were unable to provide adequate PPEs for trainees. Preventive measures such as mandatory leaves, reduced workload/working hours and shift system had reduced the duration for acquiring employable skills which could affect employability and aggravate graduate unemployment in Ghana. The sustainability and quality of job opportunities presented by COVID-19 to graduate trainees-farming; trading and online teaching could also not be guaranteed.Research limitations/implicationsIt was recommended that employers/trainers should provide adequate PPEs, introduce teleworking with the necessary tools and training for their trainees. Educational institutions should provide work-based learning methods in their curricula to enhance employable skills for national service graduates. Government's support for trainees venturing into self-employed job opportunities presented by the COVID-19 was also recommendedPractical implicationsIt was recommended that employers/trainers should provide adequate PPEs, introduce teleworking with the necessary tools and training for their trainees. Government's support for trainees venturing into self-employed job opportunities presented by the COVID-19 was also recommended.Originality/valueThis paper has not been published anywhere.

scholarly journals Analysis of Credit Card Fraud detection using Machine Learning models on balanced and imbalanced datasets

2021 ◽  
Vol 9 (7) ◽  
pp. 846-852
Keyword(s):  
Machine Learning ◽  
Logistic Regression ◽  
Predictive Models ◽  
Credit Card ◽  
Fraud Detection ◽  
Classification Algorithms ◽  
Learning Models ◽  
Credit Card Fraud ◽  
Online Transactions ◽  
Machine Learning Models

With the advent of modern transaction technology, many are using online transactions to transfer money from one person to another. Credit Card Fraud, a rising problem in the financial department goes unnoticed most of the time. A lot of research is going on in this area.The Credit Card Fraud Detection project is developed to spot whether a new transaction is fraudulent or not with the knowledge of previousdata. We use various predictive models to ascertain how accurate they are in predicting whether a transaction is abnormalor regular. Techniques like Decision Tree, Logistic Regression, SVMand Naïve Bayes are the classification algorithms to detect non-fraud and fraud transactions.

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