A Survey and a Credit Card Fraud Detection and Prevention Model using the Decision Tree Algorithm

Today, many people prefer online payment methods due to the rapid growth in cashless electronic transactions. Credit and debit cards are most popular but prone fraud nature of their use tendency fraudsters access details. This study proposes a theoretical credit detection prevention model using Decision Tree Algorithm (DCA). Moreover, survey questionnaire was used investigate students' perceptions card incidents. Data were collected from 102 students different universities countries around world. The results showed that 95.9% respondents knew how credit/debit occurs, while 4.1% them did not. Finally, 81.6% expressed willingness tool based on proposed prevent or detect