CONTACTLESS PAYMENTS FRAUD DETECTION METHODS AND IS SOCIETY PREPARED TO RESIST: A CASE STUDY

Authors

  • Jelena Mamčenko Vilnius College of Technologies and Design (LT)
  • Brigita Šustickiene Vilnius College of Technologies and Design (LT)
  • Jūratė Romeikienė Vilnius College of Technologies and Design (LT)

DOI:

https://doi.org/10.17770/sie2023vol2.7159

Keywords:

credit cards, contactless payment, data mining, fraud, unsupervised learning

Abstract

The ability to use contactless payment technologies, non-cash payments and credit card payments is becoming almost an essential requirement for consumers and merchants in today's economic conditions. Different market sectors are rapidly adapting to these technologies and looking for the most convenient, secure, and fastest possible solutions that combine intelligent data processing, security, and business management functions. Millions of debit and credit card holders care about secure payments, the businesses that receive these payments are secure in terms of security, and the operators that process such incoming and outgoing payments are interested in innovative solutions that set them apart from the competition. Amid the COVID-19 pandemic, when e-commerce was growing exponentially, the global market for fraud detection and prevention, currently stands at USD 20.9 billion, and is expected to grow, until 2025 will rise to USD 38.2 billion by the end of the year; holds the market at 12.8 % annually. The US remains the dominant region in this market segment, but European countries are also increasingly investing in fraud prevention and detection solutions, which are growing in demand in Europe due to an increase in cybercrime as well as advanced bots and cyber-attack.

 

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Published

2023-07-03

How to Cite

Mamčenko, J., Šustickiene, B., & Romeikienė, J. (2023). CONTACTLESS PAYMENTS FRAUD DETECTION METHODS AND IS SOCIETY PREPARED TO RESIST: A CASE STUDY. SOCIETY. INTEGRATION. EDUCATION. Proceedings of the International Scientific Conference, 2, 467-477. https://doi.org/10.17770/sie2023vol2.7159