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Credit Card Fraud Detection System in UK: A Case Study on Royal Bank of Scotland Group

1. Introduction

The research carries a discussion about the credit card fraud detection system in UK by analyzing the case study of Royal bank of Scotland. It discusses the reason behind implementation of such detection system for fraud credit cards.

1.1 Aim of research study

The primary aim of this research work is to analyze the complete system of fraud credit card detection. It also aims to highlight the technology or technological tools used for setting up a credit card fraud detection system.

1.2 Objective of research study

  • To scrutinize the whole analysis of credit card fraud detection system by using a case study of Royal bank of Scotland.
  • To deeply analyze and evaluate the process and the working of the system of fraud card detection.
  • To study the technology used for the set up of this detection system.
  • To understand the importance of credit card fraud detection system implemented by Royal bank of Scotland.

1.3 Hypothesis

  • The credit card fraud detection system helps Royal bank of Scotland to detect fraudulence and is thus beneficial for the organization.
  • The credit card fraud detection system is not beneficial for Royal bank of Scotland and doesn’t produce any useful impact on their working or performance.

2. Literature review

2.2 Credit card fraud detection system

According to Sharma and Panigrahi (2013), credit card usage has increased the chances of fraudulence. Many illegal companies are there who are making profits by giving services of credit cards and it has been found that people are trending (more than earlier) for credit card payments. Some other persons are there who take advantage of credit card users by promising them to provide services at low cost. In this context Wei et al. (2013) stated that Royal Bank of Scotland is just trying to stop or reduce such frauds so that people become aware of existence of such things. Because payments through credit card has increased the number of credit card users and with such increasing number of users frauds are also taking place. On the other hand, credit card fraud detection system is supported by different technological tools and algorithm.

2.3 Analysis of credit card fraud detection system with the help of different technologies and tools

Large scale data mining and artificial intelligence is the main technology on which the system of credit card fraud detection is dependent. Apart from this fuzzy algorithm, genetic programming etc. are also used for such system. The system prevents leakage of any personal detail of the user and this the main reason behind implementation of the system. Few years back, Royal bank of Scotland faced loss due to lost of customers. And it was all because of increase in credit card frauds. This affected the bank’s bane or images as customers withdrew their shares. Thus this system helps the bank to maintain security of data.

2.4 Importance of credit card fraud detection system

Credit card fraud detection system helped the Royal Bank of Scotland to inspect the reason behind credit card frauds. It helped the experts to keep a proper record of credit card users of their bank. And made easy for the experts or bankers to motivate or alert the customers behind such frauds.

2.5 Summary

Credit card fraud detection system needs technological and algorithm support as it involves advanced technology for maintain security of highly confidential data. Royal bank of Scotland has implemented this system for securing the data like passwords or personal details of credit card users. It made the bankers to aware their customers about the ways through which fake servicemen ask for their credit card details.

3. Research methodology

3.1 Research approach

Inductive approach is adopted by the research for carrying out this research work. Inductive research is also known as top to bottom research which helps to interlink different theories and principles.

3.2 Research design

For any research work, the most important thing is its presentation style and this is what research design helps to cope with. For this research, description and experimental research design has been utilized.

3.3 Research philosophy

Research philosophy makes the process of data collection method easy and supportive as it is done with the help of various philosophies based on the topic of the dissertation.

3.4 Data collection approach

Primary data acts as a first hand information which makes the researcher to directly connect the views of the targeted audience with the reality of the research topic. It makes the researcher to think deeply and analyze the whole research work while acquiring knowledge.

3.5 Sample Size

5 middle-level of employees and 5 higher or top level of employees have been interviewed for the collection of primary data.

3.6 Research ethics

It forms basis of data collection. It makes researcher to collect data while following the ethical behavior and code of conducts.

3.7 Limitations

Time and budget requirement are the major limitations of this research work.


Duman, E., and Elikucuk, I. (2013). Solving credit card fraud detection problem by the new metaheuristics migrating birds optimization. In Advances in Computational Intelligence (pp. 62-71).Springer Berlin Heidelberg.

Sharma, A., and Panigrahi, P. K. (2013). A review of financial accounting fraud detection based on data mining techniques. arXiv preprint arXiv:1309.3944.

Woźniak, M., Graña, M., and Corchado, E. (2014).A survey of multiple classifier systems as hybrid systems. Information Fusion, 16, 3-17.

Wei, W., Li, J., Cao, L., Ou, Y., and Chen, J. (2013).Effective detection of sophisticated online banking fraud on extremely imbalanced data. World Wide Web, 16(4), 449-475.

Akhilomen, J. (2013). Data mining application for cyber credit-card fraud detection system.In Advances in Data Mining. Applications and Theoretical Aspects (pp. 218-228). Springer Berlin Heidelberg.

Gaber, C., Hemery, B., Achemlal, M., Pasquet, M., and Urien, P. (2013).Synthetic logs generator for fraud detection in mobile transfer services. In Collaboration Technologies and Systems (CTS), 2013 International Conference on (pp. 174-179). IEEE.

Bahnsen, A. C., Stojanovic, A., Aouada, D., and Ottersten, B. (2014).Improving credit card fraud detection with calibrated probabilities.In Proceedings of the fourteenth SIAM International Conference on Data Mining (pp. 677-685).

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