Credit Card Fraud Identification Using Calibrated K nearest Neighbor

Amit S. Vaishnav¹ , Namrata S. Shroff²

Section:Research Paper, Product Type: Journal
Vol.12 , Issue.2 , pp.1-5, Apr-2024

Online published on Apr 30, 2024

Copyright © Amit S. Vaishnav, Namrata S. Shroff . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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Abstract :
Credit card fraud has become a significant concern in today`s digital world, leading to substantial financial losses for individuals and businesses alike. Detecting fraudulent transactions accurately and efficiently is crucial for maintaining the security of financial systems. The proposed method combines the power of KNN, a popular classification algorithm, with calibration techniques to enhance the fraud identification performance. Calibration is employed to adjust the probabilities assigned by the KNN algorithm, allowing for more accurate classification decisions and better control over the false positive rate. To evaluate the effectiveness of the proposed approach, comprehensive experiments are conducted on a benchmark credit card fraud dataset. The results demonstrate that the calibrated KNN method outperforms the traditional KNN classifier in terms of both accuracy and other performance parameters. The calibrated KNN approach achieves higher fraud detection rates and produces well-calibrated probability estimates, reducing the risk of false alarms or missed fraud cases. This research contributes to the advancement of credit card fraud detection systems and provides valuable insights for financial institutions and individuals concerned with safeguarding against fraudulent activities.

Key-Words / Index Term :
Calibrated KNN, KNN classifier, Fraud, Fraudulent and Credit card

References :
[1] Srinivasa Rao Dammavalam, Md Mukheed, “Credit Card Fraud Detection Using Machine Learning�, International Journal of Advances in Engineering and Management, Vol.5, Issue.1, pp.147-154, 2023.
[2] N.S. Shroff, A.S. Vaishnav, “A Review of Credit Card Fraud Detection Using Machine Learning�, International Journal of Scientific Research in Network Security and Communication, Vol.11 Issue.2, pp.1-6, 2023.
[3] AnastasiiaIzotova, Adel Valiullin, “Comparison of Poisson process and machine learning algorithms approach for credit card fraud detection� Elsevier, Vol.186, pp.721-726, 2021.
[4] Manoj Kumar Reddy Mallidi, Yeshwanth Zagabathuni, “Analysis of Credit Card Fraud detection using Machine Learning models on balanced and imbalanced datasets�, International Journal of Emerging Trends in Engineering Research, Vol.9, Issue.7, pp.846-852, 2021.
[5] Rashmi More, Suresh Shirgave, Chetan J Awati, Rashmi Deshmukh “Credit Card Fraud Detection Using Supervised Learning Approach�, International Journal of Scientific & Technology Research, Vol.9 Issue.10, pp.216-219, 2020.
[6] Andhavarapu Bhanusri, K.Ratna Sree Valli , P.Jyothi , G.Varun Sai , R.Rohith Sai Subash, “Credit card fraud detection using Machine learning algorithms�, Journal of Research in Humanities and Social Science, Vol.8 Issue.2, pp.4-11, 2020.
[7] Varun Kumar K S, Vijaya Kumar V G, Vijay Shankar A, Pratibha K, “Credit Card Fraud Detection using Machine Learning Algorithms�, International Journal of Engineering Research & Technology, Vol.9, Issue.7, pp.1526-1530, 2020.
[8] A. A. Taha, S. J. Malebary, "An Intelligent Approach to Credit Card Fraud Detection Using an Optimized Light Gradient Boosting Machine," IEEE, Vol.8, pp.25579-25587, 2020.
[9] Vaishnavi Nath Dornadula, S Geetha, "Credit Card Fraud Detection using Machine Learning Algorithms�, Elsevier, Vol.165, pp.631-641, 2019.
[10] S P Maniraj, Aditya Saini, Swarna Deep Sarkar, Shadab Ahmed, “Credit Card Fraud Detection using Machine Learning and Data Science�, International Journal of Engineering Research & Technology, Vol.8, Issue.9, pp.110-115, 2019.
[11] Suresh K Shirgave, Chetan J. Awati, Rashmi More, Sonam S. Patil, “A Review On Credit Card Fraud Detection Using Machine Learning�, International Journal of Scientific & Technology Research, Vol.8, Issue.10, pp.1217-1220, 2019.
[12] Hamzah Ali Shukur, Sefer Kurnaz, “Credit Card Fraud Detection using Machine Learning Methodology�, International Journal of Computer Science and Mobile Computing, Vol.8, Issue.3, pp.257-260, 2019.
[13] D. Tanouz, R. R. Subramanian, D. Eswar, G. V. P. Reddy, A. R. Kumar, C. V. N. M. Praneeth, "Credit Card Fraud Detection Using Machine Learning," 2021 5th International Conference on Intelligent Computing and Control Systems (ICICCS), pp.967-972, 2021.
[14] M. Azhan, S. Meraj, "Credit Card Fraud Detection using Machine Learning and Deep Learning Techniques," 2020 3rd International Conference on Intelligent Sustainable Systems (ICISS), pp.514-518, 2020.