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Title: :  Fraud detection using machine learning
PaperId: :  25010
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 10 Issue 5 2024
DUI:    16.0415/IJARIIE-25010
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
Manoj MCMR University

Abstract

computer engineering
Machine Learning Techniques, Supervised Learning, Unsupervised Learning Decision Trees, Neural Networks, Anomaly Detection, Feature Engineering, Data Preprocessing Model Evaluation (using metrics such as AUPR and AUROC), Imbalanced Datasets: Fraudulent vs Non - fraudalent cases Part-I: Financial Fraud Real-world Examples Banking sector E-commerce sector Insurance sector Python-based implementation for above sectors Part-II Case Studies Pattern Recognition Predictive Analytics Cybersecurity.
One of the key problem faced by different industry domains is fraud detection, especially in finance, e-commerce and insurance where companies bears huge financial loss due to fraudulent activities. This research focuses on how machine learning can help in improving the accuracy and intelligence of fraud detection systems. We will introduce typical fraud detection and show the limitation of these methods, so that leads to the method update into machine learning algorithm. In our analysis, we show how models from different learning families (like decision trees, neural networks and anomaly detection) are trained to detect patterns that could help pinpoint fraudulent behaviour or risky transactions. Moreover, we look into what makes feature engineering, data preprocessing and model evaluation as important components in developing a strong fraud detection system. The real-world use-cases of machine-learning-helped fraud detection and the challenges that ruin the expectation, courtesy — case studies in dealing with imbalanced data and changing patterns in fraudulent activities. Such research highlights the capacity of machine learning to modernize fraud detection approaches, and offers implications for future study to better this detection capability and effectively tackle new threats. In this paper, we survey and compare the performance of different machine learning algorithms (such as decision tree, support vector machine (SVM), random forest, deep learning models) for Given fraud detections across various domains such as finance business transactions, healthcare domain activities & e-commerce portal. ML, powered by supervised and unsupervised learning techniques can find anomalies, predict or different types of fraud transactions, and even adjust to previously unidentified patterns of fraud. It delves deeper into problems such as imbalances in the datasets and interpretability of models explaining approaches such as oversampling, engineering features and explainable AI. The experiment results show that ML dramatically raised fraud detection accuracy and efficiency, even used to decrease false positives while detecting on time predictions.

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IJARIIE Manoj M. "Fraud detection using machine learning" International Journal Of Advance Research And Innovative Ideas In Education Volume 10 Issue 5 2024 Page 681-685
MLA Manoj M. "Fraud detection using machine learning." International Journal Of Advance Research And Innovative Ideas In Education 10.5(2024) : 681-685.
APA Manoj M. (2024). Fraud detection using machine learning. International Journal Of Advance Research And Innovative Ideas In Education, 10(5), 681-685.
Chicago Manoj M. "Fraud detection using machine learning." International Journal Of Advance Research And Innovative Ideas In Education 10, no. 5 (2024) : 681-685.
Oxford Manoj M. 'Fraud detection using machine learning', International Journal Of Advance Research And Innovative Ideas In Education, vol. 10, no. 5, 2024, p. 681-685. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/Fraud_detection_using_machine_learning_ijariie25010.pdf (Accessed : ).
Harvard Manoj M. (2024) 'Fraud detection using machine learning', International Journal Of Advance Research And Innovative Ideas In Education, 10(5), pp. 681-685IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/Fraud_detection_using_machine_learning_ijariie25010.pdf (Accessed : )
IEEE Manoj M, "Fraud detection using machine learning," International Journal Of Advance Research And Innovative Ideas In Education, vol. 10, no. 5, pp. 681-685, Sep-Oct 2024. [Online]. Available: https://ijariie.com/AdminUploadPdf/Fraud_detection_using_machine_learning_ijariie25010.pdf [Accessed : ].
Turabian Manoj M. "Fraud detection using machine learning." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 10 number 5 ().
Vancouver Manoj M. Fraud detection using machine learning. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2024 [Cited : ]; 10(5) : 681-685. Available from: https://ijariie.com/AdminUploadPdf/Fraud_detection_using_machine_learning_ijariie25010.pdf
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