Financial Fraud Detection in Plastic Payment Cards using Isolation Forest Algorithm
Ankaj Kumar1, Gouri Sankar Mishra2, Parma Nand3, Madhav Singh Chahar4, Sonu Kumar Mahto5
1Ankaj Kumar, Department of Computer Science and Engineering, Sharda University, Greater Noida (Uttar Pradesh), India.
2Gouri Sankar Mishra, Department of Computer Science and Engineering, Sharda University, Greater Noida (Uttar Pradesh), India.
3Parma Nand, Department of Computer Science and Engineering, Sharda University, Greater Noida (Uttar Pradesh), India.
4Madhav Singh Chahar, Department of Computer Science and Engineering, Sharda University, Greater Noida (Uttar Pradesh), India.
5Sonu Kumar Mahto*, Department of Computer Science and Engineering, Sharda University, Greater Noida (Uttar Pradesh), India.
Manuscript received on April 28, 2021. | Revised Manuscript received on June 13, 2021. | Manuscript published on June 30, 2021. | PP: 132-136 | Volume-10, Issue-8, June 2021 | Retrieval Number: 100.1/ijitee.G88730510721| DOI: 10.35940/ijitee.G8873.0610821
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Abstract: The need for technology has always found space in Financial Transaction as the number of fraud in financial transactions increases day by day. In this research we have proposed a new methodology by using the isolation forest algorithm and local outlier detection algorithm to detect the financial fraud. A standard data set is used in experimentation to classify a transaction occurred is a fraudulent or not. We have used neural networks and machine learning for classification. We have focused on the deployment of anomaly detection algorithms that is Local Outlier Factor and Isolation Forest algorithm (IFA) on financial fraud transactions data.
Keywords: In This Research We Have Proposed A New Methodology By Using The Isolation Forest Algorithm And Local Outlier Detection Algorithm To Detect The Financial Fraud.