Proceedings of the First International Conference on Advanced Scientific Innovation in Science, Engineering and Technology, ICASISET 2020, 16-17 May 2020, Chennai, India

Research Article

An Efficient Machine Learning Model for Location Aware Credit Fraud and Risk Classification and Detection

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  • @INPROCEEDINGS{10.4108/eai.16-5-2020.2304200,
        author={V.  Muthulakshmi and C.  Saravanakumar and A.  Tamizhselvi},
        title={An Efficient Machine Learning Model for Location Aware Credit Fraud and Risk Classification and Detection},
        proceedings={Proceedings of the First  International Conference on Advanced Scientific Innovation in Science, Engineering and Technology, ICASISET 2020, 16-17 May 2020, Chennai, India},
        publisher={EAI},
        proceedings_a={ICASISET},
        year={2021},
        month={1},
        keywords={machine learning svm deep learning fraud detection risk analysis},
        doi={10.4108/eai.16-5-2020.2304200}
    }
    
  • V. Muthulakshmi
    C. Saravanakumar
    A. Tamizhselvi
    Year: 2021
    An Efficient Machine Learning Model for Location Aware Credit Fraud and Risk Classification and Detection
    ICASISET
    EAI
    DOI: 10.4108/eai.16-5-2020.2304200
V. Muthulakshmi1,*, C. Saravanakumar2, A. Tamizhselvi3
  • 1: Associate Professor, Department of Information Technology St. Joseph’s College of Engineering, OMR, Chennai 600 119, India
  • 2: Associate Professor, Department of Information Technology, St.Joseph’s Institute of Technology, OMR, Chennai - 600119, India
  • 3: Associate Professor, Department of Information Technology, St. Joseph’s College of Engineering, OMR, Chennai 600 119, India
*Contact email: hoditlabaffairs@stjosephs.ac.in

Abstract

Online transaction grows in enormous rate because of the strength of usage by the user. User always use online mode to pay the amount to the respective merchant. Various method of payment is available in the market but credit card is so popular due to the pre credit is assigned to the customer by banker. Card user gets extra time for paying the payment which gives comfortable live to them. Security of the card suffers in various factors such as theft, fraud, illegal access, so it is protected by using modern algorithm with automated capability. Artificial Intelligent algorithms are applied to detect the fraud but that is not achieving enough accuracy. This type of problem is overcome by using location based risk identification model with multidimensional features for analysis. Three phases of processing is carried out namely feature management, risk management and Location awareness. The focus of the model is to protect the credit card frauds in multi level security by identifying the source and location of access. It achieves high level of security when compared to all exiting algorithms with reliable manner.