Proceedings of 4th International Conference on Recent Trends on Electronics, Information, Communication & Technology (RTEICT-2019), pp. 1030-1035.
ISSN/ISBN: Not available at this time. DOI: 10.1109/RTEICT46194.2019.9016804
Abstract: Due to the internet and social media age, a huge volume of ecommerce sites are using online platform for their business transactions. The advantage of e-commerce and online payable sites are faster service and time saving. Majority of the customers that use ecommerce sites carry out their transactions using credit cards. But the modern fraudsters are consuming the Internet platform to attempt fraud with ease. An attempt has been made to enlighten fraud in credit card domain using Benford's Law and deep learning Autoencoders algorithm in neural networks. To test the efficiency of our model, random forest binary classification models are used as a comparison. The model shows better results for our proposed model than existing solutions in terms of recall, precision and ROC-AVC curve.
Bibtex:
@INPROCEEDINGS{,
author={Kurien, Kaithekuzhical Leena and Chikkamannur, Ajeet A.},
booktitle={2019 4th International Conference on Recent Trends on Electronics, Information, Communication & Technology (RTEICT)},
title={Benford's Law and Deep Learning Autoencoders: An approach for Fraud Detection of Credit card Transactions in Social Media},
year={2019},
volume={},
number={},
pages={1030-1035},
doi={10.1109/RTEICT46194.2019.9016804}}
Reference Type: Conference Paper
Subject Area(s): Accounting, Computer Science