Enron Corpus Fraud Detection
Lucky Mohanty1, Kirtika Thakur2, G. Manju3
1Lucky Mohanty, Student, B. Tech in Computer Science and Engineering, Department of Computer Science and Engineering, Kattankulathur Campus, SRM Institute of Science and Technology. (Tamil Nadu) India.
2Kirtika Thakur, Student, B. Tech in Computer Science and Engineering, Department of Computer Science and Engineering, Kattankulathur Campus, SRM Institute of Science and Technology. (Tamil Nadu) India.
3Dr. G. Manju, Associate Professor, Department of Computer Science and Engineering, Kattankulathur Campus, SRM Institute of Science and Technologyd. (Tamil Nadu) India.
Manuscript received on 02 April 2019 | Revised Manuscript received on 07 May 2019 | Manuscript published on 30 May 2019 | PP: 315-317 | Volume-8 Issue-1, May 2019 | Retrieval Number: A3329058119/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The main motive behind this work is to identify the person of interest based on the email data from the Enron corpus which is made public for research. Fraud detection is done using artificial neural network (ANN) with Adam optimizer and ReLU activation functions which is a machine learning approach. With advancements in the field of Artificial Intelligence the fraud detection can done effectively in python environment. This work achieves greater accuracy in terms of recall, precision and F1 score. The work can prove useful to various firms that maintain accounting data of the financial transactions that take place in the given organization. The goal is to devise a method that can be implemented on accounting data of an organization, company or firm to identify the individuals susceptible of committing fraudulent activities by manipulating the financial statements to mislead the investors and shareholders. This ultimately aims to reduce the losses suffered by the investors and shareholders by detection of various fraudulent entities in the given organization.
Index Terms: Enron Corpus, Artificial Neural Network, Adam Optimizer, ReLU Activation Function, Fraud Detection
Scope of the Article: Artificial Intelligence