Comparative study of deep learning explainability and causal ai for fraud detection
Authors
Erum Parkar
Department of Artificial Intelligence and Machine Learning, Symbiosis Institute of Technology, Symbiosis International (Deemed) University, Pune, India
Shilpa Gite
Department of Artificial Intelligence and Machine Learning, Symbiosis Institute of Technology, Symbiosis International (Deemed) University, Pune, India
Symbiosis Centre for Applied Artificial Intelligence, Symbiosis Institute of Technology (Pune Campus), Symbiosis International Deemed University, Pune, India
Sashikala Mishra
sashikala.mishra@sitpune.edu.in
Department of Artificial Intelligence and Machine Learning, Symbiosis Institute of Technology, Symbiosis International (Deemed) University, Pune, India
Biswajeet Pradhan
Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS), School of Civil and Environmental Engineering, Faculty of Engineering and Information Technology, University of Technology Sydney, Australia
Abdullah Alamri
Department of Geology and Geophysics, College of Science, King Saud University, Riyadh, Saudi Arabia
DOI: https://doi.org/10.2478/ijssis-2024-0023 | Journal eISSN: 1178-5608
Language: English
Submitted on: Apr 25, 2024
Published on: Aug 6, 2024
Published by: Macquarie University, Australia
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year
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© 2024 Erum Parkar, Shilpa Gite, Sashikala Mishra, Biswajeet Pradhan, Abdullah Alamri, published by Macquarie University, Australia
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.