Attention layer integrated BiLSTM for financial fraud prediction

Author:

G R JainishORCID,P Alwin Infant

Publisher

Springer Science and Business Media LLC

Reference29 articles.

1. Iscan C, Kumas O, Akbulut FP, Akbulut A (2023) Wallet-Based Transaction Fraud Prevention Through LightGBM With the Focus on Minimizing False Alarms. IEEE Access 11:131465–131474. https://doi.org/10.1109/ACCESS.2023.3321666

2. PwC’s Global Economic Crime and Fraud Survey 2022: India Insights[online] https://www.pwc.in/consulting/forensics/pwcs-global-economic-crime-and-fraud-survey-2022.html. Accessed Nov 2022

3. Statistica, Public opinion on kind of financial fraud experienced in India as of May 2023[online], https://www.statista.com/statistics/1394713/india-poll-on-kind-of-financial-fraud-experienced/. Accessed May 2023

4. Hilal W, Gadsden SA, Yawney J (2021) Financial Fraud: A Review of Anomaly Detection Techniques and Recent Advances. Expert Syst Appl 193:116429

5. Alarfaj FK, Malik I, Khan HU, Almusallam N, Ramzan M, Ahmed M (2022) Credit Card Fraud Detection Using State-of-the-Art Machine Learning and Deep Learning Algorithms. IEEE Access 10:39700–39715. https://doi.org/10.1109/ACCESS.2022.3166891

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