Estimating Financial Fraud through Transaction-Level Features and Machine Learning

• Published in: Mathematics (Basel) Vol. 11; no. 5; p. 1184
• Main Authors: Alwadain, Ayed, Ali, Rao Faizan, Muneer, Amgad
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.03.2023
• Subjects: Accuracy; Algorithms; Artificial intelligence; Automation; Classification; Classifiers; Conditional GAN; Credit card fraud; Datasets; Deep learning; Economic development; Estimation theory; Evaluation; financial fraud; Financial institutions; Fraud; Fraud prevention; Generative adversarial networks; Machine learning; Mathematical research; Methods; Neural networks; Performance evaluation; Policies; prediction; Risk; risk mitigation; Support vector machines; Tables (data); transaction; United States

In today’s world, financial institutions (FIs) play a pivotal role in any country’s economic growth and are vital for intermediation between the providers of investable funds, such as depositors, investors and users. FIs focus on developing effective policies for financial fraud risk mitigation howe...