Financial Fraud Detection Using Value-at-Risk With Machine Learning in Skewed Data
Abdullahi Ubale Usman,
Sunusi Bala Abdullahi,
Yu Liping
et al.
Abstract:The significant losses that banks and other financial organizations suffered due to new bank account (NBA) fraud are alarming as the number of online banking service users increases. The inherent skewness and rarity of NBA fraud instances have been a major challenge to the machine learning (ML) models and happen when non-fraud instances outweigh the fraud instances, which leads the ML models to overlook and erroneously consider fraud as non-fraud instances. Such errors can erode the confidence and trust of cus… Show more
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