Detection and Control of Credit Card Fraud Attacks in Sliding Window with Exponential Forgetting

Artikel i vetenskaplig tidskrift, 2025

Credit card fraud causes significant financial losses and frequently
occurs as fraud attack, defined as short-term sequence of fraudulent
transactions associated with high transaction rates and amounts,
business areas historically tied to fraud, unusual transaction times
and locations and different types of errors.

Confidence interval method in the moving window with exponential
forgetting is proposed in this paper which allows to capture recent
changes in the shopping behaviour of the cardholder, detect fraudulent
amounts and mitigate the attack. Fraud risk scoring method
is used for estimation of the intensity of the fraudulent activity via
monitoring of the transaction rates, merchant category codes, times
and some other factors for detection of the start of the attack.

The development and verification are based on detailed analysis of
the transaction patterns from the dataset, which represents an extensive
collection of around 24.4 million credit card transactions from
IBM financial database. Recommendations for further development
of the detection techniques are also presented.