Credit card fraud detection remains a critical challenge for financial institutions, particularly due to extreme class imbalance and the continuously evolving nature of fraudulent behavior. This study investigates two complementary approaches: anomaly detection based on multivariate normal...

Association rule mining is a widely used data mining technique in various domains. It enables the identification of trends, frequent patterns, and relationships among the data. This study introduced a new method for mining association rules independently from multiple data sources. It combined...

Batteries are crucial for decarbonising energy storage and mitigating climate change. As the battery industry expands, it faces increasing complexity due to accelerated innovation cycles, rising competition, and growing technological diversity, emphasising the need for cost-effective strategic...

While big data analytics capabilities (BDAC) have been pivotal to retail companies, their effects on innovation capabilities and sustainable performance have not been investigated systematically thus far. Therefore, this study explores the influence of BDAC on the innovation capabilities and...

The financial sector faces mounting challenges in processing vast volumes of high-velocity data to support intelligent, real-time decision-making. Traditional machine learning models often fall short in accuracy, scalability, and responsiveness when dealing with large, dynamic financial...