Resumen
National Payment Switches (NPSs) and International Payment Switches (IPSs), including major players such as SWIFT, Mastercard, and CHIPS, have become vital to the financial infrastructure, facilitating secure and efficient transactions among local financial institutions. Nonetheless, the growing adoption of digital payments has heightened the risk of financial fraud. Consequently, NPSs, under the direct ownership of Central Banks (CBs), are increasingly adopting advanced technologies, such as cognitive computing, to bolster their fraud detection capabilities in their respective countries. This article delves into the role of cognitive computing in detecting financial fraud within NPSs. It examines the advantages of cognitive computing in recognising patterns of fraudulent behaviour and analysing vast amounts of data. Additionally, the study highlights the importance of focusing on how cognitive computing can augment traditional fraud detection methods, such as rule-based systems and data analytics. Nineteen real-world cases from eighteen countries are analysed, exploring the cognitive computing tools employed by NPSs to identify fraudulent transactions. The challenges and limitations of implementing cognitive computing in fraud detection and potential solutions to address these issues are identified. The primary assumption that cognitive computing is crucial for detecting financial fraud in NPSs is substantiated. Its ability to analyse large datasets and pinpoint patterns of fraudulent behaviour proves invaluable for financial institutions seeking to protect themselves against financial fraud in a progressively digital world. The conclusions drawn from the overview of the cases aim to identify best practices, potentially trigger new benchmarking standards, and facilitate the development of integrated cross-border solutions to combat financial fraud on a global scale effectively. The purpose of this research is to examine the role of cognitive computing in detecting financial fraud within NPSs, identify its advantages, challenges and limitations, and provide real-world case examples.