Hierarchical risk assessment of digital financial fraud: a multi-criteria analysis

Purpose The present study aims to identify and evaluate the key determinants of digital financial fraud (DFF) while also establishing a hierarchical structure of various DFF types based on perceived risk levels. In the context of the rapid proliferation of digital payment systems, a comprehensive understanding of the vulnerabilities within this ecosystem is essential for formulating effective fraud mitigation strategies. Design/methodology/approach This study utilizes analytical hierarchy process (AHP) and Fuzzy AHP to systematically prioritize digital fraud types and their sub-criteria. Robustness was validated via Kendall's W for expert consensus and leave-one-out sensitivity analysis, confirming the stability and reliability of the derived rankings. Findings The results indicate that malware attacks represent the highest perceived risk among DFF types, followed by phishing and Subscriber Identity Module (SIM) swapping. Furthermore, the study identifies accessibility, user awareness and trust as critical dimensions influencing susceptibility to DFF. These findings contribute to a more nuanced understanding of risk perception and vulnerability in digital financial environments. Research limitations/implications The study relies exclusively on expert opinion and does not incorporate empirical data from actual fraud incidents or large-scale user surveys. Future research may enhance the robustness of the findings by integrating empirical case studies and conducting cross-regional or demographic analyses. Originality/value This research offers a novel contribution to the field by applying AHP and Fuzzy AHP techniques to the assessment of DFF risk. The methodological framework and findings provide valuable insights for academic researchers, policymakers and practitioners seeking to enhance the security and resilience of digital financial systems.