Designing a Conceptual Model for Fraud Detection in Banking Payments Using a Blockchain Approach

The main objective of this study is to design a conceptual model for detecting and preventing fraud in banking payment systems through blockchain technology. This research is applied–developmental in purpose, interpretivist in philosophy, inductive in approach, and qualitative in strategy. Data were collected through a literature review, semi-structured interviews with ten banking and blockchain experts, and a questionnaire. Thematic analysis and meta-synthesis were employed to identify categories and components. Inter-coder reliability (81% and 83%) confirmed the consistency of coding across researchers. The results revealed that fraud detection in blockchain-based payment systems is influenced by four major categories: technological, internal organizational, external organizational, and financial–technical factors. The final model indicates that blockchain enhances fraud detection efficiency by eliminating intermediaries, improving data transparency, increasing transaction security, and reducing operational costs. Moreover, technology transfer, legal frameworks, information infrastructure, management capabilities, and financial capacities play critical roles in the effective implementation of blockchain in the banking sector. The proposed model demonstrates that blockchain technology can serve as a reliable and transparent infrastructure for fraud detection and prevention in Iran’s banking industry. By ensuring data integrity and accountability, blockchain provides a transformative framework that strengthens trust and operational performance in digital financial systems.