EventsThe 2nd International Online Conference on Risk and Financial Management
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This submission belongs to the session S6. Emerging Tech Convergence: Future Financial Infrastructure of the event The 2nd International Online Conference on Risk and Financial Management
Published date
28 Oct, 2026
Academic Editor
author-avatarRamona Rupeika-Apoga
Citation
Saman Ikram Abbasi, Kamran Razzaq, Muhamamd Naeem, Smart and Secure: Leveraging AI-Blockchain Convergence to Transform Banking Infrastructure, in Proceedings of The 2nd International Online Conference on Risk and Financial Management, 2 November–4 November 2026, MDPI: Basel, Switzerland
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Smart and Secure: Leveraging AI-Blockchain Convergence to Transform Banking Infrastructure

Saman Ikram Abbasi 1
Muhamamd Naeem 3
1. Shaheed Zulfikar Ali Bhutto Institute of Science and Technology University, Department of Computer Sciences,Islamabad, 44000, Pakistan
2. Department of Marketing Operations and Systems, Northumbria University, Newcastle, UK
3. University of Kotli Azad jammu & Kashmir, Department of Business Administration, Kotli AJ&K, 11100, Pakistan
Abstract

Introduction: This study examines how artificial intelligence (AI) and blockchain technology converge to shape the future architecture of banking infrastructure. As banks seek to enhance efficiency, security, and customer trust, integrating AI-driven analytics with blockchain ledger systems presents a transformative opportunity for core banking functions. This study addresses research gaps by exploring how the combined deployment of AI and blockchain can redefine trust, transparency, and automation.

Methodology: We started with a systematic review of literature, industry reports, and case studies regarding AI-powered blockchain in banking. The comparative analysis focused on assessing the capabilities of AI and blockchain technologies, with an emphasis on transaction security, fraud-detection accuracy, and customer trust. Examples of smart contract-based lending platforms, AI-based anti-money laundering (AML) solutions, and blockchain-based know-your-customer (KYC) systems were studied to assess implementation outcomes. A framework was developed to chart the interdependencies between AI-driven decision-making and blockchain-based transaction verification.

Findings: The results show that the combination of AI and blockchain has a profound impact on fraud detection, with ML algorithms accurately detecting anomalies. Smart contracts with AI functionality demonstrated efficiency in loan approval and credit risk evaluation. AI-enabled identity verification in blockchain KYC systems streamlined the onboarding process and improved regulatory compliance. The findings show that the combination of AI and blockchain is more effective and secure than using technology alone in terms of security and customer confidence.

Conclusion: The interaction between AI and blockchain technology has the power to revolutionise bank infrastructure, making it secure, efficient, and transparent. This integrated approach enhances fraud prevention, streamlines regulatory compliance, and improves customer trust through automated and intelligent transaction processing. This research goes beyond the boundaries of technology analysis by providing novel perspectives on AI-blockchain integrated banking ecosystems, laying the groundwork for further research in regulatory design and digital banking transformation.

Keywords
Artificial Intelligence
Blockchain
Fraud Detection
Smart Contracts
Financial Technology
Regulatory Compliance
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