AL-Qadisiyah Journal For Administrative and Economic sciences

Secure Intelligence in Banking: An Integrated Framework for Artificial Intelligence with Data Privacy and Security Preservation

Document Type : Research Paper

Authors

hayder makki shakir 1
Hadir H Shubbar 2

1 Faculty of Computer Science and Information Technology, University of Al-Qadisiyah, Qadisiyah, Iraq

2 Faculty of Administration and Economics-Department of Banking and Finance-University of AL- Qadisiya , Republic of Iraq.

https://doi.org/DOI://doi.org/10.33916
Abstract
AI is being deployed to transform digital banking, allowing us to move beyond just predictive analytics and fraud detection. But when they implement AI on a scale, they expose sensitive financial information to privacy, security, and compliance breaches. This paper introduces a Secure Intelligence Architecture (SIA). 1 HE, SMPC, DP, and TEE-Based Conceptual Framework Our conceptual framework is a combination of Homomorphic Encryption (HE), Secure Multi-Party Computation (SMPC), Differential Privacy (DP), and Trusted Execution Environments that are used to guarantee end-to-end confidentiality and privacy compliance. Composed of four interdependent fractal layers (Data Governance, Privacy & Cryptography, AI Intelligence, and Compliance & Monitoring), the Academy Framework establishes trust as a continuous, flowing process throughout the entire data lifecycle. According to the theory, the SIA reduces exposure risk and enhances compliance through automated RegTech auditing. A model based on a ‘fake algorithm’ and its formal arithmetic establishes that we can have secure computation without compromising the usability. The research presents an example for building scalable, trustworthy AI in financial ecosystems .                                                                                                                       

Keywords

Artificial Intelligence
Secure Banking
Homomorphic Encryption
Differential Privacy
Trusted Execution Environments
Computational Trust
RegTech
Data Governance
and Privacy-Preserving Analytics
AL-Qadisiyah Journal For Administrative and Economic sciences
Volume 26, Special 2
Winter 2026
Pages 22-34

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