Financial Inclusion and Institutional Resilience in AI-Driven Islamic Finance: A Contract-Based Risk Governance Framework
The growing use of artificial intelligence (AI) in Islamic finance has complicated the allocation of responsibility when financing decisions depend on automated assessments. This study develops a conceptual governance framework by reconstructing the complementary functions of Kafalah, Wakalah, and rahn. Using a qualitative doctrinal-comparative approach, it examines the contracts individually and through three pairwise relationships, then maps their functions to AI-related risks and institutional controls. The analysis identifies Kafalah–rahn as a mechanism for coordinating guarantees and collateral, Kafalah–Wakalah for linking guarantee obligations with accountable delegation, and Wakalah–rahn for governing delegated collateral activities. These relationships inform a five-layer architecture covering contractual authority, contingent risk allocation, collateral risk mitigation, technological governance, and maqāṣid al-sharīʿah-based evaluation. An illustrative financing scenario shows how model validation, human oversight, decision traceability, and proportionate safeguards may operate together. The framework distinguishes responsible financial access from institutional resilience without assuming that either outcome follows automatically. Its contribution is conceptual, and practical effectiveness requires subsequent expert and institutional assessment.
Authors
- Dudang Gojali (ORCID: https://orcid.org/0000-0003-0494-3156)
- Sahidan Abdulmana (ORCID: https://orcid.org/0000-0003-2618-7347)
- Egi Al Fansyah
- Muharman Lubis
- Iwan Setiawan
Institutions
- Fatoni University (TH)
- Sunan Gunung Djati State Islamic University Bandung (ID)
- Telkom University (ID)
Publication Details
- Journal
- Electronic Integrated Computer Algorithm Journal
- Published
- 2026-10-31
- DOI
- https://doi.org/10.62123/enigma.v4i1.243
- Primary Topic
- Islamic Finance and Banking Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00