EXPLAINABILITY AS A SHARĪʿAH OBLIGATION: A MAQĀṢID GOVERNANCE MODEL FOR AI IN ISLAMIC FINANCE GROUNDED IN AL-SARAKHSĪ'S MUʿĀMALĀT
DOI:
https://doi.org/10.33102/43dvwn47Keywords:
Explainable AI, Maqāṣid al-Sharīʿah, Al-Sarakhsī, Muʿāmalāt, Sharīʿah GovernanceAbstract
This study examines the governance gap that has emerged from the rapid adoption of artificial intelligence in Islamic finance, particularly in credit scoring, ṣukūk pricing, and takāful underwriting, where black-box machine learning models generate decisions whose opacity raises substantive concerns under the Sharīʿah principles of ʿadl, riḍāʾ, amānah, and contractual transparency, and introduces a form of uncertainty analogous to gharar that weakens Sharīʿah auditability. The research problem addressed is the absence of an operational governance framework that integrates Explainable AI (XAI) techniques with Islamic jurisprudential epistemology, since existing XAI tools such as LIME and SHAP were not designed with reference to maqāṣid al-sharīʿah reasoning. The study adopts a qualitative doctrinal research design combined with conceptual framework development, drawing on Imām al-Sarakhsī's Al-Mabsūṭ as the primary classical source and supplementing the doctrinal analysis with two illustrative case studies on ṣukūk pricing and takāful underwriting. The main findings indicate that four jurisprudential principles reconstructed from al-Sarakhsī's muʿāmalāt theory, namely bayān, dafʿ al-ḍarar, yaqīn, and maṣlaḥah, can be operationalised into a three-layer interpretive structure comprising probabilistic bayān, justificatory taʿlīl, and maṣlaḥah-based evaluation, which together form the proposed Maqāṣid-Explainability Governance Model (MEGM). The author's analysis suggests that layered interpretability can satisfy certain auditability requirements articulated by AAOIFI and IFSB that conventional XAI approaches, when applied in isolation, may not fully meet, and that explainability in Islamic finance should be understood not merely as a technical preference but as a fiduciary obligation. The study concludes that al-Sarakhsī's muʿāmalāt theory provides a working jurisprudential foundation for ethical AI governance, and recommends that Islamic financial institutions, Sharīʿah committees, and regulators adopt the MEGM as a structured tool for auditing automated decision-making systems.
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