Fair Credit Decision Assurance: An Ethical Governance Framework For AI-Based Credit Scoring in Bangladesh with Islamic Finance Duties
DOI:
https://doi.org/10.65150/EP-jefrr/V2E10/2026-02Keywords:
AI credit scoring, algorithmic fairness, explainability, financial inclusion, Islamic finance, maqasid al-Shariah, BangladeshAbstract
Purpose: Machine-learning credit scoring can extend formal credit to people with thin files, but alternative data can also turn social disadvantage into apparently neutral risk scores. This paper develops a governance framework for AI-based credit scoring in Bangladesh and adapts it to the duties of Islamic financial institutions.
Design/methodology/approach: The study is a structured integrative review combined with policy and doctrinal analysis. It synthesizes peer-reviewed research on algorithmic lending, fairness and explainability; international benchmarks (the EU AI Act, U.S. adverse action guidance, the NIST AI Risk Management Framework and the OECD AI Principles); Bangladeshi instruments on e-KYC, credit information, digital nano-loans, e-loans and data protection; and Islamic finance sources on maqasid al-Shariah, gharar and Shariah governance.
Findings: Bangladesh now permits fully digital small-value lending, yet its current instruments say little about model validation, bias testing, reason-giving or contestation. Predictive accuracy alone is an inadequate standard because a model can improve portfolio performance while concentrating false rejections on women, rural applicants or new-to-credit borrowers.
Originality/value: The paper proposes a Fair Credit Decision Assurance (FCDA) model with six gates: lawful data, feature relevance, fairness testing, explanation, human reconsideration and monitoring. A Shariah overlay adds product-level review and treats unexplained adverse decisions as a governance concern related to gharar.
Practical implications: The model gives banks, finance companies, mobile financial service providers and Bangladesh Bank a staged route to supervising algorithmic credit without halting innovation.
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Copyright (c) 2026 Sumaia Yasmin Keya , Niger Sultana, Md. Baharul Hasan, Md. Shahed Alamm, Md. Aminul Islam, Ummey Sumaiya (Author)
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