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FinTech firms are rapidly transforming the Middle East’s financial services, but sustainability tends to trail innovation. This study examines how artificial intelligence (AI) enhances sustainable financial decision-making among UAE, Saudi Arabian, and Bahraini FinTech firms using secondary data derived from financial statements, industry databases, and policy reports. Drawing on the triple bottom line (TBL) and technology-organization-environment (TOE) frameworks, the study employs quantitative and econometric analysis. Results show that AI adoption grows notably in sustainability integration—economic (β = 0.48), environmental (β = 0.55), and social (β = 0.67)—with machine learning and natural language processing improving environmental, social, and governance (ESG) scores (+15% financial inclusion) and emissions reduction (up to 1250 kg CO2e/year). The UAE is a front-runner in ESG performance (65.8), driven by its AI Strategy 2031, with Saudi Arabia (60.1) and Bahrain (62.3) expanding on regulatory frameworks. Policy implications highlight regulatory openness, AI capacity building, and cross-border collaboration to leverage the potential of AI for sustainable finance to the maximum. This research adds to the nascent discourse on AI-driven sustainability in emerging markets and offers actionable policy suggestions for reconciling FinTech innovation with ESG goals in the region.

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Leveraging Artificial Intelligence for Enhancing Sustainable Financial Decision-Making in Fintech Startups

  • 章节

  • 发表日期：

    2026年

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  • Shahnawaz Ali,
  • Ammar Al-Mansour

摘要

FinTech firms are rapidly transforming the Middle East’s financial services, but sustainability tends to trail innovation. This study examines how artificial intelligence (AI) enhances sustainable financial decision-making among UAE, Saudi Arabian, and Bahraini FinTech firms using secondary data derived from financial statements, industry databases, and policy reports. Drawing on the triple bottom line (TBL) and technology-organization-environment (TOE) frameworks, the study employs quantitative and econometric analysis. Results show that AI adoption grows notably in sustainability integration—economic (β = 0.48), environmental (β = 0.55), and social (β = 0.67)—with machine learning and natural language processing improving environmental, social, and governance (ESG) scores (+15% financial inclusion) and emissions reduction (up to 1250 kg CO2e/year). The UAE is a front-runner in ESG performance (65.8), driven by its AI Strategy 2031, with Saudi Arabia (60.1) and Bahrain (62.3) expanding on regulatory frameworks. Policy implications highlight regulatory openness, AI capacity building, and cross-border collaboration to leverage the potential of AI for sustainable finance to the maximum. This research adds to the nascent discourse on AI-driven sustainability in emerging markets and offers actionable policy suggestions for reconciling FinTech innovation with ESG goals in the region.