Artificial Intelligence Enhanced Credit Scoring for MSMEs: A Policy Framework for Financial Sustainability in Emerging Economies

Authors

  • Shahinaz Hanem Abdellatif Corresponding and Lead Author: Assoc. Professor Shahinaz Hanem Abdellatif – Associate Professor – University Canada West and GUS Fellow.
  • Charity Yang University Canada West, Vancouver, Canada.
  • Abiba Nigussi University Canada West, Vancouver, Canada.

Keywords:

Economic and Financial Sustainability, AI-enhanced Credit Scoring, Microfinance, SMEs, SDGs, Financial, Inclusion, AI in Emerging Economies

Abstract

In emerging economies, the rapid expansion of social media, mobile penetration, and AI applications pose both opportunities and challenges for policymakers in the financial sector. Despite the proliferation of AI and alternative data in financial technology, few policy frameworks comprehensively integrate multidisciplinary theories to address credit access barriers in data-poor environments. Existing models often lack contextual sensitivity to informal economies and overlook the ethical, institutional, and sustainability dimensions necessary for equitable financial innovation. The study explores the potential of thick data and alternative information sources, such as mobile phone usage and social media activity, in AI-enhanced credit scoring, for micro, small, and medium-sized enterprises (MSMEs) by translating these qualitative cues into quantifiable indicators and applying systematic validation mechanisms, and proposes an integrated policy framework, drawing on the context of the MENA region. Credit scoring models, mine data retrieved from the social network accounts and microblogs to be assessed then analyze this data to measure behavioral indicators to forecast individuals’ financial behavior such as transaction patterns and digital payment activity then calculate their credit scores. This builds upon theoretical frameworks, such as the development finance theory, to explore how financial resources can be better mobilized and allocated. The study aims to utilize AI-enhanced credit scoring to help promote financial sustainability by improving credit access for the underserved population, overcoming data scarcity, lessening lending risks, and advancing financial inclusion in emerging markets through sustainable finance frameworks.  The study provides valuable insights to financial institutions, regulators, and multilateral development finance organizations to promote the Sustainable Development Goals (SDGs) and support economic development and resilience.

 

Keywords: Economic and Financial Sustainability, AI-enhanced Credit Scoring, Microfinance, SMEs, SDGs, Financial, Inclusion, AI in Emerging Economies

Downloads

Published

2026-06-01

How to Cite

Hanem Abdellatif, S. ., Yang, C. ., & Nigussi, A. . (2026). Artificial Intelligence Enhanced Credit Scoring for MSMEs: A Policy Framework for Financial Sustainability in Emerging Economies . European Journal of Sustainable Development, 15(2), 585. Retrieved from https://ecsdev.org/ojs/index.php/ejsd/article/view/2010

Issue

Section

Articles