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A Conceptual Framework for Financial Inclusion in Emerging Economies: Leveraging AI to Expand Access to Credit
Subject area: Science,Engineering and Technology · Area of research: Artificial Intelligence
Abstract
Financial inclusion remains a critical development challenge in emerging economies, where vast segments of the population and small businesses lack access to formal credit systems. Traditional financial institutions often rely on rigid credit assessment models that exclude individuals without conventional credit histories or collateral. In this context, Artificial Intelligence (AI) presents a transformative opportunity to expand credit access through the use of non-traditional data sources and intelligent decision-making algorithms. This proposes a conceptual framework for leveraging AI to enhance financial inclusion by enabling more inclusive and accurate credit underwriting in emerging markets. The framework integrates AI-driven models such as machine learning and natural language processing with alternative data, including mobile phone usage, social media activity, utility payments, and transaction histories from digital wallets. These models can generate dynamic credit scores for underserved populations, enabling financial institutions and fintech companies to assess creditworthiness more effectively. The framework also includes feedback loops for continuous model improvement and real-time risk monitoring. The potential of this AI-enabled approach to address structural barriers in traditional financial systems, such as high operational costs, limited infrastructure, and biased human decision-making. Case studies from Africa, South Asia, and Latin America demonstrate successful early applications, particularly in microfinance and mobile lending platforms. This concludes with recommendations for policymakers, financial institutions, and technology developers to foster responsible AI deployment. Emphasis is placed on regulatory alignment, ethical considerations, data privacy, and digital literacy. Overall, this conceptual framework underscores the pivotal role of AI in bridging the credit gap and promoting inclusive economic growth in emerging economies. By harnessing the power of data and intelligent analytics, AI can help reshape the financial landscape to better serve the needs of traditionally excluded communities.
Keywords
Conceptual framework, Financial inclusion, Economies, Leveraging AI, Expand access credit
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How to cite this paper
@article{1708933,
author = {Ademola Adewuyi, Tolulope Joyce Oladuji, Ayodeji Ajuwon, Chigozie Regina Nwangele},
title = {A Conceptual Framework for Financial Inclusion in Emerging Economies: Leveraging AI to Expand Access to Credit},
journal = {Iconic Research And Engineering Journals},
year = {2020},
volume = {4},
number = {1},
pages = {222-236},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1708933.pdf},
abstract = {Financial inclusion remains a critical development challenge in emerging economies, where vast segments of the population and small businesses lack access to formal credit systems. Traditional financial institutions often rely on rigid credit assessment models that exclude individuals without conventional credit histories or collateral. In this context, Artificial Intelligence (AI) presents a transformative opportunity to expand credit access through the use of non-traditional data sources and intelligent decision-making algorithms. This proposes a conceptual framework for leveraging AI to enhance financial inclusion by enabling more inclusive and accurate credit underwriting in emerging markets. The framework integrates AI-driven models such as machine learning and natural language processing with alternative data, including mobile phone usage, social media activity, utility payments, and transaction histories from digital wallets. These models can generate dynamic credit scores for underserved populations, enabling financial institutions and fintech companies to assess creditworthiness more effectively. The framework also includes feedback loops for continuous model improvement and real-time risk monitoring. The potential of this AI-enabled approach to address structural barriers in traditional financial systems, such as high operational costs, limited infrastructure, and biased human decision-making. Case studies from Africa, South Asia, and Latin America demonstrate successful early applications, particularly in microfinance and mobile lending platforms. This concludes with recommendations for policymakers, financial institutions, and technology developers to foster responsible AI deployment. Emphasis is placed on regulatory alignment, ethical considerations, data privacy, and digital literacy. Overall, this conceptual framework underscores the pivotal role of AI in bridging the credit gap and promoting inclusive economic growth in emerging economies. By harnessing the power of data and intelligent analytics, AI can help reshape the financial landscape to better serve the needs of traditionally excluded communities.},
keywords = {Conceptual framework, Financial inclusion, Economies, Leveraging AI, Expand access credit},
month = {July},
}