article · International Journal of Advanced Economics
Artificial intelligence offers notable potential to address persistent challenges within developmental economics, especially regarding poverty alleviation and financial inclusion. At present, financial inclusion remains constrained by restricted access to banking services, socioeconomic disparities, and regulatory hurdles. Applying artificial intelligence through data analytics and predictive models can facilitate customised financial products, robust risk assessment, and targeted interventions. Nevertheless, deploying these tools introduces significant hurdles, including risks to data privacy, ethical concerns such as algorithmic bias, and accessibility constraints across underserved populations. Examining case studies and operational best practices highlights the necessity for flexible policy frameworks, continuous impact assessment, and coordinated cross-sector partnerships. In addition, integrating emerging systems like blockchain with updated regulatory measures may strengthen future development initiatives aimed at sustainable and inclusive growth.
Expanding financial access is vital for sustainable development and reducing poverty, yet traditional banking models frequently fail underserved communities. Understanding the opportunities and risks of artificial intelligence enables policymakers and financial institutions to deploy data-driven tools effectively while safeguarding user privacy and preventing algorithmic discrimination.
Potential applications include automated risk assessment engines and tailored financial services built for underserved populations. The primary users would be financial institutions, development organisations, and regulatory bodies. As the text outlines broad concepts, case studies, and policy requirements rather than validating a specific software product, the research sits at an early conceptual stage well upstream of commercial deployment.
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AI presents immense potential in addressing the complex challenges of developmental economics, particularly in the realms of financial inclusion and poverty alleviation. This abstract explores the opportunities and challenges associated with integrating AI solutions in these critical areas. Financial inclusion, essential for sustainable development, remains hampered by barriers such as limited access to banking services, socioeconomic disparities, and regulatory constraints. AI offers innovative approaches through data analytics and prediction models, enabling tailored financial services, risk assessment, and personalized interventions. However, the implementation of AI solutions poses significant challenges, including concerns regarding data privacy, ethical implications such as algorithmic bias, and accessibility issues in underserved regions. Through case studies and best practices, lessons can be gleaned to inform future initiatives, emphasizing the importance of adaptable policy frameworks, collaboration, and impact assessment. Looking ahead, emerging AI technologies like blockchain and enhanced regulatory measures hold promise, necessitating cross-sector partnerships and a concerted effort to harness AI's transformative potential for sustainable development and inclusive growth. Keywords: Developmental Economics, Financial Inclusion, Poverty Alleviation, AI Solutions, Challenges, Opportunities.
This page summarises published work. The authoritative version sits with the publisher.
DOI: 10.51594/ijae.v6i4.1073
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