ARTIFICIAL INTELLIGENCE, FINANCIAL INCLUSION, AND DEBT FINANCING IN SAUDI ARABIA: SUPPORTING SAUDI VISION 2030
DOI:
https://doi.org/10.18623/rvd.v23.5861Keywords:
Artificial Intelligence, Financial Inclusion, Debt Financing, Digital Lending, Credit Risk Assessment, Machine Learning, Alternative Data Analytics, Sme Financing, Fintech Innovation, Saudi Vision 2030Abstract
Financial inclusion is seen as one of the pillars of economic diversification and sustainable development in Saudi Arabia, with particular reference to the Saudi Vision 2030 initiative. Expanding access to credit and debt financing for individuals, small and medium enterprises, and the less financially included remains important for entrepreneurship, inequality reduction, and private sector growth. Nevertheless, the application of credit assessment tools is seen to be excluding high-value credit applicants owing to the lack of credit history. This article seeks to investigate the role played by artificial intelligence in enhancing financial inclusion and access to debt financing in Saudi Arabia. It is believed that the application of machine learning algorithms, alternative data analytics, and credit scoring tools can enhance the expansion of access to credit and debt financing. Financial inclusion is seen to be improved through the application of predictive models, digital lending tools, and data-driven decision-making tools. Based on the investigation, it is evident that the application of credit evaluation tools is important in enhancing financial inclusion and access to credit and debt financing. Furthermore, the investigation highlights the importance of considering the governance, regulatory, and ethical issues related to the application of lending tools. As the government seeks to achieve its economic objectives through the application of technology innovation, this research highlights the importance of enhancing access to credit and debt financing through the application of artificial intelligence tools in the Saudi Arabian economy.
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