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Role of Artificial Intelligence in Strategic Debt Sustainability Planning

Role of Artificial Intelligence in Strategic Debt Sustainability Planning
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Author(s): Shveta Gupta (Chitkara University, India), Gurwinder Singh Badal (Chitkara University, India)and Dhiresh Kulshrestha (Chitkara University, India)
Copyright: 2024
Pages: 9
Source title: Ethical AI and Data Management Strategies in Marketing
Source Author(s)/Editor(s): Shefali Saluja (Chitkara Business School, Chitkara University, India), Varun Nayyar (Center for Distance and Online Education, Chitkara University, India), Kuldeep Rojhe (Center for Distance and Online Education, Chitkara University, India)and Sandhir Sharma (Chitkara Business School, Chitkara University, India)
DOI: 10.4018/979-8-3693-6660-8.ch012

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Abstract

Artificial intelligence is being utilised to discover fiscal hazards, shady tendencies and patterns, and dangerous entities in revenue creation. Previously, public debt was regarded as a vital tool for temporarily increasing revenue or purchasing power in exchange for the government's commitment to repay the main sum borrowed and, in most cases, interest on that principal. However, it has now become a permanent feature. The purpose of the government borrowing is to fill up the gap between the government revenue and proposed spending for the fiscal year. The objective of the study is to examine the significance of artificial intelligence in estimating the public debt on fiscal deficit of the government's, and to examine the trends in the revenue and fiscal deficits, with the view to identify the factors responsible for the same. The secondary data has been collected from Union Government's budget documents of various years. Further economic surveys and various other publications of Government of India, RBI, and other regulatory bodies has also been used to collect data and other relevant information. To analyse the collected data, statistical techniques such as solow model, trend regression analysis, and ratio analysis etc., has been used. The analysis results found that liabilities and debt in relation to GSDP have been increasing, and this has been particularly noticeable throughout the UDAY scheme's execution era and efficiency can be achieved with the use of AI in the field. However, the debt-to-GDP ratio is significantly below the 25% target set by the fourteenth finance commission.

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