Author(s)

Rakibul Hasan Chowdhury 

Affiliation(s)

CCBA certified & Member, International Institute of Business Analysis (IIBA), USA.

MS Business Analytics, Trine University, USA.

MSc. Digital Business Management (2022), University of Portsmouth, UK.

Corresponding Author

Rakibul Hasan Chowdhury 

ABSTRACT

Public debt management is a cornerstone of economic stability, yet traditional methods often struggle to address the complexities of contemporary economic environments characterized by volatility, interconnected markets, and rapid technological advancements. This research explores the transformative role of advanced data analytics in modernizing public debt management practices. By integrating predictive analytics, risk assessment tools, and portfolio optimization techniques, advanced analytics offers innovative solutions to enhance forecasting accuracy, manage risks proactively, and optimize debt portfolios. Through an analysis of case studies from both developing and developed economies, the study highlights the global applicability and scalability of these tools. Key findings reveal that advanced analytics significantly improve fiscal resilience, reduces borrowing costs, and fosters long-term sustainability. However, challenges such as the need for robust data infrastructure, skilled personnel, and high initial investments remain barriers to widespread adoption. This paper underscores the critical need for continued research, innovation, and collaboration to fully leverage the potential of data analytics in public debt management, ensuring sustainable economic growth in an increasingly dynamic global landscape.

KEYWORDS

Public debt management; Advanced data analytics; Predictive analytics; Risk assessment; Portfolio optimization; Debt sustainability; Economic stability; Fiscal resilience; Machine learning; Big data analytics

CITE THIS PAPER

Rakibul Hasan Chowdhury. Public debt management with advanced data analytics. AI and Data Science Journal. 2024, 1(1): 6-19. DOI: https://doi.org/10.61784/adsj3001.

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