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recruitment mechanisms and competitive compensation policies are necessary to prevent
“brain drain” from the public sector to private enterprises.
Fourth, build a data-driven decision-making culture. This requires changing
management thinking, shifting from subjective experience to verified quantitative analysis.
3.5.4. Implementation roadmap and sustainability
Viet Nam may adopt a phased approach: (i) piloting risk-monitoring models in
selected ministries, sectors, or localities with large-scale public investment; (ii) assessing
impacts in terms of effectiveness, costs, and the level of acceptance among officials; and
(iii) refining the institutional framework before scaling up nationwide.
The three pillars, Smart Treasury Platform, AI integration, and human resource
development, should be implemented in a synchronized manner within the financial
sector’s digital transformation strategy through 2030. The long-term objective is not only
to detect irregularities but also to optimize resource allocation, enhance the efficiency of
public expenditure, and strengthen public trust.
Building an intelligent PIE monitoring model represents a comprehensive reform
process that combines data infrastructure, analytical technologies, and human capacity. If
implemented systematically, Viet Nam can gradually move toward a transparent,
proactive, and sustainable public financial governance model in the digital era.
4. Conclusion
The application of BDA and AI in monitoring PIE marks a shift from an ex-post
control model to a proactive risk-based governance approach. With public investment
accounting for approximately 28-30% of total state budget expenditure, strengthening
monitoring capacity is crucial to improving the efficiency of national resource allocation.
However, technology can only be effective when built upon a solid data governance
foundation, a transparent legal framework, and clear accountability mechanisms. The
Smart PFM model is not intended to replace human decision-makers with algorithms, but
rather to enhance data-driven decision-making capacity. If implemented through an
appropriate roadmap, Viet Nam can gradually develop an intelligent, transparent, and
digitally adaptive public financial ecosystem aligned with the demands of the digital era.
References
[1]. Agrawal, A., Gans, J., & Goldfarb, A. (2018). Prediction Machines: The Simple
Economics of Artificial Intelligence. Harvard Business Review Press.
[2]. Government of Viet Nam. (2020). Decree No. 13/2020/NĐ-CP on the National E-
Procurement System and online bidding implementation.
[3]. Financial Informatics and Statistics Center (FIST), MOF of Viet Nam. (2023).
Finance Sector Digital Transformation Report 2023.
[4]. IMF. (2023). Fiscal Monitor: Navigating the High Debt Challenges.
[5]. Janssen, M., & Estevez, E. (2019). Lean government and platform-based
governance - Doing more with less. Government Information Quarterly, 36.
[6]. Janssen, M., & van der Voort, H. (2016). Adaptive governance: Towards a stable,
accountable and responsive government. Government Information Quarterly, 33(1).
[7]. Klievink, B., et al. (2020). Towards data-driven economies: Strategic and
organizational challenges in the public sector. Government Information Quarterly, 37(1).
[8]. Kitchin, R. (2014). The Data Revolution: Big Data, Open Data, Data
Infrastructures and Their Consequences. SAGE Publications.
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