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Digital transformation of organizations: Intelligence financial management system

Author

Listed:
  • Pinyaphat Tasatanattakool
  • Katekeaw Pradit
  • Prachyanun Nilsook
  • Panita Wannapiroon

Abstract

This research aims to 1) synthesize the conceptual framework and 2) develop the architecture and evaluate its applicability. This paper outlines the architectural framework for the digital transformation of enterprises, specifically focusing on an intelligent financial management system. The research is synthesized, and a systematic review employs the PRISMA flow diagram. This system will utilize a financial management database that includes salary management, accounting management, fixed asset management, risk control, report management, financial analysis, and system administration. This framework will integrate advanced artificial intelligence techniques to improve operational efficiency, accuracy, and security in financial operations. It can improve risk assessment, elevate client contacts, and optimize economic decision-making processes, therefore aiding in the formation of organizational support, management supervision, operational plans, and administrative decisions, among other elements. The results showed that this architecture has an excellent level of suitability (mean = 4.63, standard deviation = 0.44). It demonstrates that entities employing advanced financial management systems to facilitate data storage mitigate inaccuracies and assist in the rapid, precise, and efficient analysis of data, which is an outcome of implementing digital transformation. This shift enhances decision-making processes and fosters a culture of accountability and transparency within organizations, ultimately driving sustainable growth and innovation.

Suggested Citation

  • Pinyaphat Tasatanattakool & Katekeaw Pradit & Prachyanun Nilsook & Panita Wannapiroon, 2025. "Digital transformation of organizations: Intelligence financial management system," International Journal of Innovative Research and Scientific Studies, Innovative Research Publishing, vol. 8(1), pages 773-783.
    • Handle: RePEc:aac:ijirss:v:8:y:2025:i:1:p:773-783:id:4422
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