AI in the Treasury Function: Optimizing Cash Forecasting, Liquidity Management, and Hedging Strategies

• Author(s): Ayoola Olamilekan Sikiru ; Onyeka Kelvin Chima ; Mary Otunba ; Olatunde Gaffar ; Adedoyin Adeola Adenuga
• Paper ID: 1709992
• Page: 395-421
• Published Date: 31-10-2021
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 5 Issue 4 October-2021

Abstract

The integration of Artificial Intelligence (AI) into the treasury function represents a transformative shift in how organizations manage financial operations, especially in the domains of cash forecasting, liquidity management, and hedging strategies. This paper examines the impact of AI-driven solutions on enhancing the accuracy, efficiency, and strategic depth of treasury processes. Traditional treasury practices often rely on manual data collection, static models, and reactive decision-making, which limit responsiveness and expose firms to financial risk. However, with the rise of AI technologies—particularly machine learning, natural language processing, and predictive analytics—treasurers can now process large datasets in real time, identify patterns with higher precision, and forecast cash positions with greater confidence. In cash forecasting, AI enables dynamic models that adjust to market shifts and internal transactional behavior, reducing forecasting errors and enhancing short-term liquidity planning. In liquidity management, AI tools provide continuous visibility into global cash positions, automate surplus allocation, and ensure real-time optimization of working capital. These improvements support strategic decision-making by enabling treasury teams to respond quickly to market volatility and regulatory changes. Furthermore, in the area of hedging, AI algorithms can analyze market trends, correlate risk exposures, and recommend optimal hedging instruments, leading to more resilient and cost-effective risk mitigation strategies. The paper also discusses the challenges of AI adoption, including data quality, integration with legacy systems, and governance considerations. By leveraging case studies and empirical findings, this research underscores the critical role AI plays in reshaping the future of corporate treasury and driving financial agility. As organizations increasingly prioritize digital transformation, embedding AI in treasury workflows is no longer optional but essential for maintaining competitive advantage, improving stakeholder confidence, and achieving operational resilience.

Keywords

Artificial Intelligence, Treasury Function, Cash Forecasting, Liquidity Management, Hedging Strategies, Machine Learning, Financial Risk, Predictive Analytics, Corporate Finance, Digital Transformation.

Citations

IRE Journals:
Ayoola Olamilekan Sikiru , Onyeka Kelvin Chima , Mary Otunba , Olatunde Gaffar , Adedoyin Adeola Adenuga "AI in the Treasury Function: Optimizing Cash Forecasting, Liquidity Management, and Hedging Strategies" Iconic Research And Engineering Journals Volume 5 Issue 4 2021 Page 395-421

IEEE:
Ayoola Olamilekan Sikiru , Onyeka Kelvin Chima , Mary Otunba , Olatunde Gaffar , Adedoyin Adeola Adenuga "AI in the Treasury Function: Optimizing Cash Forecasting, Liquidity Management, and Hedging Strategies" Iconic Research And Engineering Journals, 5(4)