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Navigating the next frontier: Practical AI in treasury operations

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In the rapidly evolving field of treasury management, the integration of Artificial Intelligence (AI) is proving to be transformative and increasingly indispensable.

According to a research article from the National Bureau of Economic Research, more than 50% of companies with over 5,000 employees and 60% of those with over 10,000 employees are now utilising AI. At the 2024 EuroFinance Global Treasury Americas West Coast conference, treasurer at the tech giant Microsoft offered profound insights on how AI is revolutionising treasury operations, boosting operational efficiencies, and enhancing decision-making processes.

Unpacking AI integration at Microsoft treasury

Kathy Brustad, Director of global treasury and financial services at Microsoft, spearheads the organisation’s machine learning and AI initiatives within its treasury team. Brustad explained that AI spans a wide spectrum, from traditional machine learning to more sophisticated generative AI technologies. This development has revolutionised the way tasks are executed across various sectors, especially in treasury and financial operations.

At Microsoft, AI integration has streamlined several core financial operations, enhancing both efficiency and accuracy. Brustad told delegates at the conference about machine learning solutions that bolster credit risk management and cash forecasting. These tools predict potential late payments and their anticipated delays, which are critical for effective liquidity management. Additionally, generative AI has revolutionised how structured data is handled, enabling treasury professionals to query databases through natural language. These queries are automatically converted into SQL by AI systems, simplifying data retrieval and making the process quicker and more user-friendly.

In the collections department, the treasury team has implemented AI tools to improve the efficiency of collection agents. These tools summarise case histories and automatically draft emails based on predefined policies and specific case details. This integration not only accelerates response times but also ensures consistency and accuracy in communications. 

Furthermore, the integration of AI into Microsoft’s treasury operations has significantly enhanced productivity by reducing the time spent on routine tasks so staff can focus on more strategic activities. Brustad emphasised that AI tools are not just about replacing human effort but augmenting human capabilities with superior data processing and analytical insights.

Adapting treasury roles for an AI-driven future

Navigating the integration of AI into treasury operations requires significant cultural and skill-based adaptations. Brustad stressed the importance of fostering a workplace culture that supports continuous learning and adaptability, a critical component in environments where technological advancements rapidly transform operations. 

Furthermore, Brustad emphasised the critical need to integrate technical skills with deep treasury knowledge. She relayed that teaching treasury professionals how to use technology is generally more straightforward than training technologists on the intricacies of treasury functions. She stressed that a deep understanding of treasury operations is essential for effectively deploying AI solutions. The deployment of AI goes beyond mere technological implementation; it includes ensuring team members are equipped to interpret AI outputs responsibly and are able to discern when outputs may be skewed or require manual intervention.

The future of treasury involves not only embracing new technologies but also fostering a workforce that combines a strong grasp of traditional treasury functions with the capability to leverage new tools. This dual focus ensures that AI technologies are used effectively and responsibly within the treasury domain, maintaining a balance between innovation and the nuanced understanding of the field’s fundamentals.

Looking to the future, Brustad is optimistic about the role of AI in enhancing treasury operations. She predicts that AI would not only streamline existing processes but also introduce new capabilities for predictive analysis and strategic decision-making. This evolution is expected to enable treasury departments to anticipate financial outcomes more accurately and respond to market changes with greater agility, ultimately supporting more informed and strategic financial decisions.