AI in Treasury: Artificial Intelligence or Augmented Intelligence?

Written by Patrick Kunz

Artificial Intelligence (AI) has become a buzzword across industries, and treasury management is no exception. However, there’s an important distinction to be made when discussing AI in the context of treasury: Is it truly Artificial Intelligence, or is it more about Augmented Intelligence?

AI Will Not Replace You – It Will Enhance You

One of the most common fears surrounding AI is that it will replace jobs, making human professionals obsolete. In treasury, this concern is understandable. With AI’s rapid advancement, it might seem like machines could eventually take over tasks like cash forecasting, liquidity management, and financial risk assessment.

The truth, however, is that AI in treasury is designed not to replace professionals but to augment their capabilities. It’s not about machines replacing humans but about empowering them with faster, more accurate decision-making tools.

The Role of AI in Improving Processes

Rather than automating treasury functions completely, AI enhances existing processes by increasing efficiency and accuracy. In areas like cash management and financial reporting, AI algorithms can quickly analyze vast amounts of data and offer real-time insights. This allows treasurers to make better, data-driven decisions and free up time to focus on strategy and value-added tasks.

For example, AI can significantly improve cash forecasting by identifying trends and patterns that might go unnoticed by human analysis. It can process large datasets in seconds, allowing treasury teams to make faster decisions and act proactively rather than reactively.

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Over 70% of businesses have experienced fraud attempts, and the financial impact continues to rise. As fraud tactics become more sophisticated, relying on outdated prevention strategies simply isn’t enough.

Join Tom A. (Senior Fraud Consultant UK at Trustpair) and our very own Royston Da Costa (Assistant Treasurer at Ferguson PLC) on February 20, 2025, at 11:00 AM for an essential webinar that will equip you with the latest insights and strategies to protect your organization from evolving AI-driven fraud threats. Moderated by Patrick Kunz, FRM QT

What you’ll learn:

  • How cyber fraud is evolving with real-world AI-driven scams
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This session is tailored for finance professionals, treasury leaders, and risk managers who want to stay ahead of fraud risks.

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Real-Life Examples of AI in Treasury

Here are a few examples from major corporations that showcase the power of AI in augmenting treasury processes:

  1. AI in Cash Forecasting at Coca-Cola
    Coca-Cola has integrated AI into its cash forecasting process to enhance accuracy and efficiency. By using machine learning algorithms, the company analyzes historical data and detects patterns in cash flows more effectively than traditional methods. This has led to more accurate short-term cash forecasts, optimizing liquidity management. (Source: Coca-Cola AI Cash Forecasting Case Study)
  2. AI in Risk Management at HSBC
    HSBC has deployed AI for its risk management functions, particularly for credit risk analysis. Using machine learning, HSBC analyzes large datasets to identify emerging risks in its portfolio. This allows treasury professionals to detect signs of potential financial stress much earlier than traditional risk models could. The bank’s use of AI has streamlined risk management, improving decision-making in a fast-moving financial environment. (Source: HSBC Risk Management with AI)
  3. AI for FX Risk Management at Shell
    Shell has employed AI tools to improve its foreign exchange (FX) risk management. By using machine learning models to predict currency fluctuations, Shell’s treasury team can make more informed hedging decisions, reducing the company’s exposure to currency volatility. The system helps them optimize the timing and size of FX trades, providing more efficient and accurate risk management strategies. (Source: Shell FX Risk Management with AI)
  4. AI-Powered Fraud Detection at American Express
    American Express has used AI to enhance fraud detection within its payments processing systems. With machine learning models that learn from patterns in transaction data, the company can quickly identify unusual transactions and flag them for further investigation. This not only helps prevent fraud but also improves the overall security and efficiency of its treasury operations by reducing the time spent on manual reviews and investigations. (Source: American Express Fraud Detection with AI)
  5. Automating Reconciliations at Siemens
    Siemens has adopted AI to automate the reconciliation of bank transactions within its treasury. Traditionally, this process was time-consuming and prone to errors. With AI-driven automation, Siemens now benefits from faster, more accurate reconciliations. The system can automatically match transactions and highlight discrepancies, saving significant time and reducing manual effort. (Source: Siemens AI-Powered Bank Reconciliation Case Study)

Speed and Accuracy

In treasury, where accuracy is paramount, AI can play a crucial role in reducing human error and streamlining operations. By automating repetitive tasks like transaction categorization, reconciliation, and monitoring of financial exposures, AI can not only reduce errors but also speed up these processes.

With faster and more accurate data analysis, treasury professionals can optimize cash management, hedge risks more effectively, and identify opportunities for cost-saving or investment more efficiently.

The Bottom Line: AI as a Collaborative Tool

Ultimately, AI in treasury is a tool to enhance human expertise. It’s about creating smarter, more efficient teams rather than replacing jobs. Treasury professionals will continue to play a critical role in making strategic decisions, interpreting data, and navigating the complexities of financial markets. AI, however, will allow them to work smarter, not harder.

The future of AI in treasury is less about replacing human jobs and more about enabling treasury teams to unlock their full potential. By leveraging AI to automate mundane tasks and improve decision-making, treasury professionals can deliver greater value to their organizations.

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