Practical AI use cases in corporate treasury

Artificial Intelligence (AI) has moved beyond a buzzword to become a transformative technology in corporate finance. A 2025 PwC survey reveals that nearly half (49%) of technology leaders surveyed stated that AI was “fully integrated” into their firm’s core business strategy. To find out more on how Finance leaders are positioning AI in their corporate strategies, read our research conducted in partnership with Opinium.

Corporate treasury plays a big role in your organization’s financial stability. Treasury managers are moving away from manual, error-prone processes. Instead, corporate treasury focuses on substantive, practical applications that deliver measurable value in efficiency and risk management.

AI serves as a “co-pilot,” augmenting human expertise rather than replacing it. An AI functionality can learn from data, spot trends, and make accurate predictions. And Treasury staff can use AI to manage liquidity, optimize cash flow, control financial risks, and ensure the smooth flow of funds across all operations.

Core AI applications in treasury operations

Treasury managers can implement AI tools to improve cash flow forecasting, streamline payments, and detect and prevent fraudulent transactions.

Enhanced cash flow forecasting

Traditional forecasting relies on historical averages, which can be inaccurate in volatile markets. Sands Partners explains that overestimating demand based on historical data may result in excess inventory. Whereas, underestimating demand can lead to stockouts, missed sales opportunities, and customer dissatisfaction.

You need accurate cash flow forecasting to plan production, allocate resources effectively, and manage staffing efficiently. Without proper planning, you may damage relationships with suppliers and customers.

AI transforms forecasting by analyzing vast datasets from ERPs, bank statements, and even external economic indicators.

Use AI to predict customer payment delays based on historical payment patterns. Managers might use that information to insist on a cash deposit before each order is filled. If your business is seasonal, AI can combine historical sales data with demand forecasting to plan cash management.

How does your cash management forecast compare to actual results? AI can perform the variance analysis so you can make adjustments moving forward. AI-powered tools generate more accurate and granular forecasts, resulting in optimized borrowing, reduced idle cash, and enhanced working capital management.

Streamlined payments and working capital optimization

Even if you process hundreds (or thousands) of transactions, AI allows you to make informed decisions about every transaction and maximize working capital.

Businesses that retain useful data can train AI models and enhance their performance. For example, many companies are training AI to provide clients with more customized marketing experiences.

Dynamic discounting for early payments

Dynamic discounting is a solution that offers suppliers the option of receiving early payment in exchange for a discount on their invoices. The supplier can receive cash inflows sooner, and your firm can retain more working capital.

How much of a discount should you offer a supplier? AI can analyze a vendor’s payment history and financial standing to optimize dynamic discounting strategies, offering the right discount in exchange for early payment.

Automated cash application

According to a Stanford Business School study, AI helps businesses by automating repetitive tasks and identifying issues in real-time. Matching invoices to purchase orders and incoming payments can be a time-consuming task; however, AI can streamline the process.

AI, using Machine Learning (ML) and Natural Language Processing (NLP), can automatically match incoming payments to outstanding invoices, even when remittance information is unstructured or missing. This accelerates cash application and reduces days sales outstanding (DSO).

How and when you pay suppliers is another challenge. You need to consider the time and cost of processing the payment, while also maintaining a strong supplier relationship. An AI tool can analyze a payment’s size, required delivery speed, and supplier capabilities to recommend the most cost-effective payment type, such as ACH or an instant payment method.

Advanced fraud detection and risk management

As technology advances and businesses implement more technological solutions, the risk of fraud increases.

For example, a fictitious payee occurs when an individual sends an invoice with a company name and address that is very similar to an actual vendor. The individual hopes that the business will not notice the slight difference and pay the fraudulent invoice. AI can prevent fraud by speeding up the transaction review process.

If the accounting department carefully reviews incoming invoices and reconciles the bank account quickly, the risk of paying a fake invoice decreases. AI algorithms learn an organization’s standard payment patterns and can flag anomalies in real-time, such as deviations in amount, frequency, or geographic location.

It can also analyze communications to identify signs of Business Email Compromise (BEC) scams. In a BEC scam, a third party emails the business and attempts to have an employee pay an invoice, make a purchase, or wire funds to a fraudulent account.

These fraud detection strategies prevent significant financial loss, reducing the number of false positives that require manual review and protecting the company’s reputation.

Automated reconciliation and reporting

As mentioned above, reconciling the bank account quickly reduces the risk of fraud. The cash account may have more transactions than any other account, and high volumes also increase the risk of errors.

AI can automate a significant portion of the bank reconciliation process by intelligently matching bank statement entries with general ledger records and suggesting corrective actions for discrepancies. AI-powered chatbots can handle routine internal queries about payment status or treasury policies, freeing up the team to focus on more complex tasks.

The strategic shift: From operational to analytical

J.P. Morgan states that: “Treasury’s traditional back-office function is no more. In today’s workplace, treasury has transformed into a strategic operation that can drive a company’s bottom-line growth.” An effective treasury department adds value by optimizing investment and working capital strategies, as well as streamlining the vendor payment process.

Automating repetitive tasks allows treasury professionals to shift their focus from manual processing to higher-value analytical and strategic work. AI augments human capabilities with superior data processing and analytical insights, enabling treasury to become a more strategic partner to the business.

Leveraging AI to transform corporate treasury

AI is already delivering tangible benefits in treasury through smarter forecasting, robust fraud detection, and streamlined operations. Adopting these practical applications is key to building a more efficient, resilient, and strategically impactful treasury function for the future.

Ready to see how technology can transform your treasury operations? Discover how SAP Taulia can help you optimize working capital and strengthen your supply chain.