What Do Treasurers Need to Understand About AI?

A bulk of a Treasurer’s day-to-day involves both administrative and repetitive work such as:

Manual data gathering and consolidation:

The treasury team needs to gather datasets from disparate sources such as ERPs, TMS, bank portals, etc. They also need to collaborate with different internal teams such as Payroll, A/R, and A/P. Most of their time is spent on gathering and consolidating data into a “master sheet.” This process is not just time-intensive but also error-prone.

Automation provides the following benefits:

Increased efficiency: 

Automated data gathering captures real-time data from multiple banks, ERPs, and TMS across regions. Furthermore, through automation, the treasury team’s bandwidth is optimized to high-value tasks such as cash forecasting, risk management, and cash management.

Increased accuracy:

All necessary data is collected at a single point without human intervention, eliminating the risk of human errors. Accurate data enhances confidence in decision-making for borrowing, investing, M&A, etc.

Broader scope of data: 

Granular visibility is enhanced with drill-down capabilities into entity-level data. Additionally, teams can easily access data at any point in time without searching through multiple spreadsheets and portals.

A more holistic view of data:

Automatically storing all the data into a single repository allows monitoring categories like A/R, A/P, taxes, payroll across different geographies, horizons, company codes, etc., at the global and local level.

Treasury management software (or TMS) helps companies automatically manage their finances, such as capital, assets, and investments. The rate of TMS adoption has steadily increased over recent years. According to research conducted by Technavio in 2020, the CAGR of TMS is estimated to be 5%, and incremental growth is to be $975.62 million.

Despite the user growth of TMS, it has certain limitations. For example, TMS cannot collect data from a large number of different systems and improve forecast accuracy. Additionally, an on-premise TMS needs to be continuously upgraded by the company, lacks flexibility and scalability, and takes longer to implement.

However, AI-powered cloud-based applications integrate seamlessly with various data sources, including TMS, and offer time and cost savings. Furthermore, it ensures accessible and user-based data access from multiple regions and seamless collaboration. Data is backed up regularly, and the treasury management system is updated automatically. The most significant advantage offered is that it prevents data theft and that its maintenance is easier and cheaper than any in-house treasury software.

A world-leading food & beverage company faced the following challenges with its TMS:

• Manual invoice processing, leading to inaccurate A/R forecasts.
• The previous modeling only allowed short-term forecasting with 20-day horizons.
• Manual tracking of customer and invoice-level payment status, which was also time-consuming.

Through HighRadius’ cloud-based AI-powered solution, the company gathered data automatically from disparate data sources, created long-term cash forecasts, highlighted variances in A/R forecasts at customer and invoice-level, and achieved 96% forecast accuracy.

As treasury focuses on being more proactive and strategic in its functions, AI adoption continues to accelerate. The future trajectory of AI is expected to rise since it helps working capital management, funding, cash forecasting, fraud management, foreign exchange, risk management, etc.

AI helps treasurers achieve their goals by:

• Processing vast volumes of data, making accurate predictions, and finding patterns/ anomalies in transactions and customer behaviors.
• Capturing customer data to understand payment patterns and supports adding multiple variables for tracking due dates accurately.
• Using the time series algorithm to prioritize recent trends over historical ones. This helps understand changes in stock prices, bank deposits, and withdrawals and allows accurate future predictions.
• Incorporating external factors such as raw material price fluctuations to get a better sales forecast. This boosts forecast accuracy to enhance decision-making substantially.
• Detecting variance between forecasts and actuals through a closed feedback loop system allows AI models to learn from historical data and reduce variance with time.

Additional treasury technologies such as APIs are used for seamless integration to banks to enable real-time information gathering. APIs also allow fraud detection in payments. Moreover, automation performs repetitive and labor-intensive tasks with speed and accuracy.

Additional benefits from emerging technologies such as AI and automation in treasury:

• Reduced turnaround time: Automation frees up the bandwidth of treasury teams to drive faster and better decisions.
• Improved cash management: Tracking the cash conversion cycle faster enables better cash management.
• Reduced idle cash: CFOs can allocate idle cash to their short-term and long-term goals.
• Increased strategic investments: Decisions on business expansions and acquisitions are made accurately and adequately. 

A billion-dollar construction company improved its relations with investors through timely reports by generating cash forecasts with 95% accuracy, improved cash flow visibility, and variance analysis. Schedule a demo with HighRadius today to learn how AI-based cash flow forecasting can help your business improve its liquidity management.