The adoption of AI for enterprise treasury management enables businesses to abandon manual spreadsheets for automated data pipelines.

Corporate finance departments face pressure from market volatility, regulatory demands, and digital finance requirements. Ashish Kumar, head of Infosys Oracle Sales for North America, and CM Grover, CEO of IBS FinTech, recently discussed the realities of corporate treasuries.

IBS FinTech has operated for 19 years and currently ranks in the top five globally according to an IDC report. Grover notes that while AI-powered automation has reached many areas of corporate life, treasury departments often still rely on manual spreadsheets.

“IBS FinTech has identified the gap in the CFO’s office in corporations where they are managing their most critical information system, that is, treasury management on Excel,” Grover said.

Treasury teams manage cash, liquidity, and risk. Companies face foreign currency risk through imports and exports, alongside related commodity risks. Cash surplus companies also need to invest in operations to generate returns.

The key problem for many enterprises is a lack of real-time data connection. Teams often execute trades on platforms like Bloomberg, Reuters, or 360D, manually enter the data into spreadsheets, and then post accounting entries into an enterprise resource planning system.

Successfully implementing AI in enterprise treasury management

AI implementations in finance depend on resolving these manual bottlenecks. Enterprise leaders often view the technology as a fast solution, but the technology requires digitised and automated data as a foundation.

“It is not by talking you can do AI in treasury,” Grover said. “You have to create that underlying data set that has to be digitised and automated.”

Integrating treasury management systems with existing enterprise resource planning platforms allows companies to establish this data foundation. IBS FinTech built its backend on Oracle databases from its inception and now integrates with Oracle Cloud, NetSuite, and Fusion.

A connected ecosystem requires the treasury management system to communicate directly with the enterprise resource planning platform, trading platforms, and banks. This integration provides executives with accurate information to manage liquidity, mitigate risk, and monitor compliance violations across the system.

Grover expects global volatility to increase due to geopolitical and economic factors impacting commodities, equities, and foreign exchange. Executives must prioritise automation and real-time information systems to operate in this uncertain environment.

Kumar noted that modernising treasury management with AI and connecting it to enterprise resource planning systems builds financial resilience. Enterprise leaders should audit their existing data workflows. If a finance team relies on manual entry between a trading platform and an enterprise resource planning platform, AI initiatives will fail due to poor data quality.

Implementing direct integrations ensures data flows in real time without error, providing the necessary baseline for future technology deployment.

See also: DBS pilots system that lets AI agents make payments for customers

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The post How AI upgrades enterprise treasury management appeared first on AI News.

Origianl Creator: Ryan Daws
Original Link: https://www.artificialintelligence-news.com/news/how-ai-upgrades-enterprise-treasury-management/
Originally Posted: Thu, 19 Feb 2026 13:48:55 +0000