The integration of artificial intelligence into enterprise treasury management promises a significant shift, moving businesses away from reliance on manual spreadsheets towards sophisticated, automated data pipelines. This evolution is critical as corporate finance departments grapple with an increasingly complex landscape marked by market volatility, stringent regulatory demands, and the imperative for digital financial operations.
Ashish Kumar, who leads Oracle Sales for North America at Infosys, and CM Grover, CEO of IBS FinTech, recently shared insights into the current state and future trajectory of corporate treasuries. Grover highlighted that despite the widespread adoption of AI-powered automation across various business functions, treasury departments often remain tethered to traditional, manual spreadsheet methods for managing critical financial data.
“IBS FinTech has identified a significant gap within the CFO’s office,” Grover explained. “Many corporations are still managing their most vital information system—their treasury management—using Excel, which is inherently prone to errors and lacks real-time capabilities.”
Treasury teams are tasked with the complex oversight of cash, liquidity, and financial risk. Companies are exposed to foreign currency fluctuations through international trade and face associated commodity price risks. Furthermore, organizations with surplus cash need to strategically invest these funds to generate returns and support operational growth.
A fundamental challenge for many enterprises is the absence of real-time data connectivity. It is common for teams to execute trades on platforms like Bloomberg, Reuters, or 360D, then manually input this data into spreadsheets, and subsequently post accounting entries into their enterprise resource planning (ERP) systems. This multi-step, manual process is not only time-consuming but also a breeding ground for inaccuracies.
**Successfully Implementing AI in Enterprise Treasury Management**
The effective implementation of AI in finance hinges on addressing these manual bottlenecks. While many business leaders may perceive AI as a quick fix, its successful deployment relies heavily on a foundation of digitized and automated data.
“Achieving AI in treasury is not merely a matter of discussion; it requires the creation of an underlying data set that is both digitized and automated,” Grover emphasized.
The pathway to establishing this crucial data foundation involves integrating treasury management systems (TMS) with existing ERP platforms. IBS FinTech, for instance, built its core infrastructure on Oracle databases from its inception and now seamlessly integrates with Oracle Cloud, NetSuite, and Fusion.
A truly connected financial ecosystem necessitates that the TMS communicates directly with the ERP, trading platforms, and banking systems. Such deep integration empowers executives with accurate, real-time information, enabling them to effectively manage liquidity, mitigate risks, and monitor compliance across the entire organization.
Grover anticipates a continued rise in global market volatility, driven by geopolitical and economic factors that invariably impact commodities, equities, and foreign exchange markets. In this uncertain environment, executives must prioritize automation and real-time information systems to maintain operational agility and strategic foresight.
Kumar echoed this sentiment, noting that modernizing treasury management through AI and establishing robust connections with ERP systems is key to building financial resilience. He advises enterprise leaders to rigorously audit their existing data workflows. If a finance team relies on manual data entry between trading platforms and ERP systems, any AI initiative is likely to falter due to compromised data quality.
By implementing direct integrations, companies ensure that data flows in real time without errors, creating the essential baseline for the successful deployment of advanced technologies and future innovations in financial management.
Original article, Author: Samuel Thompson. If you wish to reprint this article, please indicate the source:https://aicnbc.com/18987.html
