Oracle Financial Services is integrating its new agentic AI platform for corporate banking directly into legacy core systems while automating document-heavy workflows.  

The tech company designed the platform, which launched April 14, as an “enterprise-grade layer that embeds AI directly into core banking processes, allowing institutions to integrate with existing systems while modernizing incrementally,” Sovan Shatpathy, senior vice president of product management and development at Oracle Financial Services, told FinAi News. 

“Because agents are pre-built and aligned to domain workflows, banks can move quickly, deploying targeted capabilities in phases rather than undertaking wholesale core replacement,” he said.  

As of January, 99% of financial services firms eventually plan to deploy AI agents into production, but only 11% have done so due to implementation challenges, according to AI consulting firm NeuronsLab. 

Automating corporate banking 

Oracle’s new platform provides pre-built AI agents for treasury, trade finance, credit and lending, automating back-office work and client-facing processes, according to its April 14 release.  

The agents are designed to execute tasks including:

• Loan and financial data extraction;
• Loan data validation;
• Market analysis; 
• Risk assessment summaries; and
• Credit memo drafting. 

Oracle is targeting significant time savings by streamlining manual, fragmented workflows, Shatpathy said. For example, a credit manager can use an AI agent to extract key financial ratios from hundreds of pages of documents in less than a minute, with validation and approval then taking roughly an hour, he said. 

“In a non-AI workflow, the same task typically takes a full working day due to variability in formats, nomenclature and complexity,” he said. “At scale, for a mid-sized bank operating across 20 regions with five credit managers per region, this would translate to approximately 700 hours saved per day.” 

Industry shift 

Oracle expects commercial banking to shift toward “highly proactive, real-time and personalized engagement” over the next few years as AI agents “orchestrate interactions across channels, anticipate client needs and enable bankers to focus on higher-value advisory roles,” Shatpathy said.  

Oracle is also developing agentic tools to automate processes such as collateral management so that banks can extract and standardize key data, regardless of format, and “populate it directly into downstream systems within seconds,” he said. 

This can result in faster turnaround times, greater operational efficiency and more valuable client engagement opportunities, he said. 

Banks that have recently adopted Oracle’s AI tools include M&T Bank and Bank of Valletta, according to the company. 

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