Oracle Financial Services reposted this
Banks are modernizing finance to enhance efficiency and agility. While updating legacy systems is challenging and costly, can intelligent automation—combining RPA, AI, and generative AI—help banks scale and drive greater value in their transformation journey? During our Finance Transformation session at #OCW this week, Yogi Singh from Oracle hosted an engaging conversation with executives Morgan Klein-MacNeil from TD, Andy Coffey from M&T Bank and Vishnu Mangal from Scotiabank, where they shared their insightful transformation journeys. One mentioned that they focused on consolidating data and profitability insights, and their transformation included a major shift to a single general ledger system, emphasizing change management and consistent data practices. While another is on a SaaS transformation journey, as they are working to improve efficiency by consolidating data from four ledgers. The goal is to go live with profitability-focused applications by 2025, using a lift-and-shift approach. One said they have began their journey in 2010, focusing on standardizing global operations. They learned that building a solid foundation before layering new capabilities was essential to success. When it comes to discuss change management challenges, all speakers advocated for tackling transformation one use case at a time and stressed the importance of integrating core systems, like retail and capital markets, to drive impact. They also shared some best practices for data consolidation: - Focus on specific use cases rather than trying to overhaul everything at once. - Establish a single source of data and ensure integration with core systems to identify key financial impacts like cash flow and taxes. - Build data foundations first, then layer advanced capabilities like profitability analysis. They discussed their Gen AI and automation use cases and lessons learned: - Using Gen AI to support CFO office with insights, analytics, and reporting, driving product innovation and profitability. - Highlighting the need to separate AI from RPA, noting that many end users mistakenly interchange these technologies. - Emphasizing the need for permanent, rule-based solutions in automation to avoid short-term fixes and ensure lasting business impact. Banks are prioritizing building robust data foundations, leveraging Gen AI to enhance financial insights, and streamlining legacy systems to improve overall efficiency. As automation and AI continue to evolve, the focus remains on strategic application, effective change management, and continuous learning to drive sustainable finance transformation. #FinanceTransformation #Banking #ai #genai #IntelligentAutomation #financemodernization #roboticprocessautomation #RPA Sabrina Scott Jason Wynne Mark Atherton Gina D'Onofrio Brian Tom
