The Importance of Data Infrastructure for Artificial Intelligence in the Financial Sector
Modern data infrastructure strategies necessary for the effective use of artificial intelligence and automation processes in finance departments were discussed.
As finance functions focus on transformation processes to benefit from artificial intelligence and automation, experts are discussing the obstacles created by legacy systems and manual processes, along with solutions.
Legacy Infrastructure Issues in Financial Processes
Although finance departments are expected to provide forward-looking guidance, many organizations continue to use legacy systems designed for historical reporting.
Research shows that manual processes and legacy systems are among the biggest obstacles slowing down month-end closes.
Strategies for Real-Time Visibility
Capturing financial events at the transaction level allows teams to move while maintaining flexibility in results instead of relying on monthly reports.
Establishing a common financial language is vital to increasing the reliability of automation and reconciliation processes.
Managing Artificial Intelligence Outputs
Holding finance accountable for artificial intelligence accuracy and linking changes to business outcomes enables scalable automation.
Experts emphasize that foundational fragmentation must be addressed before scaling automation.