Webinar: AI Financial Close

How to Increase Match Rates, Reduce Exceptions, and Close Faster

Practical AI tools finance teams are using today

Finance teams are constantly under pressure to close faster, reduce manual work, and adopt AI — without adding more people, tools or technical overhead.

In this session, Danielle Roberts and Luke Havens from Trintech will demonstrate how AI is being embedded directly into the financial close process to increase transaction match rates, reduce exception handling, and simplify rule management — all within an existing close workflow.

You’ll see how AI-assisted rule creation is helping teams achieve over a 90% auto-match rate by automatically identifying patterns in transaction data. You will also see how AI-powered variance analysis reduces manual investigation, surfaces material risk early, and delivers explainable insight you can trust in the close.

Whether you’re evaluating close automation tools or looking to maximize the value of your current system, this session will show practical, production-ready AI use cases that drive measurable impact — not experimental side projects.

This session is ideal for CFOs, CAOs, controllers, FP&A, and accounting teams. Attendees will learn:

• How AI-assisted matching improves accuracy
• Why most teams leave value on the table in their rule configuration
• What AI in record-to-report looks like today — and what’s coming next
• How AI-powered flux analysis surfaces material variances instantly, enabling faster insights and smarter decision-making during close.