Streamline Annual Grant Audits with AI

Start time:
March 20, 2025 10:00 AM PT
Duration:
45 minutes
Location:
Online
Contact:
Ivana Hermida, Moss Adams, (858) 627-5510
Cost to attend:
Complimentary

Grant audits are a highly regulated process, particularly when it comes to complying with Sarbanes-Oxley (SOX) controls. Whether it’s an annual or monthly grant, stock teams must ensure all data is accurate and compliant before approval, including checking for issues like terminations, incorrect grant dates, or improper vesting schedules.

AI not only helps mitigate the risk of non-compliance, but also streamlines workflows, reduces time spent on repetitive tasks, and improves overall accuracy.

Join us for our webcast, Streamline Annual Grant Audits with AI, in which we’ll discuss how to:

  • Address errors and common data pitfalls
  • Identify outliers to avoid compliance risks
  • Take steps to prepare for the approval process
  • Leverage AI to enhance efficiency
Register

Speakers

Tim Oakes, Partner, Moss Adams

Since 1996, Tim has developed technology systems and applications to help companies manage employee human relations, compensation, and equity compensation processes. He’s a leader of the firm’s Business Solutions Group, which delivers leading-edge technology solutions for clients across a variety of industries.

Tim has experience managing and conducting all aspects of system development projects, including business justification and requirements, business process design, development and testing, production rollout and implementation, system stabilization, and ongoing enhancements. His strong application development background is complemented by his deep business consulting experience.

Austin Ulfers, Senior, Moss Adams

Austin is a senior consultant with the Business Solutions Group at Moss Adams, supporting a variety of clients. His experience includes software and web application design and analysis, data engineering and analysis, and automated reporting. Prior to Moss Adams, Austin completed internships in data engineering, big data, and data science at local firms and was a machine learning engineer.

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