Revenue Recognition Webinar

Simple one-time sales are becoming a thing of the past as the connected customer demands more choice and places more value on experiences than ownership. A majority of companies are now considering recurring revenue models to take advantage of this shift, but they are frequently stymied by inflexible legacy back-office systems that weren’t designed with digital-age transactions in mind.

At the same time changing financial regulations, most notably the advent of ASC606/IFRS15, have made the ability to handle complex revenue recognition a mandate. Even those that use fairly simple contracts will need to reexamine their revenue recognition processes.

Join enterprise revenue management experts from Aria (Monetization) and Softrax (Revenue Recognition).  In this webinar you’ll learn:

  • The challenges enterprises face with new business models and new revenue recognition regulations like ASC 606 and IFRS 15
  • The options available in adjusting your back-office capabilities to the new reality
  • Best practices to reduce the cost and risk of preparing your back-office for these coming changes.

Make sure your company is ready for the recurring revenue revolution 

Watch On Demand

Meet the Panel
Jeff Halden
Jeff Halden
Solutions Advisor

Jeff grew up in the San Francisco Bay Area and has served as a Partner at Ernst & Young, Vice President for Cap Gemini in their finance and accounting practices, and multiple early-stage businesses. He attended UC Davis, holds MBA and MHA post graduate degrees from Tulane University, and is a CPA. - See more at:



Brendan O’Brien
Co-Founder and CIO
Aria Systems

Brendan is Chief Innovation Officer and a Co-founder at Aria Systems. In 2002 he introduced the world to cloud billing, and innovated database-driven, enterprise-grade web applications - before the concept of “cloud” was even on the horizon. O’Brien is at the forefront of the recurring revenue revolution that is empowering enterprises -- and specifically enabling information systems and new business models to secure predictive revenue streams while improving business processes.