GGRAsia – Feldman to serve on IGSA responsible gaming committee

Feldman to serve on IGSA responsible gaming committee

Jun 21, 2023 Newsdesk Industry Talk, Latest News

The International Gaming Standards Association (IGSA), a specialist technical advisor regarding electronic gaming machine technology and digital infrastructure for the casino and betting industries, has announced the creation of a Responsible Gaming Committee.

“All board members affirmed their intention to participate in and support the committee,” stated the body in a Tuesday press release.

Alan Feldman (pictured), described as one of the world’s leading experts on responsible gaming, “has agreed to serve” on the committee, according to the announcement.

Mr Feldman, who spent nearly 30 years with casino operator MGM Resorts International, is a Distinguished Fellow at the University of Nevada, Las Vegas’ International Gaming Institute. He is also Chair Emeritus of the U.S.-based International Center for Responsible Gaming.

IGSA said its newest committee “intends to offer support for regulators and operators with a multi-tier framework entitled the Responsible Gaming Maturity Model (RGMM)”.

“This approach will offer regulators and operators a path from discovery to a highly-quantifiable and predictable responsible gaming model,” stated the association.

“The RGMM will ensure regulators and operators can grow from implementing basic policy to managing a precise dashboard of key performance indicators generated from quantitative data,” it added. “The final and ultimate level will be to embrace the power of prediction and preventive detection.”

Earle Hall, IGSA’s chairman, was cited in the release as saying the “time has come to create a global standard, process and path for predictive responsible gaming.”

“Regulators have done an incredible job of creating their individual approaches. It is now time to pull the best practices together into a journey from discovery to quantitative management,” he stated.

Mr Hall also said it was “time to shift the paradigm to a data-driven predictability model to remove the tremendous burden on regulators and operators.”