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Kinectify and Kindbridge Behavioural Health sign deal

Updated:2024-03-20 09:23    Views:148

Kindbridge Behavioural Health (KBH) and Kinectify, a provider of anti-money laundering (AML) risk management technologies for casino operators in the US and Canada, have joined forces.

The partnership intends to improve problem gambling technology for gaming operators, and advance a risk-free and environmentally friendly gambling atmosphere.

Further, Kinectify is releasing a comprehensive responsible gaming (RG) platform with its current AML platform. This platform provides specialised workspaces for AML and RG teams enabling them to handle activities like player care, case management, reporting and monitoring.

This collaboration will make it possible for anyone harmed by gambling to receive care more quickly and effectively. 

Daniel Umfleet,Online Casino Games for Real Money CEO of Kindbridge, said: “Mapping out as many ways as possible for people with a gambling problem to gain access to a network of training providers that understand what they are going through is key to creating a safer gambling environment and a sustainable industry.

“By teaming up with Kinectify to gain behavioural insights from their AML technologies and by helping them round out their RG Case Management software with the KBH treatment network implemented and easy to deploy, we can now start to connect the link from AML to gambling harms to direct care access faster than ever before.”

Joseph Martin, Kinectify CEO, said: “We are thrilled to partner with Kindbridge, the first organization solely focused on building treatment infrastructure through telehealth.

"We look forward to testing a variety of treatment modalities on those that are more dangerously impacted by their gambling behaviour and assisting states with solutions for treatment disparity gaps that exist due to a lack of trained resources in this field.”

Joseph Martin will also become a member of the Kindbridge Research Institute (KRI) Board. The KRI specialises in using data analysis to create efficient treatment models and strategies.



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