Facial recognition company ClientScan has launched a new AI-driven system that aims to protect self-excluded gamblers.
ClientScan has been developed by experts and advisors from the Visual Geometry Group at Oxford University.
If a gambler chooses to self-exclude from in-person gambling, their information – including their image – is stored on a secure cloud environment. The facial recognition software can detect and recognise players who have self-excluded in less than one tenth of a second, with an accuracy rate of over 99%.
The software is low cost, has been approved by Microsoft and can be run on any standard Microsoft Windows PC that has access to one or many webcams.
Once ClientScan is installed, if someone who is on the self-excluding database enters a shop, the camera will pick up their image in real-time and send an alert either via its App, WhatsApp or email to staff on site; alerting them that the person who has entered the premises has self-excluded and will provide information such as their name and self-exclusion period.
This technology will help operators prioritise the safety and wellbeing of its customers, as well as enabling operators to adhere to self-exclusion regulations.
Laura Bedborough, Head of Business Development and co-founder of ClientScan, said: “We take immense pride in launching ClientScan, one of the world’s first AI-driven systems dedicated to protecting self-excluded gamblers.
"Our solution represents a comprehensive and custom development of a Convolution Neural Network to ensure exceptional speed and accuracy whilst maintaining high levels of security.
“ClientScan is designed to specifically address the challenges of self-exclusion within the UK gaming sector and our solution ensures strict compliance with the Gambling Commission regulatory framework.”
