Facial recognition technology created by ClientScan aims to assist casinos and similar gaming establishments in recognizing individuals listed for self-exclusion. This application allows for the identification of those who have decided to cease gambling, whether for personal reasons or due to worries about potential addiction, and could prevent them from accessing these locations.
The system, a collaboration with Oxford University specialists, employs a protected cloud-based repository to maintain data, including images, of individuals on the self-exclusion list. Utilizing standard camera equipment, the software can pinpoint individuals in a fraction of a second with a high degree of precision. Should a match occur with the self-exclusion database, personnel receive immediate notifications, enabling them to intervene discreetly.
ClientScan stresses that this innovation prioritizes ethical gaming practices and the well-being of at-risk individuals.
Laura Bedborough, the business development lead at ClientScan and a company co-founder, expressed great enthusiasm for the launch of ClientScan. She described it as a pioneering AI-driven platform designed to pinpoint gamblers who have implemented self-exclusion measures. Bedborough highlighted the system’s foundation on advanced convolutional neural network technology, meticulously tailored for exceptional precision and speed without sacrificing security. She further noted that ClientScan was meticulously crafted to tackle the challenge of self-exclusion within the UK’s gambling sector, ensuring adherence to all pertinent regulations set forth by the Gambling Commission.
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