AI-based video verification will be the next level of authentication for the gaming industry

We live in an era where machines, software, and various automatic processes are transforming a large part of the world’s productive activities. Artificial intelligence (AI) plays a very important role in this transformation. One of the most promising fields of application of AI is the so-called identity verification processes, where agility, scalability and security have become a priority, especially for the iGaming industry with online verification scenarios. The coolest thing about all this is that video has now been integrated into the equation, which makes online casinos implement more advanced security measures.

While it is true that video verification has enabled better-informed responses, the application of AI for this purpose has undoubtedly come to change the game completely. Taking advantage of the benefits gained through video to verify intrusion alarms has gained tremendous momentum in recent years as the technology has improved and become less expensive.

Identity verification processes face three major challenges: security, agility, and scalability. If we talk about security, impersonation fraud is the big problem to attack, especially in the iGaming industry, where this is not uncommon. Verification systems must therefore include new levels of security that go beyond the request for an ID document, and this is where AI and its video capabilities come into play.

Developments in AI undoubtedly promise to solve many of the challenges ahead. With AI, biometric and document authenticity validations can be automated with degrees of confidence approaching those of a human expert. They have the ability to process millions of transactions at a rate unattainable by teams of human validators.

Facial recognition technologies make it possible to identify a person by analyzing the characteristics of his or her face. The process is performed by matching a previous facial record of the user with a facial record at the time of identification or validation of a given transaction. Different automatic AI models that extract features on the symmetry of the elements of a face or more sophisticated deep neural network models can be employed for this task.