Incode Launches Deepsight AI System to Combat Deepfakes and Synthetic Identity Attacks
Incode has launched Deepsight, an AI-driven system designed to detect and prevent deepfakes and synthetic identity attacks for large organizations. Utilizing a three-layer model that evaluates behavior, device integrity, and visual signals, Deepsight has been validated by Purdue University for its high accuracy and low false acceptance rate. Currently deployed by companies like TikTok and Scotiabank, the system safeguards millions of users across over six million identity sessions amid rising AI-generated fraud attempts.
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Incode has introduced Deepsight, an AI-based defense system aimed at detecting and blocking deepfakes, virtual cameras, and synthetic identity attacks for large organizations. This product is part of Incode's broader investment in AI for identity verification and trust, linked to its upcoming Agentic Identity project.
Deepsight utilizes a three-layer model that assesses behavior, device integrity, and visual signals to enhance identity checks. The system has been evaluated by Purdue University, achieving the highest accuracy and lowest false acceptance rate among commercial deepfake detection systems.
Deepsight is currently deployed by enterprises such as TikTok, Scotiabank, and Nubank, protecting millions of users across over six million identity sessions. Incode processes billions of identity checks annually as AI-generated fraud attempts increase.
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