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The need for reliable and safe methods of user verification has grown as digital banking continues to grow. Passwords PINs and one-time codes are examples of older techniques that are no longer as trustworthy. They are more susceptible to unauthorized access because they can be stolen hacked or misused through phishing attacks. To get around these limitations the current work provides an improved banking security system with anti-spoofing and AI-based facial recognition. Deep learning technology is used in this system to identify a persons face and it also uses small real-time signals like blinking and skin texture to determine if the person is truly alive. A CNN model analyzes a persons facial features and compares them to user information that is safely kept in the system. It is difficult for someone to trick the system with printed photos mobile displays or masks because of the integrated anti-spoofing feature. In general this configuration makes online transactions safer and gives users greater confidence in their digital banking.