Multimodal biometric authentication combines multiple identity factors, such as voice, face, fingerprints, device data, and behavior, to create a more layered verification process than single-factor methods. A mix of core modalities, such as facial recognition, voice biometrics, fingerprints, and behavioral patterns, works together to create a stronger, layered identity verification system. Advancements in AI, liveness detection, deepfake detection, and real-time processing help authentication run faster, stay secure, and handle more users. Key trends such as continuous authentication, zero-trust security, passive biometrics, privacy-focused AI, and edge processing are shaping the evolution of identity verification. Despite its benefits, challenges such as privacy risks, system complexity, bias, and user trust must be carefully managed to implement solutions effectively and ethically. Source: https://www.resemble.ai/resources/multimodal-biometric-authentication-future-trends-risks-and-security-applications