M.Pragnika, B.Akshara, P.Shailaja 02 10 Inpersonbankingisstill an important part of financial services around the world Hybrid bank branches with service robots can improve efficiency and reduce operating costs An efficient autonomous KnowYourCustomer KYC is required for hybrid banking In this paper an automated deep learning based framework for interbank KYC in robotbased cyberphysical banking is proposed A deep biometric architecture was used to model the customers KYC and anonymize the collected visual data to ensure the customers privacy The symmetricasymmetric encryptiondecryption module in addition to the blockchain network was used for secure and decentralized transmission and validation of the biometric information Ahighcapacity fragile watermarking algorithm based on the integertointeger discrete wavelet transform in combination with the Z6 and A6 lattice vector quantization for the secure transmission and storage of inperson banking documents is also proposed The proposed framework was simulated and validated using a Pepper humanoid robot for the automated biometricbased collection of handwritten bank checks from customers adhering to COVID19 pandemic safety guidelines The biometric information of bank customers such as fingerprint and name is embedded as a watermark in the related bank documents using the proposed framework The results show that the proposed security protection framework can embed more biometric data in bank documents in comparison with similar algorithms Furthermore the quality of the secured bank documents is 20 higher in comparison with other proposed algorithms Copyright (c) Journal of Science Engineering Technology and Management Science. All rights reserved 2026