• Pranav Khare
• Shristi Srivastava

In the context of business operations, it is imperative for service providers to engage in the identification and evaluation of clients, as well as the assessment of the risks associated with them, before proceeding with the delivery of services. Providers have challenges in verifying the identities or completing due diligence of potential customers who do not possess formal documentation or whose identity verification is problematic. The process of e-KYC entails authorized organizations accessing a digital identification system in order to identify and validate the identities of clients, occasionally extracting necessary information. This study presents an advanced E-KYC (Know Your Customer) authentication system that leverages blockchain technology and AI-driven face recognition to address the inefficiencies and security vulnerabilities of traditional KYC processes. In addition, the proposed system contains data storage using encrypted blocks and users’ consent-based data sharing for privacy. Some of the causal attributes that make identification and recognition accurate are Haar-cascade for face detection, Deep Face for image comparison, and others give this project an accuracy rate of 92%. It provides an intuitive graphical user interface to ease the process of using the system and uses OTP for further user authentication. Administrators are able to increase efficiency through the utilization of efficient fast search and date wise sorting for subsequent user interaction tracking.

KYC, E-KYC, AI-driven, DNN, Haar-cascade, DeepFace.

"Transforming KYC with AI: A Comprehensive Review of Artificial Intelligence-Based Identity Verification ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 12, page no.h525-h531, December-2023, Available :http://www.jetir.org/papers/JETIR2312766.pdf

"Transforming KYC with AI: A Comprehensive Review of Artificial Intelligence-Based Identity Verification ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 12, page no. pph525-h531, December-2023, Available at : http://www.jetir.org/papers/JETIR2312766.pdf