Advanced International Journal for Research

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Digital KYC System for Verification Using OCR and Machine Learning

Author(s) Mr. Naveen K Pattar, Mr. Bhushan Appaji Patil, Ms. Laxmi Kalyani, Ms. Laxmi Konakeri, Prof. Pritam Dhumale
Country India
Abstract Know Your Customer (KYC) is an essential identity verification process used by banks, financial institutions, insurers, telecommunications operators, and digital service providers. Conventional KYC relies on manual document inspection and data entry, which increases processing time, operational effort, and the risk of human error. This paper presents a Digital KYC system that integrates Optical Character Recognition (OCR) and
machine learning to automate the major stages of customer identity verification. Authenticated users upload identity documents such as Aadhaar and PAN cards; OCR extracts the text, and data-processing rules convert the raw output into structured fields such as name, date of birth, and identification number. The extracted fields are validated through document-specific patterns, format checking, normalization, and consistency verification, and a face-detection stage prepares the document photograph and the user’s selfie for biometric comparison. The application layer is implemented with a FastAPI backend in Python, SQLAlchemy, and MySQL and is secured with JWT authentication, bcrypt password hashing, role-based access control, rate limiting, secure file handling, notifications, and audit functionality. A working web interface demonstrates the complete workflow, including image-quality assessment and OCR confidence reporting. Dataset-level accuracy has not yet been measured and is identified as the next experimental phase. The proposed approach reduces manual KYC effort and provides a modular, scalable foundation for digital identity verification.
Keywords Digital KYC, face detection, face verification, FastAPI, identity verification, machine learning, optical character recognition.
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 7, Issue 6, November-December 2026
Published On 2026-11-09
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E-ISSN 3048-7641
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