Leveraging OpenCV and Tensorflow in an Automated E-KYC System

Q: How many days will it take for my paper to be published?

The review time for papers is not fixed. However, if the paper is accepted and the author completes the processing charges formalities, the paper will be published within a few working days.

Q: I would like to receive a hard copy of the journal materials. Are there any additional charges?

You can log in to the author portal and pay 500 INR to receive the hard copy materials.

Ayaan Shaikh; Joshua Angre; Yash Tapse; Tanay Soni

Leveraging OpenCV and Tensorflow in an Automated E-KYC System

Authors: Ayaan Shaikh, Joshua Angre, Yash Tapse, Tanay Soni

Unique Paper ID: 169351
Volume: 11
Issue: 6
PageNo: 1415-1420

Keywords: No Keywords Found

Abstract:
The increasing demand for secure and efficient identity verification in financial services has led to the rise of automated Electronic Know Your Customer (e-KYC) systems. This paper presents a comprehensive analysis of leveraging OpenCV and TensorFlow to enhance the e-KYC process by integrating real-time video-based human verification, natural language processing (NLP), optical character recognition (OCR), and biometric data analysis. The proposed framework utilizes real-time eye and hand movement tracking for human verification, followed by ID card detection, signature verification, and data extraction through OCR. By incorporating adaptive machine learning models, the system ensures continual improvements in accuracy and processing speed, enabling quicker customer onboarding and document verification. Additionally, the framework provides real-time feedback for discrepancies in user data, ensuring compliance with regulatory standards while enhancing user experience. This survey evaluates current methodologies and highlights the transformative potential of deep learning architectures in creating robust, user-friendly, and scalable e-KYC solutions. We conclude by outlining future research directions aimed at improving the scalability, security, and performance of automated e-KYC systems in diverse financial contexts, contributing to operational efficiency in financial institutions.

Download article

email to a friend

Cite This Article

ISSN: 2349-6002
Volume: 11
Issue: 6
PageNo: 1415-1420

Leveraging OpenCV and Tensorflow in an Automated E-KYC System

Available:https://ijirt.org/article?manuscript=169351

Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

Join Our IPN

IJIRT Partner Network

Submit your research paper and those of your network (friends, colleagues, or peers) through your IPN account, and receive 800 INR for each paper that gets published.

Join Now