Enhancing Facial Recognition Accuracy in eKYC Systems: A Comparative Evaluation of Euclidean Distance, Cosine Similarity, and SSIM Under Real-World Challenges

Lerworatham, Akaphat and Smajli, Ensi and Feldman, Gerald and Ghonem, Miftah and Mahmoud, Haitham and Elmitwally, Nouh (2024) Enhancing Facial Recognition Accuracy in eKYC Systems: A Comparative Evaluation of Euclidean Distance, Cosine Similarity, and SSIM Under Real-World Challenges. In: The 4th International Conference of Advanced Computing and Informatics, 16 - 17 December 2024, Birmingham City University. (In Press)

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Abstract

Ensuring robust banking security is an ongoing challenge, especially in the face of increasingly sophisticated fraud techniques. One critical aspect is the accuracy of facial recognition technology, which plays a central role in elec-tronic Know Your Customer (eKYC) processes. Inaccurate facial recognition can result in security breaches, allowing fraudsters to exploit vulnerabilities during customer registration and transactions. This issue is particularly signif-icant in Thailand’s banking industry, where reliance on eKYC frameworks is growing. Current facial recognition methods often struggle with false posi-tives, impersonation, and spoofing attacks, threatening the integrity of finan-cial systems.
Hence, this paper addresses these concerns by exploring both the limitations of existing face recognition techniques and the opportunities presented by recent advancements in deep learning. The primary goal of this research is to enhance the accuracy of face recognition systems used in eKYC through the integration of advanced algorithms. By refining facial feature extraction methods and employing adaptive learning models, we aim to reinforce the verification process and significantly reduce the risk of fraud.

Item Type:	Conference or Workshop Item (Paper)
Dates:	Date Event 16 December 2024 Accepted
Subjects:	CAH11 - computing > CAH11-01 - computing > CAH11-01-01 - computer science
Divisions:	Faculty of Computing, Engineering and the Built Environment > College of Computing
Depositing User:	Nouh Elmitwally
Date Deposited:	13 Feb 2025 12:50
Last Modified:	13 Feb 2025 12:50
URI:	https://www.open-access.bcu.ac.uk/id/eprint/16135