BIOMETRIC AUTHENTICATION AND ITS ROLE IN PREVENTION OF DEBIT AND CREDIT CARD FRAUD

AUTHOR – YOGASURUTHI M* & MS. T. VAISHALI**, LLM SCHOLAR* & ASSISTANT PROFESSOR OF LAW** AT THE TAMILNADU DR. AMBEDKAR LAW UNIVERSITY (SOEL), CHENNAI

BEST CITATION – YOGASURUTHI M & MS. T. VAISHALI, BIOMETRIC AUTHENTICATION AND ITS ROLE IN PREVENTION OF DEBIT AND CREDIT CARD FRAUD, INDIAN JOURNAL OF LEGAL REVIEW (IJLR), 4 (4) OF 2024, PG. 899-908, APIS – 3920 – 0001 & ISSN – 2583-2344.

ABSTRACT:

Biometric authentication has become the latest trend in avoiding debit and credit card fraud because it relies on special, unique physiological and behavioral characteristics to verify a person’s identity. Biometric identifiers such as fingerprinting, facial recognition, and voice patterns are intrinsically safe and unique, unlike traditional methods like PINs or passwords, where thieves can easily steal or copy them. This research suggests an innovative way to prevent payment card fraud using biometrics. The solution integrates with the existing payment card security system and takes advantage of biometric recognition technology, which gives a unique ID and stores the biometric data of an individual, just like Aadhaar. A biometric verification system’s integration with a payment card security system not only improves the security of card users but also ensures the physical presence of the cardholder at the point of sale. Further, the employment of biometrics in the financial industry will assure safety standards. This aspect reduces the risks relating to identity theft and duplicate issuance of credit cards along with other wrongful uses. Besides that, the biometric authentication process could also become easy and possible at the level satisfying both the protection demands as well as the convenience aspects together with a balance, being the wonderful tool for fraud in fast-transposing the digital economy. It is changing the future of secure financial transactions with an added layer of security in multi-factor authentication and real-time identity verification.

Keywords: Biometrics, Credit Card Fraud, Fingerprint recognition, Face recognition, Iris Recognition