Critical Analysis of Online Fraud Prevention and Legal Frameworks inIndia: A Meta-Analytic Review
Keywords:
Online fraud prevention, fraud detection, biometric authentication, machine learning, legal frameworks India.Abstract
Increased digitalization of the financial and government systems in India means that there is an augmented prospect of online frauds, therefore making it a challenge that needs integrated efforts with superior technologies and solid legal frameworks. This meta- analytic review critically looks into the amalgamation of emergent aspects of artificial intelligence, deep learning, and biometric authentication with the emerging legal aspects of fraud prevention in the Indian situation. Biometric systems, and especially multimodal systems which use face, fingerprint and iris systems are more accurate in authentication and are more resistant to spoofing attacks compared to unimodal systems. Algorithms of AI and deep learning, including CNNs, LSTMs, and hybrid ensembles, surpass the rule- based method of system performance in terms of fraud detection, with accuracy levels (much) higher than 99 percent. The vulnerabilities are associated with issues of data privacy and regulatory compliance, in addition to the two-fold risks of bad actors of AI. On legal aspect, although the Information Technology Act, DPDPA 2023, and Bharatiya Nyaya Sanhita 2023 have undergone amendments to enhance the regulatory regime, they are marred by the problem of bottlenecks in implementation and lack of jurisdiction. The level of public awareness and the level of digital financial literacy remains a crucial aspect that has not received enough attention and the extent to which it influences the susceptibility to fraud. There must also be technology and therefore, policy reforms, institutional capacity building and synchronous education of the citizens are all relevant to mitigate the fraud effectively. The results point to the direction of adaptive governance models and long-term effects of AI integration in the Indian fraud prevention system.
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