Author(s): Nazia Sultana, Niraj Kishore Chimote, Hardeep Singh, Usman Ghani, Mohammad Anwar and Shahid Ameen
The study's main goal was to assess how AI-driven technologies may improve security and trust by mitigating the negative effects of financial transaction security. Data was gathered using structured questionnaires categorized by gender and income that were mailed to respondents. Purposive sampling was used to collect data from 391 respondents. In the study, regression testing was employed as a quantitative technique to extract statistical insights from the subjects. The results of the step-wise regression analysis showed that the factors under investigation are significant predictors of the Financial Transaction Security (FTS). The beta value of 0.978, according to the coefficient summary, indicates their effect on Financial Transaction Security (FTS) and their extra contribution to Enhanced Trust (ENT). In summary, the financial services sector presents a revolutionary chance to enhance security protocols by incorporating artificial intelligence (AI). Enhancing trust and security in financial transactions is one of the main advantages of incorporating AI. Security measures, dangers, and the financial ecosystem are all improved by fusing blockchain's transparent and secure platform with AI-powered fraud detection, identity verification, and smart contract automation. This study not only established the relationship between privacy issues and AI in the finance sector, but it also offered recommendations for enhancing data security and protection. Additionally, the document provides fintech organizations with best practices and strategies to ensure data security and privacy. Regulators, financial institutions, and other interested parties who wish to ensure that artificial intelligence is used in the digital finance industry in a way that is morally and responsibly should take note of these findings.