Privacy Preserving AI in Financial Sector- Balancing Utility, Security and Compliance

Main Article Content

Neha Tyagi

Abstract

The fast implementation of the use of Artificial Intelligence (AI) in the financial industry has enhanced the efficiency of operations, risk evaluation, detection of fraud, and customized services to customers to a considerable extent. Nevertheless, the wide application of sensitive financial and personal data causes serious issues connected with data privacy, data security, and regulatory compliance. The paper explores Privacy Preserving Artificial Intelligence (PPAI) approaches that would allow financial institutions to utilize AI-based insights without violating confidential information, as well as legal regulations, including the GDPR, RBI data localization policy, and new regulations in the direction of artificial intelligence globally. The suggested methodology will consist of the comparative analysis of the solutions presenting privacy protection: federated learning, differential privacy, secure multi-party computation, and homomorphic encryption, and apply them to core financial applications, such as credit scoring, transaction monitoring, and fraud detection. An integrated framework between federated learning and differential privacy is developed to combine the utility of the model and the privacy guarantees. Benchmark financial datasets are used to evaluate the performance of an experimental evaluation based on the accuracy, the risk of data leakage, computational overhead, and regulatory alignment. Findings show that the hybrid PPAI structure attains close central performance of the model where the predictive accuracy is reduced by less than 3 percent and yet the data exposure is reduced to a minimum and the privacy laws are complied with. The results indicate that a combination of privacy-preserving methods with a well-planned approach will be a good balance of utility, security, and compliance that does not affect business goals. This paper finds that Privacy Preserving AI is not a regulatory requirement but a strategic facilitator of trust, resilience, and competitive edge in the new financial ecosystem.

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How to Cite

Privacy Preserving AI in Financial Sector- Balancing Utility, Security and Compliance. (2025). International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 8(5), 12795-12802. https://doi.org/10.15662/IJRPETM.2025.0805016

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