Designing secure data applications and products in the AI-driven finance sector
Year: 2025
Type: article
Abstract: The financial sector is experiencing a profound transformation through artificial intelligence and big data technologies, creating both opportunities and security challenges. Financial institutions now implement sophisticated AI systems for fraud detection, trading, and personalized services, necessitating robust security frameworks to protect sensitive data. These organizations face threats, including data breaches, adversarial attacks, and regulatory compliance issues, requiring multilayered protection strategies. This article explores key security challenges in AI-driven finance and presents best practices, including advanced encryption, sophisticated access control, and privacy-preserving AI techniques. It also examines future directions, such as blockchain integration for immutable audit trails and quantum-safe security measures to address emerging threats.
Author: Rajkumar Sekar
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4409373228