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Research Paper | Information Technology | United States of America | Volume 13 Issue 5, May 2024 | Rating: 5.4 / 10
Enhancing Data Privacy in SAP Finance with Artificial Intelligence Driven Masking Techniques
Abstract: The application of Artificial Intelligence (AI) for personal data masking within SAP Finance systems is a mandate requirement today that addresses the growing imperative for stringent data privacy. It evaluates how AI techniques, particularly machine learning and natural language processing, can enhance the effectiveness of data masking solutions, ensuring compliance with global data protection laws such as GDPR. By integrating AI into SAP Finance, the study demonstrates potential improvements in identifying and masking sensitive financial data, thereby bolstering security and privacy without compromising system performance. The findings suggest that AI - driven data masking not only meets regulatory requirements but also offers scalability and precision beyond traditional methods. As financial data is particularly sensitive and subject to stringent regulatory requirements, effective data masking techniques are crucial for compliance and security. We evaluate current AI methodologies applied to data masking, discussing their effectiveness and efficiency in maintaining data usability while ensuring privacy and compliance with global data protection regulations such as GDPR.
Keywords: Artificial Intelligence (AI), Machine learning (ML), SAP, SAP FICO, Finance, Data privacy, Data Integrity, SAP Security, NACHA, NLP
Edition: Volume 13 Issue 5, May 2024,
Pages: 1819 - 1824