Semantic Scholar Open Access 2025 4 sitasi

From Complexity to Clarity: AI/NLP's Role in Regulatory Compliance

J. Jain Nivedhitha Dhanasekaran Mona T. Diab

Abstrak

Regulatory data compliance is a cornerstone of trust and accountability in critical sectors like finance, healthcare, and technology, yet its complexity poses significant challenges for organizations worldwide. Recent advances in nat-ural language processing, particularly large language models, have demonstrated remarkable capabilities in text analysis and reasoning, offering promising solutions for automating compliance processes. This survey examines the current state of automated data compliance, analyzing key challenges and approaches across problem areas. We identify critical limitations in current datasets and techniques, including issues of adaptability, completeness, and trust. Looking ahead, we propose research directions to address these challenges, emphasizing standardized evaluation frameworks and balanced human-AI collaboration.

Topik & Kata Kunci

Penulis (3)

J

J. Jain

N

Nivedhitha Dhanasekaran

M

Mona T. Diab

Format Sitasi

Jain, J., Dhanasekaran, N., Diab, M.T. (2025). From Complexity to Clarity: AI/NLP's Role in Regulatory Compliance. https://doi.org/10.18653/v1/2025.findings-acl.1366

Akses Cepat

Informasi Jurnal
Tahun Terbit
2025
Bahasa
en
Total Sitasi
Sumber Database
Semantic Scholar
DOI
10.18653/v1/2025.findings-acl.1366
Akses
Open Access ✓