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International Journal of Creative and Open Research in Engineering and Management

A Peer-Reviewed, Open-Access International Journal Supporting Multidisciplinary Research, Digital Publishing Standards, DOI Registration, and Academic Indexing.
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ISSN: 3108-1754 (Online)
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ISO Certification: 9001:2015
Publication Fee: 599/- INR
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License: CC BY 4.0
Peer Review: Double Blind
Volume 02, Issue 04

Published on: April 2026

NATURAL LANGUAGE PROCESSING FOR AUDITING FINANCIAL CONTRACTS AND AGREEMENTS

Singiri Tejasree

K Naresh

Department of MCA, Annamacharya Institute of Technology and Sciences, Tirupati, Andhra Pradesh, India

Article Status

Plagiarism Passed Peer Reviewed Open Access

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Abstract

Complex legal language used in financial contracts and agreements necessitates close examination to guarantee correctness, compliance, and risk reduction. Conventional auditing of such papers is a labor-intensive, time-consuming procedure that frequently relies on subject matter specialists. Natural language processing (NLP) methods have become effective tools for automating document analysis due to the quick development of artificial intelligence.

How to Cite this Paper

Tejasree, S. (2026). Natural Language Processing for Auditing Financial Contracts and Agreements. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(04). https://doi.org/10.55041/ijcope.v2i4.075

Tejasree, Singiri. "Natural Language Processing for Auditing Financial Contracts and Agreements." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 04, 2026, pp. . doi:https://doi.org/10.55041/ijcope.v2i4.075.

Tejasree, Singiri. "Natural Language Processing for Auditing Financial Contracts and Agreements." International Journal of Creative and Open Research in Engineering and Management 02, no. 04 (2026). https://doi.org/https://doi.org/10.55041/ijcope.v2i4.075.

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References

[1] BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding, J. Devlin, M. W. Chang, K. Lee, and K. Toutanova, NAACL, 2019.

[2] "Efficient Estimation of Word Representations in Vector Space," T. Mikolov et al., ICLR, 2013.
[3] Natural Language Processing with Python, S. Bird, E. Klein, and E. Loper, O'Reilly Media, 2009.
[4] Neural Network Approaches for Natural Language Processing, Y. Goldberg, 2017.
[5] Speech and Language Processing, D. Jurafsky and J. H. Martin, 2021.

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  • All submissions are screened under plagiarism detection.
  • Review follows editorial policy.
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  • Peer Review Type: Double-Blind Peer Review
  • Published on: Apr 06 2026
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