Advances In NLP-Driven Analytics for Automated Detection of Regulatory Liabilities in High-Volume Contracts
Abstract
Contract portfolios at large enterprises now routinely exceed tens of thousands of active agreements, and the regulatory obligations attaching to those agreements have multiplied faster than legal review capacity. In 2025 this gap became acute: the EU Digital Operational Resilience Act became applicable on 17 January without a transition period, forcing thousands of financial entities into large-scale contract remediation, while the general-purpose AI obligations of the EU AI Act took effect on 2 August. Both events created demand for systems that can read an entire contract portfolio and flag, with evidence, where regulatory liability exists. This paper reviews the state of natural language processing for automated regulatory liability detection as of the end of 2025 and sets out a layered architecture for production deployment. Regulatory liability detection is distinguished here from the better-studied task of clause extraction, on the argument that the former is a normative verification problem requiring a rule base, an evidence retrieval mechanism, and an adjudication step, rather than a span-labelling problem. Four technical shifts that reshaped the field during 2025 are surveyed: the maturation of long-context models beyond the length of most commercial contracts, the emergence of legal-specific retrieval evaluation, the arrival of explicit reasoning models capable of rule-grounded justification, and the closing but still material gap between proprietary and open-weight models on clause-level risk identification. Evidence is also drawn from compliance analytics research in financial audit, cybersecurity governance, critical infrastructure protection, procurement, supply chain assurance, payments, pharmaceutical regulation, aviation safety oversight, and enterprise systems engineering, on the argument that the design problems in regulatory liability detection are not confined to legal NLP and that adjacent literatures have already resolved several of them. A metric suite appropriate to the asymmetric cost structure of compliance work is then set out, in which a missed mandatory clause is not commensurate with a false alarm, and the F1 scores dominant in the literature are argued to be a poor proxy for deployment value. The paper closes on a reflexive governance question specific to this application: a system that classifies legal risk may itself fall within the scope of the regulation it is deployed to manage.
Keywords
legal NLPregulatory technologycontract analyticscompliance verificationretrieval-augmented generationlarge language modelsDORAEU AI Actobligation extractionlegal risk
References
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Plant Science Archives, 10(4), 51-59. https://doi.org/10.51470/PSA.2025.10.4.51 Dogbatsey, E. A., & Ebhojie, O. (2018). Budget compliance and statutory reporting in Sub- Saharan Africa: A systematic review of frameworks, gaps, and reform pathways. Zenodo. https://doi.org/10.5281/zenodo.20446859 \\[Originally numbered 2(6); journal name not captured in source.\\] Dogbatsey, E. A., Ebhojie, O., & Oyeleye, A. O. (2019). Reconciliation control and financial workflow redesign in emerging market organizations: A conceptual framework. Zenodo. https://doi.org/10.5281/zenodo.20447103 \\[Originally numbered 3(5); journal name not captured in source.\\] Dogbatsey, E. A., Ebhojie, O., & Oyeleye, A. O. (2021). Cross-border segregation of duties and acces\\\... \\[Entry truncated in source; title incomplete and no identifier provided. Verify and complete.\\] Dosunmu, A. A., & Ogundele, P. O. (2019). Security audit and enterprise risk assessment frameworks for resilient information systems. Iconic Research and Engineering Journals, 3(5), 434-447. https://doi.org/10.64388/IREV3I5-1713225 Dosunmu, A. A., & Ogundele, P. O. (2020). Intrusion detection and prevention models for enhancing organizational cyber defense effectiveness. Iconic Research and Engineering Journals, 4(6), 310-324. https://doi.org/10.64388/IREV4I6-1713226 Dosunmu, A. A., & Ogundele, P. O. (2021). Incident response and digital forensics strategies for rapid cyber attack containment. Gyanshauryam, International Scientific Refereed Research Journal, 4(4), 239-258. Dosunmu, A. A., & Ogundele, P. O. (2022). Threat intelligence integration frameworks supporting proactive enterprise cybersecurity decision making. Gyanshauryam, International Scientific Refereed Research Journal, 5(3), 397-416. Dosunmu, A. A., & Ogundele, P. O. (2023). Cyber threat actor analysis models for strategic enterprise security planning. Shodhshauryam, International Scientific Refereed Research Journal, 6(5), 513-531. Dosunmu, A. A., & Ogundele, P. O. (2024a). Breach and attack simulation frameworks for continuous validation of enterprise security controls. International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 10(3), 1100- 1119. Dosunmu, A. A., & Ogundele, P. O. (2024b). Cyber risk quantification models for prioritizing enterprise security investment decisions. International Journal of Multidisciplinary Research and Growth Evaluation, 5(6), 1777-1785. https://doi.org/10.54660/.IJMRGE.2024.5.6.1777-1785 Dosunmu, A. A., & Ogundele, P. O. (2024c). Enterprise scale continuous security validation models for regulated digital infrastructures. International Journal of Scientific Research in Humanities and Social Sciences, 1(2), 929-945. Dosunmu, A. A., & Ogundele, P. O. (2024d). Threat informed defence engineering models for measuring security control effectiveness at scale. International Journal of Advanced Multidisciplinary Research and Studies, 4(6), 2847-2858. Dosunmu, A. A., & Ogundele, P. O. (2025a). Adversary simulation design frameworks for proactive cyber defense in complex environments. International Journal of Computer Science and Mathematical Theory, 11(12), 193-209. https://doi.org/10.56201/ijcsmt..pg193.209 Dosunmu, A. A., & Ogundele, P. O. (2025b). Cyber defense performance measurement frameworks for executive and board level governance. Computer Science and IT Research Journal, 6(11), 895-913. https://doi.org/10.51594/csitrj.v6i11.2164 Dosunmu, A. A., & Ogundele, P. O. (2025c). Security orchestration and automation models for accelerating incident detection and response. Computer Science and IT Research Journal, 6(11), 878-894. https://doi.org/10.51594/csitrj.v6i11.2163 Ebhojie, O., Dogbatsey, E. A., & Oyeleye, A. O. (2023a). Audit liaison, corrective action planning, and control compliance in multinational organisations: A systematic literature review. 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International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 8(4), 826-845. Edivri, J., & Oteri, O. (2024). A conceptual KPI-driven decision and optimization framework for IT service delivery, portfolio performance, and adoption. Gyanshauryam, International Scientific Refereed Research Journal, 7(1), 167-187. https://doi.org/10.32628/GISRRJ246643 Efobi, O. Z., Akinleye, O. K., & Fasawe, O. (2021). Framework for data-driven operations management and performance improvement in educational institutions. Gyanshauryam, International Scientific Refereed Research Journal, 4(6), 127-158. Efobi, O. Z., Akinleye, O. K., & Fasawe, O. (2022a). Conceptual framework for sustainable procurement practices in local manufacturing enterprises in Africa. Gyanshauryam, International Scientific Refereed Research Journal, 5(6), 248-266. Efobi, O. Z., Akinleye, O. K., & Fasawe, O. (2022b). Conceptual model for data-driven lean supply chain optimization in manufacturing and retail operations. International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 8(2), 703-734. https://doi.org/10.32628/CSEIT2541335 Efobi, O. Z., Akinleye, O. K., & Fasawe, O. (2023). Conceptual framework for developing a resilience index for post-pandemic supply chains. Shodhshauryam, International Scientific Refereed Research Journal, 6(2), 421-432. Ekechi, N. V., Anunagba, C. O., & Ozowara, D. E. (2022). Advances in financial forensics techniques for detecting cyber-enabled fraud in telemedicine services. Shodhshauryam, International Scientific Refereed Research Journal, 5(1), 428-450. Ekeocha, A. H., Aganga, A. A., Adejoro, F. A., Oyebanji, A., Oluwadele, J. F., & Tawose, O. M. (2021). Phenotypic characteristics of indigenous chickens in selected regions of Nigeria. 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Development of a cross-border regulatory harmonization model for African pharmaceutical markets: The ARCH-Model framework. International Journal of Health and Pharmaceutical Research, 9(5), 148-186. https://doi.org/10.56201/ijhpr.v9.no5.2024.pg148.186 Eze, F. I., Akinleye, O. K., & Anene, U. N. (2024b). Development of a risk-based accelerated approval decision model balancing speed, safety, and evidence quality in pharmaceutical regulatory science. , 7(6), 120-161. https://doi.org/10.56201/rjpst.v7.no6.2024.pg120.161 Eze, F. I., Anene, U. N., & Akinleye, O. K. (2022a). Creation of a drug shortage early warning and regulatory response model for essential medicines in global health systems. Research Journal of Pure Science and Technology, 5(1), 57-95. https://doi.org/10.56201/rjpst.v5.no1.2022.pg57.95 Eze, F. I., Anene, U. N., & Akinleye, O. K. (2022b). Design of an integrated regulatory readiness maturity model for pharmaceutical companies seeking global market entry. 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Decentralized produced water treatment systems for remote energy assets: A conceptual design framework. International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 10(3), 1133- 1151. Falegan, O. C., & Aniebonam, S. O. (2025). Resource recovery and beneficial reuse of produced water in energy operations: A review of sustainable pathways. International Journal of Advanced Multidisciplinary Research and Studies, 5(6), 1959-1969. https://doi.org/10.62225/2583049X.2025.5.6.5678 Filani, O. M., Nnabueze, S. B., Ike, P. N., & Wedraogo, L. (2022). Real-time risk assessment dashboards using machine learning in hospital supply chain management systems. International Journal of Multidisciplinary Evolutionary Research, 3(1), 65-76. https://doi.org/10.54660/IJMER.2022.3.1.65-76 Fobellah, A. N. (2025a). Cognitive biases in financial decision-making: Implications for audit and risk management in large corporations: A conceptual review. 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Belonging-centered retention: A conceptual model linking mentorship, advising, and institutional belonging to persistence among underrepresented STEM students. Journal of Humanities and Social Policy, 11(10), 138-152. https://doi.org/10.56201/jhsp..pg138.152 Ike, P. N., Aifuwa, S. E., Nnabueze,
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