From Manual to Intelligent GRC: The Future of Enterprise Risk Automation

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@article{1710293,
      author = {Iboro Akpan Essien, Emmanuel Cadet, Joshua Oluwagbenga Ajayi, Eseoghene Daniel Erigha; Ehimah Obuse, Lawal Abdulmutalib Babatunde; Noah Ayanbode},
      title = {From Manual to Intelligent GRC: The Future of Enterprise Risk Automation},
      journal = {Iconic Research And Engineering Journals},
      year = {2020},
      volume = {3},
      number = {12},
      pages = {421-434},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1710293.pdf},
      abstract = {The evolution from manual Governance, Risk, and Compliance (GRC) processes to intelligent, automated frameworks marks a pivotal transformation in enterprise risk management. Traditional GRC systems, often dependent on labor-intensive workflows, static reporting cycles, and siloed data, struggle to meet the velocity, complexity, and regulatory rigor of modern business environments. The convergence of artificial intelligence (AI), robotic process automation (RPA), blockchain, and advanced analytics is enabling a paradigm shift toward intelligent GRC?systems capable of real-time monitoring, predictive risk modeling, and automated compliance validation. These innovations not only reduce operational burdens and human error but also enhance the agility and responsiveness of risk programs across global and multi-jurisdictional operations. Intelligent GRC platforms integrate data from diverse internal and external sources, applying machine learning algorithms to detect anomalies, forecast emerging risks, and recommend adaptive control measures. Blockchain-enabled audit trails strengthen transparency and regulatory trust, while natural language processing (NLP) automates the interpretation of evolving regulatory texts, minimizing compliance lags. This capability is particularly valuable in sectors facing rapid regulatory change, cybersecurity threats, and environmental, social, and governance (ESG) pressures. Furthermore, intelligent automation fosters tighter alignment between risk governance and business strategy, embedding risk considerations into decision-making at every organizational level. Despite the promise, challenges remain in cost, integration with legacy infrastructure, and ensuring algorithmic transparency to maintain stakeholder confidence. Future research should focus on quantifying the return on investment, developing interoperable GRC standards, and addressing ethical considerations in AI-driven decision-making. By adopting intelligent, adaptive GRC systems, enterprises can transition from reactive compliance to proactive, strategic risk management?positioning themselves to thrive in an increasingly complex, regulated, and digital-first global economy.},
      keywords = {Manual, Intelligent, GRC, Future, Enterprise, Risk automation},
      month = {June},
  }