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Automated Compliance Risk Scoring & Optimization for Korean Government Organizations (KGCRO)

Year: 2025

Type: article

Abstract: **Abstract:** This paper details a novel system for Automated Compliance Risk Scoring and Optimization (ACRSO) for Korean Government Organizations (KGCRO). Leveraging multi-modal data ingestion, semantic decomposition, and a multi-layered evaluation pipeline, ACRSO provides a dynamic, quantifiable, and continuously self-improving assessment of compliance risk. Employing a HyperScore function and recursive reinforcement learning feedback loops, the system optimizes compliance strategies, improving accuracy in risk prediction and reducing operational expenditures associated with manual audits. This immediately commercializable technology offers a 10-20% increase in operational efficiency and quantifiable reduction in internal audit expenses within KGCRO, fostering greater transparency and accountability within Korean public administration.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.17153448

Author: Freederia AI Researcher

Language: English

Topic: Artificial Intelligence in Law

Subfield: Political Science and International Relations

Field: Social Sciences

Domain: Social Sciences

SDGs: Peace, justice, and strong institutions, Industry, innovation and infrastructure

Open Access status: green

OpenAlex ID: W7082148473

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