Automated Compliance Risk Scoring & Optimization for Korean Government Organizations (KGCRO)
**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.
Institutions
- Freed–Hardeman University (US)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-09-18
- DOI
- https://doi.org/10.5281/zenodo.17153448
- Primary Topic
- Geochemistry and Geologic Mapping
- Type
- article
- Field-Weighted Citation Impact
- 0.00