NACC AI Allegation Screening — Thailand's automated anti-corruption complaint processor

Thailand's National Anti-Corruption Commission (NACC) has deployed an AI-powered complaint-screening pipeline to process the large volume of incoming corruption allegations. The system combines Optical Character Recognition (OCR), Natural Language Processing (NLP), and supervised machine learning to automate initial document segmentation, allegation classification, and workflow routing — tasks previously handled manually by NACC administrative staff.

The pipeline extracts text from scanned complaint documents, classifies the type of allegation, and routes each submission to the appropriate review unit. Human reviewers retain full authority over final screening decisions; the AI handles the time-consuming pre-processing stage, freeing staff to focus on substantive evaluation.

A 2025 peer-reviewed study published in PubMed Central documented the system's performance in operational conditions: OCR module F1-score of 81.8% (precision 84.2%, recall 79.6%), document classification accuracy of 57.5%, and an average complaint processing time reduction of 78.6% versus the manual baseline. The 57.5% classification accuracy is reported transparently by the authors as a current limitation; the system is explicitly positioned as a triage aid, not a final decision-maker.

Thailand's NACC operates under the country's constitutional anti-corruption framework. Its adoption of AI for complaint handling is noted in Thailand's chapter of the OECD Anti-Corruption and Integrity Outlook 2026 as part of broader public integrity modernisation efforts.

Read the full analysis: https://pmc.ncbi.nlm.nih.gov/articles/PMC12818598/