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Public Budget AI Audit: 5 Fraud Findings & System Evaluation

· 8 min read
Jaybee
AI & Robotics Engineer

National Budget AI Audit Findings

📌 Key Takeaways

  • Interim Audit Deployment: Using our production-grade autonomous audit agent (national_budget_ai), we completed a full audit screening across representative public procurement datasets (5 major budget programs and 6 procurement contracts).
  • 4 Core Fraud Findings (Strictly Anonymized):
    1. Split Private Contracts: Smurfing contracts under the $20,000 threshold across 12 days to evade competitive bidding ($43,000 total, 94.5% similarity to Supreme Audit rulings).
    2. Shared Address Shell Cartels: 3 dummy vendors sharing the exact same room and building winning exclusive tenders ($158,000 total).
    3. 7x–10x Unit Price Markup: Inflated advisory fees (7.0x median) and GPU server rentals (10.0x median) detected via automated HWPX table parsing.
    4. Low Delivery Efficiency (DEI 30.0%): Only 30.0% of funds reached target beneficiaries, with 70.0% absorbed in administrative overhead.
  • System Performance Evaluation:
    • Precision: 0.00% financial calculation hallucination via deterministic SQL AST parsing; 11/11 test suites passed.
    • Throughput: 0.03s per contract to generate complete audit dossiers and statutory enforcement drafts.
    • Field Limitations: Blind spots in borrowed-name owners and multi-tier private subcontracts identified.

Autonomous Budget Audit Agent: Text-to-SQL & GraphRAG

· 10 min read
Jaybee
AI & Robotics Engineer

Autonomous Public Budget Audit Agent

📌 Key Takeaways (TL;DR)

  • The Goal: Build an autonomous AI agent to audit $500B annual public expenditures, tracking government procurement contracts (KONEPS), fiscal databases (dBrain+), and messy Korean HWPX budget tables to detect price gouging, split contracts, and paper-company cartels.
  • Anticipated Challenges & Prevention: Prevented LLM numerical hallucinations by delegating calculations to a Deterministic Text-to-SQL Engine, while isolating relationship and cartel tracking to a Heterogeneous Knowledge Graph (GraphRAG) in a dual-brain architecture.
  • Actual Bugs Encountered & Solved: (1) Solved company name and street address fragmentation breaking cartel detection via a robust EntityResolver, (2) Caught temporal split contracts slipping past date filters via a 30-day sliding window algorithm, (3) Overcame auditor distrust of AI black-boxes by building an XAI Dossier Generator binding findings 1:1 with statutory clauses and 10-year official audit precedents.
  • Verification: 11 out of 11 regression test harness suites passed, successfully exposing a 38.5M KRW shared-address private procurement cartel and a 70% indirect overhead leakage (DEI score 30%).