A Multi‑Jurisdictional, Entity‑Level Governance Risk Assessment Framework
Applied Coherence Institute (ACI) & Sovereign Integrity Institute (SII)
Authors: Nathan Veil (ACI) & David Humble (SII)
Date: June 1, 2026
Status: Technical Report – Open Methodology
License: CC BY-NC 4.0
Abstract
Markets and societies lack continuous, entity‑level, verifiable signals for governance risk. Existing mechanisms – credit ratings, ESG scores, corruption indices – are infrequent, self‑reported, or country‑level. This paper introduces the Institutional Integrity and Transparency Index (IITI) , a live, public governance risk assessment system for corporate and government entities. The IITI provides weekly integrity scores (0–100) for over 200 entities across six jurisdictions, using publicly available data and a transparent, weighted indicator methodology. The paper defines institutional integrity operationally, describes the indicator framework, reports early validation results, provides a replicable architecture, and discusses methodological limitations. The IITI is positioned as a transparency instrument, not as a campaign or protest.
Keywords: governance risk, institutional integrity, transparency, accountability, entity‑level assessment
1. Introduction
Governance risk – the risk that an entity will fail to meet its stated obligations due to corruption, opacity, or regulatory capture – is systematically underpriced in credit, insurance, and procurement markets (Klitgaard, 1998; Kaufmann et al., 2010). Credit ratings focus on financial solvency, not governance integrity. ESG scores rely on self‑reporting (Berg et al., 2022). Corruption indices are country‑level and annual (Transparency International, 2025). As a result, governance risk remains invisible until a scandal, enforcement action, or collapse reveals the hidden liability.
The Institutional Integrity and Transparency Index (IITI) addresses this gap. The IITI provides weekly, entity‑level integrity scores for corporations and government entities across six jurisdictions (Thailand, Hong Kong, Singapore, the United States, China, and Laos), using only publicly available, verifiable data.
The objective of the IITI is not to determine guilt or innocence, but to provide a transparent, repeatable framework for assessing institutional integrity risk using publicly available information.
2. Operational Definitions
2.1 Institutional Integrity
In this paper, institutional integrity is operationalized as observable indicators of governance quality, transparency, accountability, regulatory compliance, and stakeholder protection. It is measured across multiple domains (see Section 4). The term is used descriptively, not normatively. A high integrity score indicates that available public data suggests strong governance practices; a low score indicates that available public data suggests governance risks, opacity, or documented misconduct.
2.2 Governance Risk
Governance risk refers to the likelihood that an entity will experience regulatory enforcement, procurement irregularities, corruption findings, or other accountability failures. The IITI does not predict such events. It reports on observable indicators that prior research has associated with such outcomes (Kaufmann et al., 2010).
2.3 Transparency as an Indicator
Limited disclosure is not interpreted as evidence of misconduct. However, transparency itself constitutes an evaluable governance characteristic. Entities with limited public disclosure receive lower scores on transparency‑related indicators, with a clear notation that low scores in such cases may reflect opacity as much as misconduct.
3. Jurisdictional Coverage
As of June 1, 2026, the IITI covers six jurisdictions:
| Jurisdiction | Corporate Entities | Government Entities |
|---|---|---|
| Thailand | 20 | 20 |
| Hong Kong | 15 | 15 |
| Singapore | 16 | 15 |
| United States | 23 | 20 |
| China | 16 | 15 |
| Laos | 12 | 12 |
| Total | 102 | 97 |
Coverage is expanding. The architecture is jurisdiction‑agnostic.
4. Indicator Framework
4.1 Corporate Indicators
| Indicator Category | Weight | Description |
|---|---|---|
| Governance | 25% | Ownership transparency, board independence, whistleblower protection |
| Legal & Regulatory Compliance | 25% | Fines, sanctions, debarment, obstruction history |
| Supply Chain & Labor Integrity | 20% | Forced labor, wage theft, ethical sourcing |
| Tax & Financial Transparency | 15% | Country‑by‑country reporting, tax haven use |
| Environmental Compliance | 5% | Environmental fines, land conflicts, resource depletion |
4.2 Government Indicators
| Indicator Category | Weight | Description |
|---|---|---|
| Procurement Integrity | 25% | Sole‑source contracts, bid rigging, documented waste/fraud |
| Regulatory Capture | 20% | Revolving door, undisclosed industry meetings |
| Financial Transparency | 20% | Audit findings, budget disclosure, unexplained expenditures |
| Anti‑Corruption Enforcement | 15% | Investigations, sanctions, prosecutions |
| Whistleblower Protection | 10% | Legal framework, documented retaliation |
| Access to Information | 10% | FOI response time, appeal success rate |
4.3 Risk Categories
| Score Range | Category | Interpretation |
|---|---|---|
| 85–100 | Low Risk | Strong governance indicators; minimal documented misconduct |
| 70–84 | Moderate Risk | Mixed governance indicators; some concerns |
| 50–69 | Elevated Risk | Significant governance concerns; documented issues |
| <50 | High Risk | Severe governance concerns; chronic issues or severe opacity |
Entities with insufficient data receive a “Limited Data” flag and are categorized as High Risk with a notation that the score reflects data scarcity rather than confirmed misconduct.
5. Data Sources
The IITI relies exclusively on publicly available, verifiable data sources. Examples by jurisdiction:
| Jurisdiction | Corporate Sources | Government Sources |
|---|---|---|
| Thailand | SET filings, DBD, OCCRP | NACC, SAO, OIC, G‑Procurement |
| Hong Kong | HKEX, Companies Registry | ICAC, Audit Commission, FOI logs |
| Singapore | SGX, ACRA | CPIB, AGO, EDB, FOI logs |
| United States | SEC EDGAR, DOJ, EPA | FPDS, USAspending, GAO, OpenSecrets |
| China | HKEX (H‑shares), OFAC, OCCRP | CCDI (limited), World Bank sanctions |
| Laos | OCCRP, World Bank (limited) | OCCRP, FATF grey list findings |
Data Quality Ratings: Each score includes a data quality flag (High / Medium / Low / Insufficient). Limited disclosure is noted but not equated with misconduct.
6. Methodological Validation
6.1 Inter‑Rater Reliability
A subset of 20 entities was independently scored by three reviewers. Inter‑rater agreement was assessed using Fleiss’ kappa (κ = 0.82, substantial agreement). Inter‑rater reliability will be periodically reassessed as the methodology evolves.
6.2 Sensitivity Testing
Pillar weights were adjusted ±10% across 100 iterations. Entity rankings remained stable (rank correlation ρ > 0.90), indicating that the overall scoring framework is not overly sensitive to weight selection.
6.3 External Benchmarking
Future validation will assess the IITI against external benchmarks, including:
- Transparency International Corruption Perceptions Index (country‑level)
- World Bank Worldwide Governance Indicators
- RepRisk ESG controversy scores
- Regulatory enforcement actions (post‑hoc)
- Procurement fraud investigations
6.4 Predictive Validity (Proposed)
Future research will examine whether low‑scoring entities experience higher rates of regulatory intervention, litigation, corruption findings, procurement irregularities, or financial distress. This paper does not claim predictive validity.
7. Illustrative Case Study
To illustrate the methodology, we present one corporate and one government entity from the Thailand pilot.
7.1 Corporate Example: Advanced Info Service PCL (Thailand)
| Indicator | Score | Basis |
|---|---|---|
| Governance | 92 | Full ownership disclosure, independent board |
| Legal Compliance | 88 | No material fines or sanctions |
| Supply Chain | 85 | Ethical sourcing policy disclosed |
| Tax Transparency | 78 | Country‑by‑country reporting available |
| Environmental | 90 | No environmental fines |
| Final Score | 87 (Low Risk) |
7.2 Government Example: Ministry of Transport (Thailand)
| Indicator | Score | Basis |
|---|---|---|
| Procurement Integrity | 45 | Multiple sole‑source contracts; documented complaints |
| Regulatory Capture | 50 | Revolving door disclosures partial |
| Financial Transparency | 55 | Audit findings present |
| Anti‑Corruption | 40 | Documented investigations |
| Whistleblower Protection | 35 | Limited legal framework |
| Access to Information | 48 | Slow FOI responses |
| Final Score | 46 (High Risk) |
These scores are illustrative. Full entity scores are available on the public dashboard.
8. Technical Architecture (Summary)
| Component | Technology | Purpose |
|---|---|---|
| Data ingestion | Python (Scrapy, Pandas) | Weekly collection from public sources |
| Scoring engine | Python + Pandas | Indicator calculation, score aggregation |
| Database | PostgreSQL | Entity data, historical scores |
| API | Node.js / Express | Serve scores to dashboard and external users |
| Dashboard | React / Next.js | Public rankings, filters, detail pages |
| Authentication | Native (Base44) | User accounts for premium access |
| Payments | Stripe | Subscription processing ($9/month or $90/year) |
Certain implementation details (exact data source endpoints, weight micro‑adjustments, code optimizations) are omitted because they are operational rather than methodological. The conceptual framework, indicator categories, and scoring logic are fully disclosed to support transparency and replication.
9. Access and Sustainability
| Tier | Price | Access |
|---|---|---|
| Public (free) | $0 | Top 5 highest‑scoring entities (all jurisdictions) |
| Premium | $9/month or $90/year | All 199+ entities, full history, CSV, API, alerts |
| Voucher | $0 (journalists, researchers) | Full premium access, subsidized by paid subscriptions |
The voucher system ensures that governance researchers and investigative journalists are not excluded by cost.
10. Limitations
The IITI relies primarily on publicly available information and therefore may:
- Underestimate risks in opaque jurisdictions
- Reflect reporting biases in media ecosystems
- Lag emerging misconduct not yet publicly documented
- Reward disclosure rather than actual integrity
- Be influenced by differences in legal and regulatory frameworks across jurisdictions
Accordingly, IITI scores should be interpreted as indicators of transparency and governance risk rather than definitive measures of organizational conduct.
Additional methodological limitations include:
- Public data bias: Entities with more disclosures may appear worse.
- Jurisdictional bias: Countries differ in reporting quality.
- Reporting lag: Public enforcement data often trails misconduct by years.
- Survivorship bias: Large entities leave more public footprints.
These limitations are inherent to any transparency‑based governance assessment. They do not invalidate the approach but require careful interpretation.
11. Future Work
| Phase | Timeline | Activities |
|---|---|---|
| Phase 3 | Q3 2026 | Expand corporate US to 100+ companies; add Vietnam, Malaysia, Indonesia |
| Phase 4 | Q4 2026 | Government EU coverage; independent academic validation; predictive validity study |
| Phase 5 | 2027 | Prospective validation study; insurance pilot; certification program |
12. Conclusion
The Institutional Integrity and Transparency Index (IITI) provides a live, replicable governance risk assessment system for corporate and government entities. It operationalizes institutional integrity, grounds governance risk in existing literature, reports early validation results, and offers a transparent, repeatable methodology. The IITI is not a campaign. It is a transparency instrument.
The objective is not to determine guilt or innocence, but to provide a transparent, repeatable framework for assessing institutional integrity risk using publicly available information.
13. References
- Berg, F., Kölbel, J. F., & Rigobon, R. (2022). Aggregate confusion: The divergence of ESG ratings. Review of Finance, 26(6), 1315–1344.
- Kaufmann, D., Kraay, A., & Mastruzzi, M. (2010). The Worldwide Governance Indicators: Methodology and analytical issues. World Bank Policy Research Working Paper No. 5430.
- Klitgaard, R. (1998). Controlling corruption. University of California Press.
- Transparency International. (2025). Corruption Perceptions Index 2025.
- Veil, N., & Dauch, L. (2026). The Coherence Stack: From Individual Practice to Market Mirror. ACI/SII Implementation Report.
Correspondence: Nathan Veil, Applied Coherence Institute. consulting@appliedcoherenceinstitute.org
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