Risk Scoring Methodology
Transparent, data-driven corruption risk assessment
Important Disclaimer
Risk scores are statistical indicators based on publicly available data patterns. A high score does not indicate wrongdoing—it identifies entities whose data patterns warrant closer examination. All data is sourced from official government registries. Conclusions should be independently verified before taking any action.
How Scores Are Calculated
Each entity receives a score from 0 to 100 based on four weighted categories. The total score determines the risk level:
70-100
High Risk
40-69
Medium Risk
0-39
Low Risk
Risk Categories
Political Connection
max 30 pointsEvaluates relationships between entities and political figures, parties, or donors.
| Indicator | Points | Description |
|---|---|---|
| Owner is current/former politician | +10 | Direct ownership by elected officials or political appointees |
| Family member of politician | +8 | Ownership by spouse, children, or close relatives of politicians |
| Political party donor | +5 | Entity or owners have made significant political donations |
| Political network connections | +1-4 | Number of connections to politically exposed persons |
| Shared address with political entity | +3 | Registered at same address as political organization |
Contract Anomaly
max 30 pointsAnalyzes patterns in government contracts that may indicate bid rigging or corruption.
| Indicator | Points | Description |
|---|---|---|
| Single-bidder contracts >50% | +10 | Majority of contracts won without competitive bidding |
| Single-bidder contracts >30% | +5 | Elevated rate of non-competitive contract awards |
| Threshold gaming | +2 each (max 8) | Contract values suspiciously close to reporting thresholds (85-100%) |
| Emergency contracts >30% | +3 | High proportion of no-bid emergency procurement |
Corporate Structure
max 25 pointsIdentifies shell company indicators and complex ownership structures designed to obscure beneficial owners.
| Indicator | Points | Description |
|---|---|---|
| Offshore jurisdiction in ownership | +10 | Owners registered in tax havens or secrecy jurisdictions |
| Suspicious founding timing | +8 | Company created less than 6 months before first major contract |
| Circular ownership detected | +5 | Ownership structures where entities own each other |
| Frequent ownership changes | +3 | More than 2 ownership changes per year |
Financial Health
max 15 pointsDetects financial anomalies that may indicate invoice padding, money laundering, or shell operations.
| Indicator | Points | Description |
|---|---|---|
| Revenue per employee >€400K | +8 | Unusually high revenue relative to workforce size |
| Missing financial statements | +5 | Required annual filings not submitted to registry |
| Asset/revenue inconsistency | +3 | Asset values inconsistent with reported business operations |
Risk Flags
When specific thresholds are crossed, the system generates explicit flags to highlight areas of concern:
| Flag Code | Severity | Description | Evidence |
|---|---|---|---|
POLITICIAN_OWNER | critical | Owner is a current or former politician | Direct ownership stake by politically exposed person |
OFFSHORE_OWNERSHIP | high | Ownership chain includes offshore jurisdiction | Beneficial owner registered in secrecy jurisdiction |
SINGLE_BIDDER | medium | Majority of contracts won without competition | Over 50% of contracts awarded as single-bidder |
THRESHOLD_GAMING | medium | Contract values cluster below reporting thresholds | Pattern of contracts at 85-99% of disclosure limits |
SHELL_INDICATORS | high | Multiple shell company indicators detected | No employees, virtual office, nominee directors |
MISSING_FINANCIALS | low | Required financial statements not filed | Annual accounts overdue or missing from registry |
Offshore Jurisdictions
The following jurisdictions are flagged when detected in ownership chains. These are commonly used for legitimate tax planning but also for obscuring beneficial ownership:
Historical Fraud Case Scoring
For documented fraud cases in our database, we use a pattern-based scoring system that analyzes the type of fraud, estimated damage, and case status:
Pattern Categories
political_bribery, nepotism, conflict_of_interest, abuse_of_office
bid_rigging, overpricing, kickback_scheme, single_bidder
shell_company, offshore_tunneling, hidden_ownership
accounting_fraud, vat_fraud, grant_fraud, money_laundering
Damage Multipliers
Status Bonuses
Data Sources
All data is sourced from official government registries. Each entity links directly to its original source for verification:
Slovakia
Czech Republic
Poland
Hungary
Austria
Germany
United Kingdom
Limitations
- 1Data completeness: Some registries have gaps or delays in reporting. Missing data does not necessarily indicate wrongdoing.
- 2Historical accuracy: Data reflects current registry state. Historical ownership or contracts may not be fully captured.
- 3False positives: Legitimate business practices can trigger high scores. Large construction companies naturally have many contracts.
- 4Jurisdiction differences: Reporting requirements vary by country. Cross-border comparisons should account for regulatory differences.
- 5No legal conclusions: This platform is for research purposes. It does not make legal determinations about corruption or fraud.
Open Source & Verifiable
Raanko is fully open source. The scoring algorithms, data processing logic, and all code can be inspected, audited, and improved by anyone.
View source code on GitHub