Data-driven analysis of regulatory signals, compliance, and risk indicators across 53 government sources.
| Rank | Source | Signals |
|---|---|---|
| 1 | Ch Officers | 22,449,602 |
| 2 | Ch Psc | 11,897,682 |
| 3 | Ch Accounts | 6,074,386 |
| 4 | Ch Mortgages | 2,493,063 |
| 5 | Dns Whois | 2,059,305 |
| 6 | Land Registry | 687,373 |
| 7 | Ico | 600,000 |
| 8 | Uktradeinfo Bulk | 399,244 |
| 9 | Payment Practices | 388,425 |
| 10 | Fsa | 380,551 |
| 11 | Gazette | 330,578 |
| 12 | Charity Commission | 272,572 |
| 13 | Ch Gazette Bulk | 269,224 |
| 14 | Contracts Finder | 202,987 |
| 15 | Gtr | 180,059 |
BORSCH.AI aggregates data from 53 government and regulatory sources to provide a comprehensive risk picture. The largest signal volume comes from Companies House filings (appointments, PSC, accounts, mortgages), followed by property data (Land Registry) and financial regulators (FCA, ICO).
Our multi-dimensional risk scoring system (Risk Score v2) evaluates companies across 5 dimensions: Financial Health, Compliance, Governance, Network Risk, and Operational Quality. Each dimension draws from multiple sources to avoid single-source bias.
Critical risk indicators include active sanctions matches, disqualified directors, winding-up petitions, and liquidation proceedings — all verified through cross-referencing with date-of-birth data to eliminate false positives.
Sources include Companies House (appointments, PSC, accounts, mortgages, gazette), FCA, Land Registry, ICO, CQC, HMRC AML, Gender Pay Gap, Modern Slavery Registry, UK Sanctions, OpenSanctions, GLEIF, and many more.
Risk Score v2 evaluates companies across 5 dimensions: Financial Health (32%), Compliance (23%), Governance (15%), Network Risk (15%), and Operational Quality (15%). Each dimension draws from multiple data sources to avoid single-source bias.
Critical signals include active sanctions matches, disqualified directors, winding-up petitions, and liquidation proceedings. All person-based matches are verified through date-of-birth cross-referencing to eliminate false positives.