FinCrimeRadar separates what a publication is for from how it is rendered. The intentionally small public taxonomy identifies Guide for deep explanation, Framework for assessment and decision support, Case File for investigation through evidence, Intelligence Brief for regulatory change, and Evidence Essay for contested analysis.
Guide and Evidence Essay are standing formats. Framework and Case File are currently experimental public formats, while Intelligence Brief remains a proposed format until it is separately tested. These labels use the existing Knowledge Hub treatment with only the compositions the subject needs, except for the established Evidence Essay treatment where examining the source chain is part of the reader's reasoning task. A format label does not create a separate site shell or template.
Existing publications are not being retrofitted merely to adopt the taxonomy. APP Scam Decision Framework is the first Framework publication under evaluation. Framework has not yet been permanently adopted, and its own second-instance evaluation remains open: rather than building a second Framework implementation, Experiment 02, Money Mule or Victim?, piloted the separate, previously proposed Case File format instead. If you have evidence about which presentation helps you work better, get in touch.
FinCrimeRadar's sanctions and PEP screening runs on data from OpenSanctions, an open-data project that consolidates sanctions lists, watchlists, and politically exposed persons data from official sources worldwide, OFAC's SDN list, UK OFSI's consolidated list, EU sanctions, UN Security Council designations, and dozens of national PEP registers, into a single structured dataset.
FinCrimeRadar does not compile, verify, or independently maintain sanctions or PEP data. The underlying data is OpenSanctions' work, sourced under a non-commercial API arrangement. Any question about the accuracy of a specific listing, designation date, or source attribution should go to OpenSanctions directly, not treated as something FinCrimeRadar has independently confirmed.
At last check, the screening tool draws on OpenSanctions' combined default collection, over 1.2 million risk entities globally, spanning sanctions designations, politically exposed persons, and related risk categories. We don't independently publish a breakdown by category, that split isn't exposed by the underlying data source in a way we can verify live. These figures change as OpenSanctions' own coverage grows and as designations are added or removed, they're a snapshot, not a fixed count.
Sanctions data is checked daily against the live OpenSanctions feed. New designations, delistings, amendments, and identifier changes are tracked and published as a daily changelog, visible in the weekly compliance digest and the site's delta tracking pages. This means the screening tool reflects the current state of the underlying data within a day of a change, not a static snapshot from whenever the tool was last manually updated.
Name screening uses fuzzy matching, comparing the searched name against records in the dataset for close matches, not just exact string matches. This is deliberate: sanctioned individuals and entities appear under multiple spellings, transliterations, and aliases, and exact-match-only screening misses genuine hits. The tradeoff is that fuzzy matching also surfaces false positives, matches that share a name pattern but are a different person entirely.
The matching threshold is adjustable in the tool itself, a lower threshold surfaces more potential matches at the cost of more false positives, a higher threshold narrows results but risks missing a genuine hit with an unusual spelling. There's no single correct setting, it depends on risk appetite and the specific use case, which is why the threshold is user-controlled rather than fixed.
Alongside sanctions and PEP matching, the tool runs a lightweight adverse media check: an automated keyword search of recent English-language news sources for the name you enter, limited to roughly the last 12 months. Each result is scored for relevance and tone, so the more clearly negative and on-topic articles surface first.
What this is not. This is an automated news-keyword search, not a curated or comprehensive negative-news product. It has real limitations worth understanding:
Treat it as a fast first-pass indicator for learning and triage, not as a substitute for a full adverse-media screening solution in a regulated firm.
FinCrimeRadar exists because genuinely useful compliance tooling and reference material shouldn't sit behind a training budget or an enterprise sales process. The tradeoff for that is stated plainly above: this is a decision-support and learning tool, not a substitute for a firm's licensed, auditable screening infrastructure. Full detail on how the site is funded is on the Editorial Standards page.