Match Scores Explained
TradeLasso uses fuzzy string matching to find near-matches. This page explains how the score is calculated and what thresholds are appropriate for compliance work.
What is fuzzy matching?
Exact-name matching fails in compliance screening. Sanctioned entities frequently appear on lists under multiple spellings, transliterations, or abbreviated names — and real exporters often have incomplete or slightly misspelled counterparty names in their records.
Fuzzy matching compares two strings and calculates how similar they are, even if they are not identical. TradeLasso uses this approach to surface near-matches that an exact search would miss.
The match score scale
| Score range | Interpretation | Recommended action |
|---|---|---|
| 95 – 100 | Extremely high confidence. The names are identical or differ only in punctuation or spacing. | Treat as a definite match. Verify using address and other identifiers before proceeding. |
| 85 – 94 | High confidence. Very close name match — likely the same entity or a known alias. | Review carefully. Compare address, country, and alternate names. |
| 80 – 84 | Probable match. Names are similar but have meaningful differences. | Review and document your determination. False positives are possible. |
| 70 – 79 | Possible match. Names share significant overlap but differences are notable. | Likely a false positive, but review context before dismissing. |
| Below 70 | Low similarity. Not shown in standard results. | Not displayed by default. |
What threshold should I use?
Note
TradeLasso defaults to showing results at 80 and above. This is the threshold most widely used by export compliance professionals as a reasonable balance between catching real matches and minimizing false-positive workload.
Depending on your risk tolerance and transaction type, you may want to adjust:
- High-risk transactions (large value, sensitive technology, unfamiliar counterparty): consider reviewing results starting from 70 to reduce the risk of missing a near-match
- Routine vendor screening: the default threshold of 80is appropriate for most use cases
- High-volume batch screening: a threshold of 85+ reduces the manual review workload while still catching high-confidence matches
Why does the same name sometimes produce different scores?
The match score reflects the similarity between your input and the name as it appears on the government list — not against all possible variations of the listed entity's name. If a sanctioned entity is listed as "Rostam Azizi" but you search for "R. Azizi", the score will be lower than if you search the full name. This is why searching name variations matters.
Scores in batch screening
In Batch Screening, each row in your CSV is individually scored. You can use thefuzzy slider in the results view to filter out rows below a chosen threshold. This is useful when processing large files and you want to focus manual review on higher-confidence matches first.