TABLE OF CONTENTS
- How Fuzziness Works (Typo Matching)
- What the Fuzziness Percentage (%) Controls
- 0% Fuzziness vs Exact Match
- Key Takeaways
What is Fuzziness?
Fuzziness will match entities with names that have an inserted, omitted or replaced character compared to the name you screened. Fuzziness allows up to one character difference for each word in the search term.
Fuzziness is a matching technique that enables us to return matches when there are small variations between the spelling of your customer's name and the names referenced in the risk lists and media. Fuzziness is sometimes referred to as edit distance or Levenshtein distance. Our Match algorithm uses fuzziness alongside other techniques to match names
Fuzziness is useful in two main scenarios:
1. The customer name has been manually entered and may contain typos or spelling mistakes
2. The customer name has been transliterated into Latin script from a non-Latin script, or is written in a different script compared to a risk list or media article.
By default, our matching algorithm uses fuzziness only for the second of these scenarios: matching transliteration variants of names. This means that, by default, fuzzy name matches are only returned when the searched and matched name words are broadly phonetically equivalent (using an industry standard phonetic algorithm).
Configuration options are available to change this default behaviour such that the first scenario (typos and spelling mistakes) may also generate matches.
Nicknames and Equivalent Names
Our system is designed to recognise common short forms and equivalent names. This means names like Steven vs Steve or Charlie vs Charles are matched because the system understands they refer to the same person.
- These matches are based on built-in recognition of name equivalents (also called hypocorisms).
- They are not just treated as typos – even when the spellings are quite different, the system knows they are related and will return a match.
How Fuzziness Works (Typo Matching)
Fuzziness is used to find matches when there are small spelling differences, such as typos or phonetic variations. This is also called edit distance.
Golden Rule of Fuzziness:
- Only one character difference per word is allowed.
- The difference can be:
- Inserted (Amiya into Aamiyah)
- Omitted (Amiya into Amia)
- Replaced (Amiya into Amiua)
We cap fuzziness at one character difference per word because:
- It catches the majority of typing mistakes.
- It prevents too many false matches (false positives).
| Fuzziness Setting | Minimum word length to allow fuzziness |
| 0% | None (no fuzziness allowed) |
| 10% | 25 |
| 20% | 13 |
| 30% | 9 |
| 40% | 7 |
| 50% | 5 |
| 60% | 5 |
| 70% | 4 |
| 80% | 4 |
| 90% | 3 |
| 100% | 3 |
What the Fuzziness Percentage (%) Controls
The percentage does not allow multiple character changes. Instead, it controls the minimum word length required before the one-character difference is accepted.
| Fuzziness Setting | Minimum Word Length for Fuzziness |
|---|---|
| 90% or 100% | 3 letters or more |
| 50% or 60% | 5 letters or more |
| 0% | One-character difference may still be allowed, depending on the word length |
Example:
- With fuzziness set to 90%, searching for Amiya may also return Aamiyah or Aamiya.
- With fuzziness set to 0%, a one-character mismatch may still be accepted in some cases.
Tip: Use higher fuzziness (e.g., 90%) when names are prone to typos or manual entry errors. Use lower fuzziness when you want stricter control.
0% Fuzziness vs Exact Match
It is important to distinguish between 0% fuzziness and Exact Match.
- 0% fuzziness: May still allow for a one-character mismatch in certain cases.
- Exact Match: A stricter setting that must be requested through Support or your Customer Success Manager (CSM).
With Exact Match:
- No character mismatches are allowed.
- Nicknames, equivalents, and aliases (e.g., Charles vs Charlie) are not matched.
- Phonetic (sound-alike) matches are not allowed.
- Honorifics (Mr, Ms, Dr) must match exactly.
- Extra words in a name are not allowed (John Smith will not match John Williams Smith).
- The one-year flexibility in date of birth matching is disabled.
Key Takeaways
- Nicknames and equivalents are matched automatically – not just through fuzziness.
- Fuzziness allows for one-character differences per word to catch common spelling mistakes.
- The fuzziness percentage controls how long a word must be before this rule applies.
- 0% fuzziness may still allow a one-character mismatch.
- Exact Match must be enabled through Support or your CSM and is the strictest setting – it does not allow any mismatches and may miss nicknames and aliases.