

Legal Name Normalization
Overview
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FAQ
Why is normalization essential?
Raw names vary widely; normalization reduces superficial differences so true matches surface and noisy false positives drop, speeding compliance decisions.
What techniques are typical?
Case folding, punctuation removal, suffix handling, token reordering, phonetics, and locale-aware transliteration combined with weighted attribute matching.
How do we avoid over-merging?
Pair normalized names with strong identifiers (DOB, LEI/EIN). Use score thresholds and human review for gray-zone matches to prevent incorrect consolidation.
What about multilingual data?
Build locale-specific rules and transliteration tables. Test against real datasets and maintain exceptions for regulated naming requirements.