Moody’s · Financial services · Dynamo
Name screening that holds up across spellings and transliterations
Moody’s analysts screen names from many sources, often spelled or transliterated in different ways.
| Area | Before | After |
|---|---|---|
| Spelling variants | Match quality dropped | Transliteration-aware matching |
| Ambiguous matches | Repeated checking | Grouped by confidence for analysts |
The problem
- Industry
- Financial services
- Location
- United States
Match quality dropped quickly as transliteration and spelling variation increased, which slowed risk-sensitive screening.
Analysts needed more precise search across many data sources, and scattered data made indicators hard to compare.
It had to run as white-label software inside large firms, and handle transliteration without hurting search quality or ease of use.
What we built
We designed matching that accounts for transliterations and aliases, and groups results by confidence.
We standardized data from different sources, so analysts compare indicators the same way each time.
We built screening flows that help analysts review potential matches, compare alternatives and move through high-volume queues.
We packaged the platform as a product other firms can license.
The result
Analysts now see ambiguous matches grouped by confidence, with less repeated checking.
Screening decisions now rest on structured results that are easier to explain. The white-label approach made the platform usable at larger institutions.
