data_entry_ops · finance · workflow
super.AI disambiguates merchant names at 99%+ accuracy for global payment network operator
One of the world's largest payment network operators struggled to resolve merchant names from unclear billing descriptions at scale, facing constantly changing merchant data, tens of millions of merchants, hundreds of billions of transactions annually, and data obscured by aggregators and third-party payment solutions.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · Unclear billing descriptor received
Unclear billing descriptions from transactions are submitted for merchant name disambiguation.
Outcome
The company achieved 99%+ accurate merchant name disambiguation with 99.7% process automation, processing up to 8.3M records hourly with zero coding required.
Results
Time saved8.3M
Volume99%+
Grounding & classification
Source type: vendor customer story
19 fields verified against source quotes, 1 dropped as unverifiable.
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