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Analytics · Customs Brokers

HTS classification accuracy analytics

A broker surfaced classification patterns and exceptions to reduce reclassifications and the penalties that follow them.

Microsoft FabricPower BIAzure SQLDAX measures
Reclassifications
-27%
illustrative
Entries analyzed
180k
historical
Error patterns
Flagged
pre-filing
Exposure
Reduced
penalty risk

Illustrative scenario · example figures

The challenge

Classification quality varied by filer and client, and errors only surfaced when customs pushed back, by which point a shipment was held or a penalty was in play.

What we built

We analyzed historical entries to flag inconsistent HTS usage for similar goods, classification changes over time, and clients with elevated exception rates.

  • Consistency analysis of HTS codes used for similar goods.
  • Reclassification and rejection rates by filer and client.
  • An early-warning list of entries that match known error patterns.

Outcomes

  • Inconsistent classifications are caught before filing, not after a hold.
  • Training focuses on the filers and goods that need it.
  • Penalty and reclassification exposure falls.

Where the data came from

Broker filing systemACE / ABIHTS schedulesHistorical entries

Data is drawn from the systems the operation already runs on and delivered in the client’s own tenant.

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