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Analytics · Customs Brokers

ACE filing error and rejection analytics

A broker analyzed ACE rejections to find the recurring causes and cut the rework that slowed clearance.

Microsoft FabricPower BIAzure Data FactoryDAX measures
Rejections
-34%
illustrative
Causes
Categorized
and ranked
Rework
Reduced
at clearance
Monitoring
Continuous
with trend

Illustrative scenario · example figures

The challenge

ACE rejections were handled one at a time with no view of the patterns, so the same avoidable errors kept returning and quietly added days to clearance.

What we built

We categorized rejection messages and tied them to filer, client, and entry type, surfacing the handful of causes behind most of the rework.

  • Rejection categorization by message, filer, and client.
  • Pareto of the causes behind most rejections.
  • A trend view that confirms whether fixes are working.

Outcomes

  • The few causes behind most rejections are named and fixed.
  • Rework and the delay it adds to clearance both fall.
  • Filing quality is monitored instead of assumed.

Where the data came from

ACE / ABIBroker filing systemRejection logsEntry master

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

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