Logistics organization processing hundreds of thousands of declarations daily
Import/export transactions requiring rapid security screening
Customs platform handling complex trade data flows
Enhance rules engine with AI to catch subtle risks in clean traffic
"No Risk" auto-classification hid dangerous shipments
New routes, product mixes evaded static rules
No capability for nuanced data pattern detection
Analysts drowned in false positives and volume
Couldn't adapt to evolving trade complexity
IQR flags extreme values by port/product norms
Isolation forests + XGBoost for pattern anomalies
Shows which fields drove each risk score
Combines model outputs for severity classification
Web dashboard for transaction exploration
Enhances without replacing existing logic
Data processing, statistical checks, ML workflows
Outlier detection across business variables
Supervised/unsupervised anomaly detection
Web exploration of flagged transactions
Voting/scoring for risk prioritization
Stats to ML integration and validation
Flagged 0.6-0.8% high-risk from 500K transactions
Reduced low-value alerts through model aggregation
Highlighted key variables driving anomalies
Prioritized genuine cases over noise
Adapts to growing volumes and trade patterns
Captures issues rules engine misses
Legitimate trade flows without delays
Guides policy refinement and deep checks
Focus shifts to genuine investigations
Handles growing declaration complexity
You’re one step away from building great software. This case study will help you learn more about how Simform helps successful companies extend their tech teams.
Discover cutting-edge ideas and insights from the world of technology and business.
You’re one step away from building great software. This case study will help you learn more about how Simform helps successful companies extend their tech teams.
