Geographic Risk Intelligence
for AML & Fraud
Real-time API delivering ML-driven risk scores, geospatial analytics, and cross-attribute anomaly detection across 41,000+ US zip codes.
Four products. One API.
Choose what you need — from core AML risk factors to fully customizable scoring.
GeoAML
Eight ML-driven risk factors including HIDTA, HIFCA, GTO, drug trafficking, industry risk, international nexus, and trade-based money laundering — scored at the zip code level.
GeoDemographic
Population-level risk enrichment including median age, income, education, and elderly concentration — with a 5-tier elder abuse risk classification.
GeoExtend
Additional enrichment layers: CBSA classifications, neighborhood data, NAICS industry statistics, and curated gang territory mapping across all 50 states.
GeoDynamic
Fully configurable risk scoring. Override default risk weights to match your institution's risk appetite and regulatory posture.
Know Your Geography
Send a transaction or entity. Get back enriched risk intelligence in real time.
1. Collect
1B+ data points from government, financial, and proprietary sources
2. Normalize & Aggregate
Standardize across zip, county, CBSA, state, and country layers
3. Feature Engineering
Select and transform predictive features for ML models
4. Machine Learning
Train models for drug trafficking, industry risk, and anomaly detection
5. Risk Indicators
Return scored, tiered risk levels via API or data file delivery
// Enriched response (simplified) { "mainZipIsHIDTA": true, "mainZipHIDTARegionName": "NY/NJ", "mainZipDrugTraffickingRiskLevel": 4, "mainZipNaicsStatsRiskLevel": 3, "mainZipGeographicAMLRiskScore": 78.4, "mainZipElderlyCategory": "4-Hgh", "mainZipMilesFromSWB": 1842.3, // Geo Analytics "mainZipToPhoneStateMatch": false, "mainZipToPhoneDistanceInMiles": 412.7, "mainZipToIPStateCdMatch": false, "mainZipToIPDistance": 893.1, // Counterparty FI "counterPartyFIName": "First National", "counterPartyBranchesClosestDistanceMiles": 247.8, "counterPartyToFIStateCdMatch": false }
Built for the full financial crime lifecycle
From onboarding to transaction monitoring to investigations.
CDD & Risk Rating
Enrich customer profiles at onboarding with zip-level AML risk scores, industry concentrations, and demographic risk factors for proportionate due diligence.
Transaction Monitoring
Feed geographic risk scores and cross-attribute anomalies (address vs. phone vs. IP vs. branch) into your TMS rules and models as predictive features.
Banking Out of Jurisdiction
Detect when counterparties bank far from their stated address using branch proximity analysis and routing number enrichment.
Elder Abuse Detection
Flag incoming payments to high elderly-concentration zip codes with 5-tier risk classification for targeted monitoring of vulnerable populations.
Fraud & Scam Classification
Classify transactions using authorized/unauthorized fraud taxonomy with scam subcategories — romance, investment, government impersonation, and more.
New Location Risk Assessment
Evaluate geographic risk before opening new branches, onboarding merchant portfolios, or expanding into new markets.
Measurable results from day one
Geographic enrichment replaces manual analyst lookups and binary risk flags with ML-driven, zip-code-level intelligence.
Fewer false positive alerts
Automated NAICS prediction replaces manual industry verification on transaction alerts.
Granularity over binary flags
ML risk scoring at zip-code level replaces county-wide HIDTA designations.
API enrichment
Onboarding reduced from weeks of manual lookups to milliseconds per request.
Ready to enrich your risk data?
Get started with a demo or explore the full API documentation.