AML Search Templates

Save and reuse common AML screening configurations for different customer types, risk levels, and regulatory requirements.

AML Search Templates

Create reusable search templates to standardise AML screening across your organisation, ensure compliance, and save time on repetitive configurations.

What are AML Templates?

AML Templates are pre-configured search profiles that define:

  • Which categories to search (sanctions, PEP, adverse media)
  • Match confidence thresholds
  • Date ranges for adverse media
  • Required vs. optional fields
  • Auto-decisioning rules

Consistency & Compliance

Templates ensure every team member screens customers the same way, meeting your compliance policies and regulatory requirements consistently.

Pre-Built Templates

VeriPlus includes 5 standard templates:

1. Quick Sanctions Check

Use Case: Low-risk customers, small transactions

{
  "name": "Quick Sanctions Check",
  "categories": ["sanctions"],
  "matchThreshold": 90,
  "autoApprove": {
    "noHits": true
  },
  "cost": 1
}

When to Use:

  • Transaction value < $1,000
  • Low-risk countries
  • Existing customers (periodic re-screening)
  • Non-regulated industries

2. Standard KYC

Use Case: Most customer onboarding scenarios

{
  "name": "Standard KYC",
  "categories": ["sanctions", "pep"],
  "matchThreshold": 85,
  "autoApprove": {
    "noHits": true,
    "lowRiskPEP": false // Manual review for any PEP
  },
  "cost": 3
}

When to Use:

  • General customer onboarding
  • Mid-value transactions ($1,000 - $10,000)
  • Most jurisdictions
  • Regulatory compliance requirement

3. Enhanced Due Diligence

Use Case: High-risk customers

{
  "name": "Enhanced Due Diligence",
  "categories": ["sanctions", "pep", "adverse_media"],
  "matchThreshold": 75, // Lower threshold = catch more
  "adverseMedia": {
    "dateRange": {
      "from": "2015-01-01" // Last 10 years
    },
    "relevanceThreshold": 70
  },
  "autoApprove": {
    "enabled": false // Always manual review
  },
  "cost": 5
}

When to Use:

  • High-value transactions (>$10,000)
  • PEPs and their relatives
  • High-risk countries (FATF watchlist)
  • Crypto exchanges
  • Large cash transactions

4. PEP Focus

Use Case: When PEP screening is primary concern

{
  "name": "PEP Focus",
  "categories": ["pep", "sanctions"],
  "matchThreshold": 70,
  "includeRCA": true, // Relatives and Close Associates
  "includeFormerPEPs": true,
  "pepRiskLevels": ["high", "medium", "low"],
  "cost": 3
}

When to Use:

  • Political donations
  • Government contractors
  • Luxury goods sales
  • Real estate transactions

5. Ongoing Monitoring

Use Case: Periodic re-screening of existing customers

{
  "name": "Ongoing Monitoring",
  "categories": ["sanctions", "pep", "adverse_media"],
  "matchThreshold": 85,
  "adverseMedia": {
    "dateRange": {
      "from": "{{lastScreeningDate}}" // Only new articles since last check
    }
  },
  "alertOnChange": true,
  "cost": 3
}

When to Use:

  • Annual customer reviews
  • Quarterly PEP monitoring
  • Event-triggered re-screening
  • Regulatory requirement

Creating Custom Templates

Template Builder

POST /api/v3/aml/templates
 
{
  "name": "Crypto Exchange KYC",
  "description": "For cryptocurrency exchange customer onboarding",
  "categories": ["sanctions", "pep", "adverse_media"],
  "matchThreshold": 85,
  "requiredFields": ["fullName", "dateOfBirth", "country"],
  "optionalFields": ["address", "passport"],
  "adverseMedia": {
    "dateRange": {
      "from": "2018-01-01" // Crypto boom era
    },
    "relevanceThreshold": 75,
    "topics": ["fraud", "money_laundering", "sanctions_violation", "crypto_crime"]
  },
  "autoDecision": {
    "autoApprove": {
      "enabled": true,
      "conditions": {
        "sanctionsHits": 0,
        "pepHits": 0,
        "adverseMediaHits": 0
      }
    },
    "autoReject": {
      "enabled": true,
      "conditions": {
        "sanctionsHits": "> 0",
        "OR": {
          "adverseMedia": {
            "topics": ["sanctions_violation", "terrorism_financing"]
          }
        }
      }
    }
  },
  "notifications": {
    "email": ["[email protected]"],
    "webhook": "https://api.example.com/aml-webhook"
  }
}

Template Fields

FieldTypeDescription
namestringTemplate display name
descriptionstringPurpose and use case
categoriesarraysanctions, pep, adverse_media
matchThresholdnumber0-100, match confidence level
requiredFieldsarrayMust be provided for search
optionalFieldsarrayImproves matching if provided
autoDecisionobjectAuto-approve/reject rules
notificationsobjectAlert destinations

Industry-Specific Templates

Banking & Fintech

{
  "name": "Bank Account Opening",
  "categories": ["sanctions", "pep", "adverse_media"],
  "matchThreshold": 90,
  "adverseMedia": {
    "topics": ["fraud", "money_laundering", "embezzlement", "regulatory_action"]
  },
  "pepRiskAssessment": {
    "domestic": "medium",
    "foreign": "high",
    "internationalOrg": "low"
  },
  "requireManualReview": {
    "pepHit": true,
    "adverseMediaRelevance": "> 85"
  }
}

Cryptocurrency

{
  "name": "Crypto Exchange KYC",
  "categories": ["sanctions", "pep", "adverse_media"],
  "matchThreshold": 85,
  "adverseMedia": {
    "topics": ["crypto_fraud", "ransomware", "sanctions_evasion", "dark_web"]
  },
  "autoReject": {
    "sanctionsHits": "> 0",
    "adverseMedia": {
      "topics": ["terrorism_financing", "ransomware"]
    }
  },
  "additionalChecks": {
    "kytCrypto": true // Also check crypto wallet if provided
  }
}

Real Estate

{
  "name": "Property Purchase",
  "categories": ["pep", "sanctions", "adverse_media"],
  "matchThreshold": 80,
  "pepFocus": {
    "includeRCA": true,
    "includeFormerPEPs": true,
    "pepRiskLevels": ["high", "medium"]
  },
  "adverseMedia": {
    "topics": ["corruption", "money_laundering", "proceeds_of_crime"]
  },
  "thresholdByValue": {
    "< 500000": { "categories": ["sanctions", "pep"] },
    ">= 500000": { "categories": ["sanctions", "pep", "adverse_media"] }
  }
}

Gaming & Gambling

{
  "name": "Casino Customer",
  "categories": ["sanctions", "adverse_media"],
  "matchThreshold": 85,
  "adverseMedia": {
    "topics": ["fraud", "money_laundering", "organized_crime"],
    "dateRange": { "from": "2019-01-01" } // Last 5 years
  },
  "enhancedDDTriggers": {
    "depositAmount": "> 10000",
    "adverseMediaHits": "> 0"
  }
}

Professional Services

{
  "name": "Legal/Accounting Client",
  "categories": ["sanctions", "pep", "adverse_media"],
  "matchThreshold": 85,
  "adverseMedia": {
    "topics": ["fraud", "tax_evasion", "corruption", "regulatory_action"]
  },
  "pepAssessment": {
    "focus": "corruption_risk"
  }
}

Risk-Based Templates

Low-Risk Customer

Criteria: Small transactions, established customer, low-risk country

{
  "name": "Low Risk - Basic",
  "categories": ["sanctions"],
  "matchThreshold": 95, // Very high threshold
  "frequency": "annual",
  "cost": 1
}

Medium-Risk Customer

Criteria: Standard customer, moderate transaction value

{
  "name": "Medium Risk - Standard",
  "categories": ["sanctions", "pep"],
  "matchThreshold": 85,
  "frequency": "semi_annual",
  "cost": 3
}

High-Risk Customer

Criteria: Large transactions, high-risk country, PEP

{
  "name": "High Risk - Enhanced",
  "categories": ["sanctions", "pep", "adverse_media"],
  "matchThreshold": 75,
  "frequency": "quarterly",
  "autoApprove": { "enabled": false },
  "cost": 5
}

Conditional Templates

Apply different templates based on customer attributes:

function selectAMLTemplate(customer, transaction) {
  // High-risk country
  if (HIGH_RISK_COUNTRIES.includes(customer.country)) {
    return 'enhanced_due_diligence';
  }
 
  // Large transaction
  if (transaction.value >= 10000) {
    return 'enhanced_due_diligence';
  }
 
  // PEP (from previous screening or self-declaration)
  if (customer.isPEP) {
    return 'pep_focus';
  }
 
  // Crypto-related
  if (customer.businessType === 'cryptocurrency') {
    return 'crypto_exchange_kyc';
  }
 
  // Default
  return 'standard_kyc';
}

Template Variables

Use variables for dynamic searches:

{
  "name": "Dynamic Customer Search",
  "categories": ["sanctions", "pep"],
  "search": {
    "fullName": "{{customer.fullName}}",
    "dateOfBirth": "{{customer.dob}}",
    "country": "{{customer.nationality}}",
    "aliases": "{{customer.aliases}}" // Optional
  },
  "adverseMedia": {
    "dateRange": {
      "from": "{{lastScreeningDate}}",
      "to": "{{currentDate}}"
    }
  }
}

Available Variables:

  • {{customer.*}} - Any customer field
  • {{transaction.value}} - Transaction amount
  • {{lastScreeningDate}} - Last AML check date
  • {{currentDate}} - Today
  • {{companyPolicy.*}} - Your policy settings

Auto-Decisioning Rules

Auto-Approve

{
  "autoApprove": {
    "enabled": true,
    "conditions": {
      "ALL": [
        { "sanctionsHits": 0 },
        { "pepHits": 0 },
        { "adverseMediaHits": 0 }
      ]
    },
    "actions": {
      "setStatus": "approved",
      "notify": false // Don't send notification for clean results
    }
  }
}

Auto-Reject

{
  "autoReject": {
    "enabled": true,
    "conditions": {
      "ANY": [
        { "sanctionsHits": "> 0", "matchScore": ">= 90" },
        {
          "adverseMedia": {
            "topics": ["terrorism_financing", "sanctions_violation"],
            "relevanceScore": ">= 85"
          }
        }
      ]
    },
    "actions": {
      "setStatus": "rejected",
      "notify": ["compliance_team", "legal_team"],
      "blockCustomer": true
    }
  }
}

Manual Review

{
  "manualReview": {
    "triggerWhen": {
      "ANY": [
        { "pepHits": "> 0" },
        { "adverseMediaHits": "> 0", "relevanceScore": ">= 70" },
        { "sanctionsMatchScore": "70-90" } // Uncertain match
      ]
    },
    "actions": {
      "assignTo": "compliance_team",
      "priority": "high",
      "sla": 4 // hours
    }
  }
}

Template Analytics

Track template performance:

GET /api/v3/aml/templates/:id/analytics
 
{
  "template": "Standard KYC",
  "period": "last_30_days",
  "metrics": {
    "totalSearches": 1245,
    "autoApproved": 1102, // 88.5%
    "manualReview": 121, // 9.7%
    "autoRejected": 22, // 1.8%
    "averageCost": 3.0,
    "hitRates": {
      "sanctions": "0.8%",
      "pep": "3.2%",
      "adverseMedia": "5.1%"
    },
    "falsePositiveRate": "4.2%",
    "processingTime": "avg 3.2s"
  }
}

Optimization Insights:

  • Are too many going to manual review? (lower threshold)
  • High false positive rate? (raise threshold, add required fields)
  • Expensive? (remove unnecessary categories for low-risk)

Best Practices

  1. Start with pre-built templates - Modify rather than build from scratch
  2. Test in sandbox - Validate template logic before production
  3. Document use cases - Clear guidance on when to use each template
  4. Review regularly - Update based on regulatory changes and analytics
  5. Version control - Track changes to templates over time
  6. Train staff - Ensure team understands which template to use when
  7. Audit trail - Log which template was used for each search

Compliance Mapping

Map templates to regulatory requirements:

RegulationRecommended Template
6AMLD (EU)Standard KYC (basic), Enhanced DD (high-risk)
PATRIOT Act (US)Standard KYC + adverse media
MiCA (Crypto - EU)Crypto Exchange KYC
UK MLR 2017Standard KYC, PEP Focus (where applicable)
FATF RecommendationsRisk-based: Low/Medium/High templates

Template Library

Shared templates across organisation:

// Organization-wide templates
GET /api/v3/aml/templates?scope=organisation
 
// My personal templates
GET /api/v3/aml/templates?scope=user
 
// Public (VeriPlus provided)
GET /api/v3/aml/templates?scope=public

Share Template:

POST /api/v3/aml/templates/:id/share
 
{
  "shareWith": "organisation", // or specific userIds
  "permissions": {
    "view": true,
    "use": true,
    "edit": false // Read-only
  }
}

Next Steps

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