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Datasets:
alerterra
/
correspondent_banking

Languages:
English
Size:
1K<n<10K
Tags:
Synthetic
banking
swift
aml
correspondent
compliance
License:
Dataset card Data Studio Files
xet
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Correspondent Banking Test Data

Multi-layer SWIFT message chains with nested activity and risk patterns

Publisher: Alerterra Intelligence | Version: 1.0 | Updated: March 2026

Overview

This dataset is part of the Alerterra Synthetic Intelligence Data Suite — 99 records across 28 fields, generated using domain-specific AI models trained on patterns from Alerterra's enterprise intelligence platform.

100% synthetic — zero PII, zero real entity data. Safe for AI/ML model training, system testing, compliance demonstrations, and analyst training.

Use Cases

  • Test correspondent banking monitoring systems
  • Validate nested MSB/MVTS detection
  • Train payable-through account risk models
  • Support de-risking decision frameworks
  • Benchmark SWIFT message screening accuracy

Dataset Structure

Metric Value
Records 99
Fields 28
Formats CSV, JSON, Parquet
Update Frequency Monthly

Fields

Field Type Description
message_id object Message Id
message_type object Message Type
sender_bic object Sender Bic
sender_bank_name object Sender Bank Name
sender_country object Sender Country
receiver_bic object Receiver Bic
receiver_bank_name object Receiver Bank Name
receiver_country object Receiver Country
intermediary_bic object Intermediary Bic
intermediary_country object Intermediary Country
ordering_customer object Ordering Customer
beneficiary_customer object Beneficiary Customer
amount_usd float64 Amount Usd
currency object Currency
value_date object Value Date
purpose_of_payment object Purpose Of Payment
relationship_type object Relationship Type
respondent_bank_tier object Respondent Bank Tier
kyc_status object Kyc Status
downstream_correspondents int64 Downstream Correspondents
nested_msb_activity bool Nested Msb Activity
high_risk_jurisdiction bool High Risk Jurisdiction
sanctions_nexus bool Sanctions Nexus
pep_transaction bool Pep Transaction
unusual_pattern object Unusual Pattern
risk_score float64 Risk Score
is_suspicious bool Is Suspicious
suspicious_reason object Suspicious Reason

Sample Data

This repository contains a free sample (100 records). The full dataset and monthly refresh subscriptions are available at alerterra.com.

Pricing

Tier Details
Sample Free (100 records)
Standard $15,000
Professional $35,000/year
Enterprise $50,000-$100,000/year

Methodology

Generated using Claude AI with domain-specific context injection encoding Alerterra's intelligence platform expertise (Vigila, Tradana, Gradara, Condura, Scrutera, RegSeal). Every dataset undergoes automated statistical validation, correlation analysis, and domain-specific business rule checks.

Citation 

@dataset{alerterra_correspondent_banking_2026,
  title = {Correspondent Banking Test Data},
  author = {Alerterra Intelligence},
  year = {2026},
  publisher = {Hugging Face},
  url = {https://huggingface.co/datasets/alerterra/correspondent_banking}
}

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