Vortex: Global Multi-Currency Ledger Twin - Synthetic Dataset

Dataset ID: Njengak11/Vortex
Version: 2.0.0
License: CC BY-NC-SA 4.0
Format: CSV (3 tables)
Total Size: ~110 MB

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📖 Overview

Vortex is a high-fidelity synthetic dataset for a borderless multi-currency neobank, designed to enable stress-testing of real-time multi-currency settlement engines and AML/CFT monitoring systems.

This dataset simulates diverse global spending and remittance behaviors across 15+ currencies with realistic customer personas, transaction patterns, and fraud scenarios.

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🎯 Use Cases

• AML/CFT Model Training - Detect suspicious transaction patterns
• Multi-Currency Settlement Testing - Stress-test FX conversion engines
• Customer Behavior Prediction - Churn, LTV, upsell modeling
• Regulatory Reporting - Stress testing, capital requirements
• Fraud Detection - Anomaly detection in cross-border transactions

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📊 Dataset Structure

Tables

Table	Rows	Size	Description
synthetic_users.csv	50,000	4 MB	Customer demographics & KYC levels
synthetic_wallets.csv	150,000	16 MB	Multi-currency balance buckets
synthetic_ledger_entries.csv	500,000	90 MB	All credit/debit transaction events

Total Records: 700,000
Total Size: ~110 MB

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🔗 Relationship Diagram

┌─────────────────────────────────────────────────────────────────┐
│                    HIERARCHICAL RELATIONSHIP                    │
└─────────────────────────────────────────────────────────────────┘

Level 1: Global SpotPay Treasury
    │
    └─── Level 2: dim_users (50,000 users)
           │
           │ Primary Key: user_id
           │
           ├───→ Level 3: dim_wallets (150,000 wallets)
           │       Foreign Key: account_id → users.user_id
           │       ~3 wallets per user (multi-currency)
           │
           └───→ Level 3: fact_ledger_entries (500,000 entries)
                   Foreign Key: account_id → users.user_id
                   Foreign Key: wallet_id → wallets.wallet_id
                   ~10 entries per user

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🔗 Foreign Key Relationships

Relationship	Parent Table	Child Table	Link Column	Integrity
1	dim_users	dim_wallets	account_id → user_id	100%
2	dim_users	fact_ledger_entries	account_id → user_id	100%
3	dim_wallets	fact_ledger_entries	wallet_id → wallet_id	100%

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📋 Column Definitions

synthetic_users.csv

Column	Type	Description
user_id	UUID	Unique user identifier (Primary Key)
persona_type	Category	Customer segment: nomad, remittance, saver
kyc_level	Category	KYC verification level: basic, standard, enhanced, premium
onboarding_date	Date	User registration date
country_of_residence	Category	2-letter country code
risk_score	Number	Risk score (0-100)
account_status	Category	active, dormant, suspended, closed

synthetic_wallets.csv

Column	Type	Description
wallet_id	UUID	Unique wallet identifier (Primary Key)
account_id	UUID	Foreign Key → users.user_id
currency	Category	3-letter currency code (15 currencies)
balance	Number	Wallet balance in currency units
wallet_status	Category	active, frozen, closed
created_date	Date	Wallet creation date

synthetic_ledger_entries.csv

Column	Type	Description
txn_id	UUID	Unique transaction identifier (Primary Key)
account_id	UUID	Foreign Key → users.user_id
wallet_id	UUID	Foreign Key → wallets.wallet_id
txn_type	Category	Transaction type (see below)
base_amount	Number	Transaction amount in original currency
base_currency	Category	Transaction currency
fx_rate	Number	FX rate to USD
settled_usd	Number	Settled amount in USD
timestamp	DateTime	Transaction execution time (millisecond precision)
is_anomaly	Binary	Fraud/anomaly flag (0=normal, 1=anomaly)

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🏷️ Transaction Types

Type	Description	Frequency
Remittance_In	International inbound transfers	20.8%
Local_Pay	Domestic P2P and bill payments	19.5%
Card_Spend	POS and e-commerce transactions	29.6%
FX_Swap	Currency exchange operations	17.9%
Yield_Earn	Interest accrual events	12.2%

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🌍 Currencies Supported (15)

Currency	Code	Frequency
US Dollar	USD	14.9%
Euro	EUR	12.1%
British Pound	GBP	9.5%
Nigerian Naira	NGN	7.4%
Kenyan Shilling	KES	7.3%
UAE Dirham	AED	6.6%
Indian Rupee	INR	6.5%
Japanese Yen	JPY	5.8%
Chinese Yuan	CNY	4.6%
Australian Dollar	AUD	4.6%
Canadian Dollar	CAD	4.5%
Singapore Dollar	SGD	4.4%
Swiss Franc	CHF	4.4%
South African Rand	ZAR	4.1%
Ghanaian Cedi	GHS	3.3%

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👥 Customer Segments

Segment	Distribution	Characteristics
Digital Nomad	60%	Receives USD/EUR, spends locally in multiple jurisdictions, high card-spend frequency
Remittance Lifeline	30%	Receives large monthly international transfers, immediate local withdrawals or P2P
High-Yield Saver	10%	Maintains high balances in stablecoins or USD, primary events are interest accruals

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🎭 Injected Scenarios (Q3.7)

Scenario 1: Follow the Sun Traveler (HIGH Criticality)

• Trigger: Card swipes in three different time zones within 24 hours
• Pattern: London (GBP) → Dubai (AED) → Nairobi (KES)
• Tests: Fraud detection vs. legitimate nomad travel

Scenario 2: Yield-Chasing Capital Movement (MEDIUM Criticality)

• Trigger: High-value balance swap from USD to high-yield local currency
• Pattern: Large FX swaps during promotional periods
• Tests: Market manipulation detection

Scenario 3: Suspicious Velocity - AML (HIGH Criticality)

• Trigger: Rapid-fire Remittance_In followed by Local_Withdrawal within <10 minutes
• Pattern: Repeats 5+ times across different counterparties
• Frequency: 0.5% of transactions
• Tests: Money laundering detection (structuring/smurfing)

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📊 Sample Data Walkthrough

User: 1d751122-4cb1-49bb-b800-1f8970df7841

Attribute	Value
Persona	Digital Nomad
KYC Level	standard
Country	Canada

Wallets (3)

Wallet ID	Currency	Balance
c5156142…	USD	$6,164.15
b1fcab7a…	EUR	€1,544.31
e17499e6…	SGD	S$30,525.74

Ledger Entries (10 for this user)

Txn ID	Type	Amount	Currency
76cc1eb8…	FX_Swap	403.47	GBP
695fe135…	FX_Swap	138.25	GBP
3685dc1f…	Remittance_In	5,240.19	EUR

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✅ Key Points

Data Integrity

• No Orphan Records: Every wallet belongs to a valid user, every ledger entry belongs to a valid user AND wallet
• Multi-Currency Structure: Each user has ~3 wallets (different currencies)
• Transaction Tracking: Every ledger entry links to both:
  • The user who initiated it (account_id)
  • The specific wallet it affected (wallet_id)
• Balance Reconciliation (Q7.10): The sum of all ledger entries per wallet matches the wallet's balance

Schema Design

This is a properly normalized star schema optimized for:

• AML/CFT monitoring (trace transactions to users)
• Multi-currency settlement (track per-wallet balances)
• Regulatory reporting (aggregate by user, wallet, or currency)

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🎯 Target Column

is_anomaly (in synthetic_ledger_entries.csv)

Value	Label	Frequency
0	Normal	98.5%
1	Anomaly	1.5%

Acceptable Range: 1.0% - 2.0%
Actual Rate: 1.5% ✅

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🔒 Privacy & Compliance

Privacy Protections

• ✅ No Real PII - All user IDs are synthetic UUIDs
• ✅ Masked Financial IDs - IBANs, SWIFT codes are synthetic
• ✅ Luhn-Valid Card PANs - Follow Luhn algorithm but use non-existent BIN (540000)
• ✅ GDPR Compliant - No personal data from real customers

Compliance Standards

• ✅ AML/CFT simulation patterns included
• ✅ KYC/KYB levels represented
• ✅ PCI-DSS compliant (no real card numbers)
• ✅ GDPR Article 25 (Data Protection by Design)

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📈 Validation Results

Check	Status
Q7.1 Constraints
timestamp_ordering	✅ PASS
fx_calculation	✅ PASS
wallet_balance_non_negative	✅ PASS
Q3.7 Scenarios
Follow the Sun Traveler	✅ PRESENT
Yield-Chasing Capital Movement	✅ PRESENT
Suspicious Velocity (AML)	✅ PRESENT
Q6.3 Rate
is_anomaly: 1.50% (target: 1.0%-2.0%)	✅ IN RANGE
Q7.10 Acceptance
ledger_balances_match	✅ PASS
fx_rates_follow_volatility	✅ PASS
pii_masked	✅ PASS
referential_integrity	✅ PASS
Overall	100% PASS (11/11)

📄 License

CC BY-NC-SA 4.0 - Creative Commons Attribution-NonCommercial-ShareAlike 4.0

You are free to:

• ✅ Share - copy and redistribute the material
• ✅ Adapt - remix, transform, and build upon the material

Under the following terms:

• Attribution - Give appropriate credit
• NonCommercial - You may not use the material for commercial purposes
• ShareAlike - If you remix, transform, or build upon the material, you must distribute your contributions under the same license

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