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1. Correspondent Banking Networks
Nima Safaei, Taha
Jaffer
Data Science & Analytics
Lab,
Customer Insights, Data and Analytics,
Scotiabank,
September 2020

2. 2
Agenda
01
02
03
04
05
06
Background
Network Construction
Network Components
Theoretical Findings
Network Analytics
Business Impacts

3. 3
Background
Correspondent Banking (CB) Network
refers to a network of financial institutions providing cross-border payment services for customers through
different channels such as SWIFT, Fedwire, etc. Through the CB network, banks and their customers can
access financial services in different jurisdictions and provide cross-border payment services to their
customers, supporting, among other things, international trade and financial inclusion.
Global Risks
Financial institutions globally are at risk of being used by criminal organizations to launder money and by
terrorist groups to facilitate the financing of their activities. Consequently, banks globally are facing increasing
scrutiny from both regulators and clients.
News: Bank stocks tumble after report alleges firms moved $2 trillion in suspicious funds (Business Insider – Sep 21 2020)
CB Network Optimization
Optimizing CB Network requires decisions to be made to onboard, terminate or restrict the bank
relationships to optimize the value of the bank to the network vs. risk.
Contributions
• First of its kind :study the structure and key properties of the CB network (https://arxiv.org/abs/1912.02262).
• Banks Evaluation Criteria: Identify network-based criteria to measure the value of banks (i.e., access
criticality, directional flow, Volume/amount of transactions, etc.)
• Proactive Strategy: finding the components in the network which are higher risks such as
Money-laundering, Terrorist financing, credit, U-turning, and Nesting.
Literature Gap
Little work has been done on theoretical foundation of the CB networks as directed graphs.

4. 4
Network
Construction
Cross-boarder payments (>3M records per year)
• Fuzzy name matching (customers/banks’ unique id)
• Text mining (typo errors, incomplete info,…)
• Duplications removalBenefit Features
Amount Thru.
Volume Thru.
Access to Banks
Access to BNS Customers
Touchpoints
# of currency cleared
Top-segment customer
Risk Features
Vostro Rate (%)
ML/TF Risk
Product Risk (%)
Internal Grade Score
Flow direction (KYC)
MachineLearning
Feature Engineering
Scoring thru. clustering (Bank Evaluation)
Network Analysis thru. Graph mining
Flow Analysis
Data Ingestion

5. 5
Network
Components
• Customer: A sender or receiver
• Correspondent Bank: A bank with inward/outward flow from/to customer
• Intermediary bank: bank without direct connection with customers
• Network Flow: Amount and Volume of transactions between pair entities
• Bridge Set: minimal set of banks the removal of which divides the network into two
disjoint sub-networks of senders and receivers (NP-hard).
• Critical Cut: minimal set of relationships the removal of which divides the network into
two disjoint sub-networks of senders and receivers (NP-hard)
• Network Diameter: the maximum distance (shortest path) between any pair of
sender-receiver.
• Bifurcated pattern: lack of unique path between each sender-receiver pair

6. 6
Theoretical
Findings

7. 7
Network
Analytics

8. 8
Business
Impacts
• Faster decision making (from weeks to hours)
• Saving in man-hours (+200K per year)
• Visibility on interbank relationships (a portion or entire CB network
can be shown over different layers, e.g., geographical, counterparty
or risk level).
• Satisfying regulatory 1st
Line behavioural monitoring
• Rapid response to new risks identified in the network
• Candidate to satisfy transaction monitoring for GBM KYC (Global
Banking & Marketing – Know Your Customer)
• 108 Vostro accounts have been closed since Jan 2018.

9. Thank you