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Developing Efficient Transaction Monitoring Processes with Limited Resources
10 December 2013 | 15.30 – 16.3010 December 2013 | 15.30 – 16.30
Moderator:
Ursula M'Crystal, Head of Money Laundering Surveillance, Global Financial Crime,
Standard Bank
Presenters:
Dr. Ana Cristina Hopffer Almada, Programme Manager, African Innovation Foundation
Solomon Kofi Dawson, Head, Compliance & AMLRO, uniBank Ghana LimitedChris McAuley, Director of Fraud & Financial Crime, Advanced Analytics Business
Unit (AABU), SAS
Developing Efficient Transaction Monitoring Processes with Limited
ResourcesResources10 December 2013 | 15.30 – 16.30
Dr. Ana Cristina Hopffer Almada, ProgrammeManager, African Innovation Foundation
Discussion Item #3
Exploring affordable tools
and resources for
33rd Annual AML & Financial Crime Conference, Africa
and resources for
monitoring suspicious
transactions
Discussion Item #3
Resources
•Human
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•Human
• Technological
Discussion Item #3
Human Resources
• Knowledge
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• Knowledge
• Compliance Culture
• Training
• Relation management
Discussion Item #3
Tools (AML Organizational
Components)
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Components)
• Primary Level
• Governamental Level
Discussion Item #3
Primary Level Technologies
• Risk Management Software
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• Risk Management Software
• Identification Software
Discussion Item #3
Role of Technology
•What can do?
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•What can do?
•What cannot do?
Discussion Item #3
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What can you do?
Discussion Item #3
Thank you!
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Thank you!
Developing Efficient Transaction Monitoring Processes with Limited Resources
10 December 2013 | 15.30 – 16.3010 December 2013 | 15.30 – 16.30
Solomon Kofi Dawson, Head, Compliance & AMLRO, uniBank Ghana Limited
Transaction Monitoring Process in
TBML
• Risk Based Approach for Customer On-boarding and screening
• Improve on Customer Acceptance and
123rd Annual AML & Financial Crime Conference, Africa
• Improve on Customer Acceptance and Nature of business alignment
• Expected volume of transaction through internal thresholds
• Trade Documentation Review through key document
Risk Based Approach for Customer
On-boarding and screening
• Low Risk
• Medium Risk.
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• Medium Risk.
• Medium High.
• High Risk.
Nature of business alignment
• Synchronizing customers CDD responses to the trade transactions
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to the trade transactions
• Compare nature of business with nature of trade transaction
• Expected volume of transaction
• Key trade documents review
Developing Efficient Transaction Monitoring
Processes with Limited Resources
10th December 2013 � 15.30
Chris McAuley, Director, SAS Institute
Common Objectives
INCREASE DETECTION RATES
• Identify more sources of non-compliance
• Ensure fewer cases go undetected
ACCURACY• Reduce false positives
• Focus on cases with higher yield
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EFFICIENCY
• Work cases and inspections faster
• Remove time wasted on data collection
TOTAL COST OF OWNERSHIP• Single, integrated platform
• Leverage investment over multiple business areas
Predictive Text
Database
Searches
Anomaly detection (example): A customer with a higher ratio of
Text mining (example): Examination of customer correspondence (inc E-Mails) to find phrases or words indicative of an association with a US entity.
Database Searches (example): Looking for
Predictive modelling (example): Finding customers with sources of funds similar to other entities in the Enterprise that case officers have determined are US liable
The Importance of Analytics
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Analytic Analytic Decisioning Decisioning
EngineEngineAutomated
Business Rules
Anomaly
Detection
Predictive
Modeling
Text
Mining Searches
Social Network Analysis
Business rule (example): An applicant providing a US address
with a higher ratio of US destined transactions than the peer group
Looking for matches across the known industry watch lists
SNA (example): A number of people on a network who are US tax liable, together with ones who appear to have avoided internal DD
illustrated using sample FATCA examples
Deployed in an “Industry Standard” way
183rd Annual AML & Financial Crime Conference, Africa