This presentation was given on October 4, 2016 at the Toronto Marriott Downtown Eaton Centre Hotel at the 14th installment of Canada’s premier event in the field of money laundering compliance and control. The theme of Money Laundering in Canada 2016 is Financial Crime, Compliance, and Regulation: Keeping Pace with the Times.

1. MONEY LAUNDERING IN CANADA 2016
FINANCIAL CRIME, COMPLIANCE & REGULATION
HOW TO
CONDUCT AN
AML SYSTEM
ASSESSMENT presented by

2. PRESENTATION
KEITH FURST

3. ANTI-
MONEY
LAUNDERING (AML)
SYSTEM

4. OVERVIEW
Implementation assessment
Ongoing data quality
Model performance

5. TECHNICAL
DOCUMENTATION
Architecture
Functional Specification
Extract, Transform and Load
(ETL) process
Operations manual
Inadequate documentation could be a risk for AML system
operations because of staff attrition.

6. AUDIT AND
CONTROLS
If, the above procedures are not implemented then it could
increase the risk for failures in the IT department which
increases the risk to Compliance (owner of the AML system).
Error handling
Database backups
Source code control

7. DATA
RECONCILIATION
Validating the counts of source data and comparing counts in
the AML system is crucial for accountability and producing an
audit trail.

8. DATA
VOLUME
TRENDS
Volatility in the daily record count of crucial transaction files
could be a symptom of issues in the ETL process.
0
10000
20000
30000
40000
50000
60000
70000
80000
90000
100000
September 2016 Record Count

9. ONGOING
DATA
VALIDATION
NULL check
Referential Integrity
Range of values
Data can change over time so it is essential to build ongoing
validation processes to ensure accuracy and make
configuration changes as needed.

10. CLIENT
ONBOARDING
STANDARDIZATION
If, new client data is captured without strict standards then the
quality of results in the AML and/ or fraud system will degrade.
i.e. Address validation and account takeover incidents.
Names
Addresses
Phone numbers
Tax identification

11. MODEL
PERFORMANCE
Distinct account / alert ratio
STR ratio
High risk entity attributes
Group segmentation
Thresholds and scoring
Creating metrics to evaluate a model’s performance over
time is a way to identify trends and improvements for
optimization.

12. IN
SUMMARY
Is employee attrition a risk because of lack of
documentation ?
Are you monitoring for data quality red flags
on a daily basis?
Is your AML dashboard helping to identify
trends at the enterprise level?

13. QUESTIONS?