Data mining is a critical component of any compliance program. By helping identify hidden patterns, discover unknown relationships in your data, and predict behaviours and trends, data mining can be a strategic part of your business. In this webinar, we will examine data mining techniques that can be used to identify risk factors in your compliance program, monitor customer activity and provide insights into your overall business. KEY TAKEAWAYS: Examine the impact of data mining as a means of fraud detection Understand how to combine technology and human behaviour to identify fraud and other financial crimes Learn data mining strategies you can incorporate into your continuous controls monitoring and compliance programs Explore real-world case studies that illustrate how to apply data mining techniques

1. STRENGTHEN YOUR AML COMPLIANCE
PROGRAM WITH DATA MINING
WEBINAR

2. PRESENTER
Rory Barrett
Business Analyst, Project
Manager
Symptai Consulting

3. SYMPTAI CONSULTING
• An industry leader in technology solutions for audit, security,
business process controls, and compliance
• Founded in 1998, over 150 clients
• Successfully implemented CaseWare AML monitoring
solutions throughout the Caribbean

4. AGENDA
• What is Data Mining?
• Impact
• Start Mining Your Data
• Applications in Industry

5. AGENDA
• What is Data Mining?
• Impact
• Start Mining Your Data
• Applications in Industry

6. WHAT IS DATA MINING?
Data can be found:
• Customer Relationship Management (CRM)
• Human Resource Management (HRM)
• Enterprise Resource Planning (ERP)
• Application Software
• Excel

7. PROBLEM: THE DATA EXPLOSION

8. PROBLEM: THE DATA EXPLOSION
“We are drowning
in information but
starved for
knowledge.”
Naisbitt, J. (1982). Megatrends:
Ten New Directions Transforming
Our Lives.
We are drowning
in DATA but
starved for
INSIGHT

9. CHALLENGES
• Keeping up with technology
• Increasing amounts of data being generated
• Analysts can only work on 100’s of cases daily

10. AGENDA
• What is Data Mining?
• Impact
• Start Mining Your Data
• Applications in Industry

11. YOU ARE UNDER INVESTIGATION
• Law enforcement claims your organization is involved in
money laundering activities
• Your customer is suspected of funding illegal weapons
purchases through her account
Stacy Valdez
– Age: 72 years old
– Marital Status: Married
– Occupation: Retired Nurse
– Customer Relationship: 32 years

12. NO REASON TO SUSPECT STACY
• Stacy has not met thresholds
• Stacy is not on watch lists
• Stacy has not
triggered alarms

13. AGENDA
• What is Data Mining?
• Impact
• Start Mining Your Data
• Applications in Industry

14. MINING YOUR DATA: MAIN STEPS
1. Identify your business objectives
2. Access your data sources
3. Prepare the data
4. Create the model
5. Test and deploy

15. • What are my business challenges?
• What do I want to achieve?
IDENTIFY YOUR BUSINESS OBJECTIVES

16. ACCESS YOUR DATA SOURCES
• Data comes in many different forms

17. PREPARE THE DATA
• Get to know your data
– Assess the data quality
– Find the data that is useful for
your needs

18. CREATE THE MODEL
• The model will define how you use the data

19. TEST AND DEPLOY

20. ANOMALY DETECTION

21. ANOMALY DETECTION: CLUSTERING

22. NEURAL NETS

23. BENEFITS
• Savings on time, manpower and costs
• Solve problems in real-time
• Fraud prediction
• More accurate data
• Better informed decisions
• Faster information for faster action
• Data mining analyses thousands of risk patterns instantly

24. ANOMALY DETECTION

25. DATA MINING ALERTS FOR RECENTLY ACTIVATED
ACCOUNTS
• Stacy Valdez reactivates her dormant account on May 2014
• Stacy deposits $100,000 in her reactivated account
• Her payments are made to 3 different computer stores
• Payment are made to a different store every 2-4 weeks
• Payments range between $60,000US-$90,000US
• Stacy continues to make deposits for a number of weeks

26. STACY IS NOT ACTING ALONE
• 11 other accounts are flagged
as making payments to the
same group of computer stores
• All accounts were previously
dormant from customers over
the age of 65
• Total payments estimate
$15,000,000+ per year!

27. We are drowning in DATA but starved for INSIGHT

28. AGENDA
• What is Data Mining?
• Impact
• Start Mining the Data
• Applications in Industry

29. DATA MINING IN OTHER INDUSTRIES
Industry
• Finance
• Insurance
• Telecom
• Healthcare
• Transport
• Consumer Goods
• Research
• Utilities
Application
• Credit Card Analysis
• Claims, Fraud Analysis
• Call record analysis
• Patient Diagnostic Analysis
• Logistic Management
• Promotion Analysis
• Image, Video, Speech
Analysis
• Power Usage Analysis

30. DATA MINING EXAMPLES
• Data Quality Management
– Data Cleansing
– Data Warehousing

31. DATA MINING EXAMPLES
• Predictive Modelling
– Artificial Intelligence

32. DATA MINING EXAMPLES
• Business Intelligence
– Dashboards
– Visualizations

33. KEY TAKEAWAYS
• Bridge the big data gap
• Changes in technology introduce new levels of risk to fraud
• Data mining helps you see what may be missing
• Adapt to ever changing threats
• Pattern matching to detect fraud
• Different data models to suit different needs
• Applicable to virtually any industry

34. Embrace your DATA and
regain your INSIGHT

35. QUESTIONS?
Contact Us
casewareanalytics.com
aml@caseware.com

36. STRENGTHEN YOUR AML COMPLIANCE
PROGRAM WITH DATA MINING
WEBINAR