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Strengthen your AML Compliance Program with Data Mining

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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



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Published in: Data & Analytics
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Strengthen your AML Compliance Program with Data Mining

  1. 1. STRENGTHEN YOUR AML COMPLIANCE PROGRAM WITH DATA MINING WEBINAR
  2. 2. PRESENTER Rory Barrett Business Analyst, Project Manager Symptai Consulting
  3. 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. 4. AGENDA • What is Data Mining? • Impact • Start Mining Your Data • Applications in Industry
  5. 5. AGENDA • What is Data Mining? • Impact • Start Mining Your Data • Applications in Industry
  6. 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. 7. PROBLEM: THE DATA EXPLOSION
  8. 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. 9. CHALLENGES • Keeping up with technology • Increasing amounts of data being generated • Analysts can only work on 100’s of cases daily
  10. 10. AGENDA • What is Data Mining? • Impact • Start Mining Your Data • Applications in Industry
  11. 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. 12. NO REASON TO SUSPECT STACY • Stacy has not met thresholds • Stacy is not on watch lists • Stacy has not triggered alarms
  13. 13. AGENDA • What is Data Mining? • Impact • Start Mining Your Data • Applications in Industry
  14. 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. 15. • What are my business challenges? • What do I want to achieve? IDENTIFY YOUR BUSINESS OBJECTIVES
  16. 16. ACCESS YOUR DATA SOURCES • Data comes in many different forms
  17. 17. PREPARE THE DATA • Get to know your data – Assess the data quality – Find the data that is useful for your needs
  18. 18. CREATE THE MODEL • The model will define how you use the data
  19. 19. TEST AND DEPLOY
  20. 20. ANOMALY DETECTION
  21. 21. ANOMALY DETECTION: CLUSTERING
  22. 22. NEURAL NETS
  23. 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. 24. ANOMALY DETECTION
  25. 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. 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. 27. We are drowning in DATA but starved for INSIGHT
  28. 28. AGENDA • What is Data Mining? • Impact • Start Mining the Data • Applications in Industry
  29. 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. 30. DATA MINING EXAMPLES • Data Quality Management – Data Cleansing – Data Warehousing
  31. 31. DATA MINING EXAMPLES • Predictive Modelling – Artificial Intelligence
  32. 32. DATA MINING EXAMPLES • Business Intelligence – Dashboards – Visualizations
  33. 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. 34. Embrace your DATA and regain your INSIGHT
  35. 35. QUESTIONS? Contact Us casewareanalytics.com aml@caseware.com
  36. 36. STRENGTHEN YOUR AML COMPLIANCE PROGRAM WITH DATA MINING WEBINAR

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