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Detecting Opportunities  and Threats with Complex Event Processing:  Case Studies in Predictive Customer Interaction Management and Fraud Detection   February 27, 2007  FINAL DRAFT 2 8th Annual Japan's International Banking & Securities System Forum Tim Bass, CISSP  Principal Global Architect, Director
 
Our Agenda ,[object Object],[object Object],[object Object]
What is Complex Event Processing? ,[object Object],[object Object],[object Object],Complex Event Processing in Distributed Systems, Stanford University, 1998
When Do You Need to Think About CEP? ,[object Object],[object Object],[object Object],[object Object],[object Object],The Power of Events , Addison Wesley, ISBN: 0-201-72789-7, 2002
CEP Brings Two Kinds Of Business Benefits Ref: Roy Schulte, Gartner, First Event Processing Symposium, 2006 2. Complex-Event Processing (CEP) for Earlier and Better Insight Order Entry Manufacturing Shipping 1. Event-Driven Architecture (EDA) for Flexibility and Maintainability
Detecting Opportunities and Threats with Complex Event Processing (CEP)
TIBCO BusinessEvents™ Overview BusinessEvents™ Solutions Space Data: Events & Databases -Real-Time & Historical Data Models: Statistical Financial Optimization Comms: Pub/Sub Messaging Queues Topics UIs Knowledge: Facts & Rules
Reference Architecture An Enterprise View of Complex Event Processing   24 EVENT PRE-PROCESSING EVENT SOURCES EXTERNAL .  .  .  LEVEL ONE EVENT TRACKING Visualization, BAM, User Interaction CEP Reference Architecture DB MANAGEMENT Historical Data Profiles & Patterns DISTRIBUTED LOCAL EVENT SERVICES . . EVENT PROFILES . . DATA BASES . . OTHER DATA LEVEL TWO SITUATION DETECTION LEVEL THREE PREDICTIVE ANALYSIS LEVEL FOUR ADAPTIVE BPM
Summary of Complex Event Processing Flexible SOA and Event-Driven Architecture
Bloor Report on Event Processing Event Processing and Decision Making Automated Operational Decisions   Automated Predictive Decisions   Human Predictive Decisions   Human Operational Decisions   Decision Latency   Event Complexity   Process Complexity   Pattern Matching and Inferencing   Anti-Money Laundering   Credit-Card Fraud Exchange Compliance Database Monitoring Algorithmic Trading Trade Desk Monitoring Customer Interaction Order Routing RFID Tariff Look-Up Rail Networks Search & Rescue Baggage Handling Liquidity Management
Our Agenda ,[object Object],[object Object],[object Object]
Use Case: Real-Time Fraud Detection ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object],Industry and Business Drivers A Sample of the Problems with Network Security and Fraud Detection
Real-Time On-Line Fraud Detection Requirements ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
On-Line Fraud Detection Use Case   Architecture and Capacity Planning Approx. 12,000 Hits Per Second During Peak Period Across the Three Sites – One Instance Of TIBCO BusinessEvents™ Capable of Handling Maximum Hits  Overall 100 Million Hits Handled Between 3PM – 4 PM   Peak Approx. 250 Million Hits Per Day Across the Three Sites Session Info Three Server Farms  ~600-700 Application Servers
“ No Code” Custom User Interface Studio TIBCO’s Enterprise RTView™ or General Interface™
Fraud Detection Use Case Summary Overview of Fraud Detection Solutions Architecture ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Our Agenda ,[object Object],[object Object],[object Object]
Use Case:  Predictive Customer Interaction Management PCIM ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Case Study:  Value Proposition ,[object Object],[object Object],[object Object]
Customer Requirements ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Solution Overview Customer Interact Solutions with TIBCO  BusinessEvents ™ ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Case Study:  Bank Employee Interface TIBCO’s General Interface™ (AJAX Web Development)
PCIM High Level Conceptual Architecture
Case Study:  Real-Time Recommendation Engine ,[object Object],[object Object],[object Object],[object Object],[object Object]
Where TIBCO BusinessEvents™ Helped. Collection, Normalization Metric of Managed Objects, Normalized Non-Contextual Events Metadata  Repository Event Management, Correlation,  Aggregation, Inference and  Analysis Correlated, Analyzed, Contextual Dialogue Events   Rules, Knowledge,  Patterns, Models Visualization, Reporting, Alert Management Application Interface Feeds Visualization: Dialogue Metrics Agents Synthetic  Warehouse Visualization: Sales  Process View vCI Dialogue Manager Inference Engine DWH Product Marketing Semantic Model Events Rules Design Environment State Model Middleware
TIBCO BusinessEvents™ ,[object Object],[object Object],[object Object],[object Object],[object Object],Modeling Tools, Statefulness, Business Rules and Process Integration UML Conceptual UML State Business Rules Business Users Event Analyzer
TIBCO BusinessEvents™ Awards 2006 Best Complex Event Processing Software Winner: TIBCO 2006 Event Processing   General Purpose  Gold Award Winner
Additional Reading
Visit TIBCO Demo Booth ,[object Object],[object Object]
Thank You! Tim Bass, CISSP Principal Global Architect, Director Emerging Technologies Group [email_address] Event Processing at TIBCO

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Detecting Opportunities and Threats with Complex Event Processing: Case Studies in Predictive Customer Interaction Management and Fraud Detection

  • 1. Detecting Opportunities and Threats with Complex Event Processing: Case Studies in Predictive Customer Interaction Management and Fraud Detection February 27, 2007 FINAL DRAFT 2 8th Annual Japan's International Banking & Securities System Forum Tim Bass, CISSP Principal Global Architect, Director
  • 2.  
  • 3.
  • 4.
  • 5.
  • 6. CEP Brings Two Kinds Of Business Benefits Ref: Roy Schulte, Gartner, First Event Processing Symposium, 2006 2. Complex-Event Processing (CEP) for Earlier and Better Insight Order Entry Manufacturing Shipping 1. Event-Driven Architecture (EDA) for Flexibility and Maintainability
  • 7. Detecting Opportunities and Threats with Complex Event Processing (CEP)
  • 8. TIBCO BusinessEvents™ Overview BusinessEvents™ Solutions Space Data: Events & Databases -Real-Time & Historical Data Models: Statistical Financial Optimization Comms: Pub/Sub Messaging Queues Topics UIs Knowledge: Facts & Rules
  • 9. Reference Architecture An Enterprise View of Complex Event Processing 24 EVENT PRE-PROCESSING EVENT SOURCES EXTERNAL . . . LEVEL ONE EVENT TRACKING Visualization, BAM, User Interaction CEP Reference Architecture DB MANAGEMENT Historical Data Profiles & Patterns DISTRIBUTED LOCAL EVENT SERVICES . . EVENT PROFILES . . DATA BASES . . OTHER DATA LEVEL TWO SITUATION DETECTION LEVEL THREE PREDICTIVE ANALYSIS LEVEL FOUR ADAPTIVE BPM
  • 10. Summary of Complex Event Processing Flexible SOA and Event-Driven Architecture
  • 11. Bloor Report on Event Processing Event Processing and Decision Making Automated Operational Decisions Automated Predictive Decisions Human Predictive Decisions Human Operational Decisions Decision Latency Event Complexity Process Complexity Pattern Matching and Inferencing Anti-Money Laundering Credit-Card Fraud Exchange Compliance Database Monitoring Algorithmic Trading Trade Desk Monitoring Customer Interaction Order Routing RFID Tariff Look-Up Rail Networks Search & Rescue Baggage Handling Liquidity Management
  • 12.
  • 13.
  • 14.
  • 15.
  • 16. On-Line Fraud Detection Use Case Architecture and Capacity Planning Approx. 12,000 Hits Per Second During Peak Period Across the Three Sites – One Instance Of TIBCO BusinessEvents™ Capable of Handling Maximum Hits Overall 100 Million Hits Handled Between 3PM – 4 PM Peak Approx. 250 Million Hits Per Day Across the Three Sites Session Info Three Server Farms ~600-700 Application Servers
  • 17. “ No Code” Custom User Interface Studio TIBCO’s Enterprise RTView™ or General Interface™
  • 18.
  • 19.
  • 20.
  • 21.
  • 22.
  • 23.
  • 24. Case Study: Bank Employee Interface TIBCO’s General Interface™ (AJAX Web Development)
  • 25. PCIM High Level Conceptual Architecture
  • 26.
  • 27. Where TIBCO BusinessEvents™ Helped. Collection, Normalization Metric of Managed Objects, Normalized Non-Contextual Events Metadata Repository Event Management, Correlation, Aggregation, Inference and Analysis Correlated, Analyzed, Contextual Dialogue Events Rules, Knowledge, Patterns, Models Visualization, Reporting, Alert Management Application Interface Feeds Visualization: Dialogue Metrics Agents Synthetic Warehouse Visualization: Sales Process View vCI Dialogue Manager Inference Engine DWH Product Marketing Semantic Model Events Rules Design Environment State Model Middleware
  • 28.
  • 29. TIBCO BusinessEvents™ Awards 2006 Best Complex Event Processing Software Winner: TIBCO 2006 Event Processing General Purpose Gold Award Winner
  • 31.
  • 32. Thank You! Tim Bass, CISSP Principal Global Architect, Director Emerging Technologies Group [email_address] Event Processing at TIBCO