Use Case Tutorial - Fraud in Retail (2/7)

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Part 2 of 7 of the Use Case Tutorial presented at DEBS'2009 in Nashville, TN

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Use Case Tutorial - Fraud in Retail (2/7)

  1. 1. CITT CENTRUM FÜR INFORMATIONS-TECHNOLOGIE TRANSFER GMBH EP-TS Use Case Workgroup Use Case: Fraud Management in the Retail Domain DEBS2009 Thomas Paulus 1
  2. 2. AGENDA  Definition of Shrinkage  Fraud Management nowadays  Characteristics of the IT-Infrastructure  Event Processing for Fraud Management  Architecture of a prototype implementation Thomas Paulus 2
  3. 3. USE CASE: FRAUD MANAGEMENT IN THE RETAIL DOMAIN DEFINITION OF THE TERM „SHRINKAGE“ Shrinkage (also known as loss or shortage) can be defined as loss of stock caused by one or a combination of:  Theft Employee Fraud  Discount fraud … Shoplifting and  Theft Customer Fraud  Return fraud … Shrinkage Administrative  Misspelling Error  Accounting error …  Delivery error Supplier Fraud  Accounting error … Thomas Paulus 3
  4. 4. USE CASE: FRAUD MANAGEMENT IN THE RETAIL DOMAIN FIGURES ON GLOBAL SHRINKAGE The Global Retail Theft Barometer 2008: Total global shrinkage: > 100 billion $ About 1.34% of the overall retail sales All Retail Industry Customer Staff Only ~ 50% of stock loss is considered to be „known“ Suppliers / Service Organisation Expenses for loss prevention: >1 billion $ Sectors differ greatly, loss calculation differs greatly Source: http://www.retailresearch.org/theft_barometer/index.php Thomas Paulus 4
  5. 5. AGENDA  Definition of Shrinkage  Fraud Management nowadays  Characteristics of the IT-Infrastructure  Event Processing for Fraud Management  Architecture of a prototype implementation Thomas Paulus 5
  6. 6. USE CASE: FRAUD MANAGEMENT IN THE RETAIL DOMAIN METHODS EMPLOYED AGAINST SHRINKAGE PROCEDURES AND ROUTINES EQUIPMENT AND TECHNOLOGY  Annual stock loss awareness campaign  Automated ordering processes  Company-wide stock loss refresher training  Cash protection tactics and equipment (both cash offices and tills)  Customer returns & refund controls (operator and customer database)  Company-wide stock loss awareness posters  Damaged goods resale controls  Dummy display cards in place of high-risk products  Employees exit searches  E.A.S. hard tagging (recycled)  Hot product identification  E.A.S. soft tagging (disposable)  Hot product management  E.A.S. source tagging (either disposable or recycled)  Hot products routine counting  Employee purchasing arrangements  Security newsletter  Employee panic alarms  Internal key control  Employee uniforms without pockets  Patrol routes for employees (red routes)  Intruder alarm systems  Point of sale information or data checks  Non-active CCTV  Random till cash checks  Point-of-sale camera monitoring Rigorous delivery checking procedures All these methods Protector display cases applied by retail outlets    Shelf replenishment techniques  R.F.I.D. intelligent tags on pallets, cases or items  Induction training for new employees  (radio frequency)  Unique till operator PIN numbers can’t avoid  Replenishment equipment to support techniques  ‘Watertight’ product monitoring procedures  Secure lockers for employees PEOPLE AND PROCESSES TODAY   Security-sealed containers/shippers Shoplifting and theft policy posters for customers and staff   Anonymous phone line Civil recovery the high level  Specialist anti-theft display equipment   Covert surveillance of customers or employees Employee awareness and training of shrinkage! LAYOUT location strategies DESIGN AND  Appropriate product  Employee stock loss training and education  Designing-out blind spots  Employee incentives—discount purchase schemes  Designing-out crime programme  Employee incentives—stock loss bonus schemes  Distribution centre secure storage  Employee integrity checks  Employees entry/exit access control  External compliance monitoring  External security—fences, anti-ram raid, roll shutters  External security/loss prevention function  Risk-based design and layouts  External stock audit function  Robust anti-theft packaging  Internal compliance monitoring  Single direction product flow  Internal security/loss prevention function  Supply chain and logistics network design  Internal stock audit function  Random checks on distribution centre picking accuracy  Store detectives  Test purchasing (mystery shopper)  Uniformed security guards Thomas Paulus 6
  7. 7. USE CASE: FRAUD MANAGEMENT IN THE RETAIL DOMAIN REASONS FOR INEFFICIENT FRAUD MANAGEMENT Autonomous  Independent loss prevention systems Systems  Video surveillance  Electronic article surveillance Post processing  Fraud is detected after it happens Why are the of recorded data  Too late for interventions current methods inefficient? Missing or not used  Individual implementations standards  Hard to compare and measure Manual fraud  Efficiency depends on the quality of the detection staff  Mistakes can be made Thomas Paulus 7
  8. 8. USE CASE: FRAUD MANAGEMENT IN THE RETAIL DOMAIN KNOWN STANDARDS AND PRODUCTS Semantics and  ARTS NEAR (Notification Event Standards Architecture for Retail)  ARTS Video Analytics  ARTS POSlog (formerly IXRetail)  ARTS SOA Blueprint for Retail First  ... approaches to solve the problems  IBM: Store Integration Framework Infrastructures  Microsoft: Smarter Retailing Architecture  Wincor Nixdorf: Store Communication Framework  ... Thomas Paulus 8
  9. 9. AGENDA  Definition of Shrinkage  Fraud Management nowadays  Characteristics of the IT-Infrastructure  Event Processing for Fraud Management  Architecture of a prototype implementation Thomas Paulus 9
  10. 10. USE CASE: FRAUD MANAGEMENT IN THE RETAIL DOMAIN TYPICAL IT LANDSCAPE IN THE RETAIL DOMAIN Characteristics:  Heterogeneous  Independent Components  No common data standards between components  No common data standards between enterprises Thomas Paulus 10
  11. 11. USE CASE: FRAUD MANAGEMENT IN THE RETAIL DOMAIN TYPICAL IT LANDSCAPE IN THE RETAIL DOMAIN High amount of business data:  Sales-Data:  x sales per shop  y sales per hour  z items per sale  Customer-Data:  Customer Counter  Credit / Debit Cards  Loyalty programs  Security-Data:  Electronic Article Surveillance data  RFID-tracking  Customer Position tracking  Video Surveillance data  …... Thomas Paulus 11
  12. 12. AGENDA  Definition of Shrinkage  Fraud Management nowadays  Characteristics of the IT-Infrastructure  Event Processing for Fraud Management  Architecture of a prototype implementation Thomas Paulus 12
  13. 13. USE CASE: FRAUD MANAGEMENT IN THE RETAIL DOMAIN EVENT PROCESSING FOR FRAUD MANAGEMENT? Why should event processing technologies be used for fraud management in the retail domain? Possible solution based on Current situation event processing technologies Pro: Pro:  Best Practice  Real-time fraud detection  Already available  Pro-active fraud management  Accepted technology Contra: Contra:  Still high amount of shrinkage  No implementations available  Expenses  Rare knowledge Thomas Paulus 13
  14. 14. USE CASE: FRAUD MANAGEMENT IN THE RETAIL DOMAIN POSSIBLE FRAUD SCENARIOS Possible Fraud Scenarios and corresponding actions Scenario Action A customer wants to return  Abort the return process an already returned item  Start a fraud management Pattern detection A customer returns very process frequently items  Call the police A customer returns an item with a differing serial number  Modify the customer properties A customer wants to return a not sold item  etc. Thomas Paulus 14
  15. 15. AGENDA  Definition of Shrinkage  Fraud Management nowadays  Characteristics of the IT-Infrastructure  Event Processing for Fraud Management  Architecture of a prototype implementation Thomas Paulus 15
  16. 16. USE CASE: FRAUD MANAGEMENT IN THE RETAIL DOMAIN CONCEPT OF A PROTOTYPE IMPLEMENTATION Fraud Management Define Recognize Act Possible architecture for future Fraud Management Complex BPM Workflow Process Layer Event Engine Processing Application Layer POS CRM … Thomas Paulus 16
  17. 17. USE CASE: FRAUD MANAGEMENT IN THE RETAIL DOMAIN NEXT STEPS  Next steps for the Fraud Management System:  Implementation of the prototype  BPM Suite: jCOM1  http://www.jcom1.com  CEP Engine: RTM (Realtime Monitoring)  http://www.realtime-monitoring.de Thomas Paulus 17

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