The When, Why and How of Mobile Fraud Prevention
2 likes1,481 views
The document discusses the prevalence and challenges of mobile fraud prevention as mobile app adoption continues to grow significantly. It highlights various mobile payment trends, types of authentication, and the essential role of tailored fraud prevention measures. The piece also suggests best practices for mobile fraud prevention, emphasizing the need for a comprehensive understanding of cross-device user behavior.
The When, Why and How of Mobile Fraud Prevention
- 1. THE WHEN, WHY & HOW OF MOBILE FRAUD PREVENTION JUNE, 2015 JON SPEER / SR. PRODUCT MARKETING MANAGER
- 3. 3 GLOBAL IOVATION TRAFFIC S H I F T I N G D I G I T A L C H A N N E L 18% 22% 25% 2% 2% 2%8% 11% 14% 73% 66% 59% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 2013 2014 2015 Mobile Web Desktop App Mobile App Desktop Web
- 4. 4 MOBILE APP ADOPTION T R A N S I T I O N F R O M D E S K T O P T O M O B I L E 76%
- 5. 5 MOBILE APP ADOPTION T R A N S I T I O N F R O M D E S K T O P T O M O B I L E Shopping Social Health & Fitness Financial 174%
- 6. 6 MOBILE APP ADOPTION T R A N S I T I O N F R O M D E S K T O P T O M O B I L E Shopping Social Health & Fitness Financial 103%
- 7. 7 MOBILE APP ADOPTION T R A N S I T I O N F R O M D E S K T O P T O M O B I L E Shopping Social Health & Fitness Financial 89%
- 8. 8 MOBILE APP ADOPTION T R A N S I T I O N F R O M D E S K T O P T O M O B I L E Shopping Social Health & Fitness Financial 26%
- 9. 9 GLOBAL IOVATION TRAFFIC M O B I L E A P P T R A F F I C G R O W T H ( Y O Y ) 0% 10% 20% 30% 40% 50% 60% Q3 14 Q4 14 Q1 15 Q2 15 Travel and Leisure Retail Logistics Interactive Gaming Financial Services
- 11. 11 US MOBILE PAYMENTS F O R R E S T E R R E S E A R C H $42.6B $90.7B$3.7B $34.2B $5.3B $16.8B $0B $20B $40B $60B $80B $100B $120B $140B $160B 2014 2019 Remote Payment Proximity Payment Peer-to-Peer Transfer Source: Forrester Research Mobile Payments Forecast 2014 to 2019 (US)
- 12. 12 AUTHENTICATION ADOPTION T H R E E T Y P E S O F A U T H E N T I C A T I O N Password Managers 2nd Factor (OTP, Device) 3rd Factor (Biometrics) REMEMBER THIS DEVICE
- 13. MOBILE THREATS
- 14. 14 PLATFORM VULNERABILITIES International banks issue SIM swap fraud alerts Memory & Stored Data
- 16. 16 EBAY 145,000,000 TARGET 70,000,000 ADOBE 36,000,000 PREMERA 11,000,000 ANTHEMJPMC 76,000,000 ANTHEM – February, 2015Home Depot – Sept 2014 56,000,000 Sony – Dec 2014JPMC – July 2014 HOME DEPOT 78,800,000 SONY 10,000 STOLEN CREDENTIALS
- 17. 17 THREATS ROGUE APPS Legitimate app stores by the number: US – 50+ Global – 300+
- 18. 18 MOBILE GAMBLING J U N I P E R R E S E A R C H CONVENIENCE • Users have their mobile device nearly all the time SPEED • With 3G and now 4G, the real time data access becomes ideal for gambling EXPERIENCE • Bigger screen display and beyond basic text payment DRIVERS BEHIND THE GROWTH
- 19. MOBILE FRAUD
- 20. 20 MOBILE PAYMENT FRAUD T A K I N G A D V A N T A G E O F C A R D N O T P R E S E N T Mobile capabilities are outpacing risk mitigation measures EMV widely expected to push more fraud to CNP
- 21. 21 MOBILE PAYMENTS FRAUD CARD PROVISIONING Digital Cash from Stolen Credit Cards Friendly Fraud Collusion PEER-TO-PEER Duplicate Deposits • Multiple Channels • Multiple Banks REMOTE DEPOSIT CAPTURE Verification Difficult for Mobile Wallets
- 22. 22 IOVATION CONSORTIUM 0.54% Fraud Rate Mobile VM: caught 4X fraud Global Carriers w/ highest fraud: tiGo (Ghana) MTN (Nigeria, Ghana) Kcell (Kazakhstan) MegaFon (Russia) Top Fraud: Credit Card Phishing/Spam Payment Account Takeover Over 1 Billion Mobile Transactions
- 23. 23 Lack of major mobile fraud levels today does not reduce the risk potential MOBILE FRAUD MYTHS VS. REALITY
- 24. PREVENTION
- 25. 25 GARTNER’S 5 LAYERS OF FRAUD PREVENTION 1 3 52 4 Endpoint-centric Navigation-centric Account-centric Cross-channels Entity Link Analysis Analysis of users and their endpoints Analysis of navigation behavior and suspect patterns Analysis of anomaly behavior on a per-channel Analysis of anomaly behavior correlated on a cross-channel basis Analysis of relationships to detect organized or collusive criminal activities
- 26. 26 MOBILE FRAUD PREVENTION O N L I N E F R A U D S O L U T I O N S M U S T B E T U N E D T O M O B I L E Same Approach Applied Differently Across Multiple Devices Fraud is fraud High level business rules Different type of operating system Different type of network Different type of user engagement Assume a cross-device user
- 27. 27 BEST PRACTICES M O B I L E F R A U D P R E V E N T I O N Mobile is not one channel
- 28. 28 BEST PRACTICES M O B I L E F R A U D P R E V E N T I O N Mobile is not one channel Leverage the power of the SDK
- 29. 29 BEST PRACTICES M O B I L E F R A U D P R E V E N T I O N Mobile is not one channel Leverage the power of the SDK Even hardware-based identifiers can be changed
- 30. 30 BEST PRACTICES M O B I L E F R A U D P R E V E N T I O N Mobile is not one channel Leverage the power of the SDK Even hardware-based identifiers can be changed Be aware of the abuse potential of some tools
- 31. 31 BEST PRACTICES M O B I L E F R A U D P R E V E N T I O N Mobile is not one channel Leverage the power of the SDK Even hardware-based identifiers can be changed Be aware of the abuse potential of some tools Geolocation… Trust but verify
- 32. Q&A UPCOMING EVENTS CUSTOMER WEBINAR SERIES JUNE 24 DIXONS CARPHONE FRAUD FORCE SUMMIT OCT 11-13, PORTLAND, OR LEND 360 OCT 13-16, ATLANTA, GA MONEY 2020 OCT 25-28, LAS VEGAS, NV