The document discusses loyalty fraud and presents strategies to make human-device interactions more secure. It notes that loyalty fraud has significantly increased in recent years, with attacks tripling from 2016-2017. Current authentication methods are easily bypassed by fraudsters. The document proposes using passive biometrics and behavioral analysis with machine learning to provide continuous authentication, separate human and bot activity, and improve security while maintaining a seamless user experience. This new approach would help to detect uncaught fraud and reduce false positives seen in traditional rule-based solutions.

1. Making the human-device
experience seamless and secure
Lewis Duker - Digital Fraud, Account Executive
LFPA Spring Conference, 2019, #LoyaltyFraud

2. Loyalty Fraud in Numbers
“nearly 40% of traffic on travel-
related websites comes from
impersonator bots”
- RSA Security, 2019
LFPA Spring Conference, 2019, #LoyaltyFraud
Value of
loyalty
rewards
worldwide
$238b
80%
Frequent Flyer
fraud is
discovered by
accident
“Almost 89& of UK
consumers are a member
of a loyalty scheme”
- Statista, 2016
From 2016-17
attacks
TRIPLED
with
48%
being hit by
ATO
costing
$2.3b
worldwide

3. Why?
Fraudsters are looking for easier
targets
Authentication that is easily
bypassed
Users access accounts infrequently
Monetization has been automated
LFPA Spring Conference, 2019, #LoyaltyFraud

4. The Fraud Flow: Account Takeover
LFPA Spring Conference, 2019, #LoyaltyFraud

5. Why are loyalty programs so vulnerable?
LFPA Spring Conference, 2019, #LoyaltyFraud

6. The Dark Net
LFPA Spring Conference, 2019, #LoyaltyFraud

7. LFPA Spring Conference, 2019, #LoyaltyFraud
YouTube

8. LFPA Spring Conference, 2019, #LoyaltyFraud

9. The Cost of
Friction
LFPA Spring Conference, 2019, #LoyaltyFraud

10. Gaps in Current Tools
LFPA Spring Conference, 2019, #LoyaltyFraud
Authentication only at login
Transactional Analysis credentials
Rule-based solutions = False Positives
Customer experience

11. The Ideal Seamless & Secure
Loyalty Program
LFPA Spring Conference, 2019, #LoyaltyFraud
PASSIVE BIOMETRICS
EMULATOR DETECTIONBOT DETECTION
BEHAVIORAL ANOMALIES

12. A New Approach: Behavioral Biometrics
LFPA Spring Conference, 2019, #LoyaltyFraud
Passive & continuous authentication
Behavioral analysis
Machine learning
Separate human from non-human
Catch undetected fraud
Device proofing
Improve user experience
Increase transaction rate

13. Key Takeaways
LFPA Spring Conference, 2019, #LoyaltyFraud
ADAPTIVE SEAMLESS CONTINUOUS

14. Thank You
Lewis Duker
Digital Fraud, Account Executive
lewis@securedtouch.com
www.securedtouch.com
LFPA Spring Conference, 2019, #LoyaltyFraud