As digital payments continue to increase in popularity, businesses across the globe are looking for ways to increase approvals of these transactions while preventing fraud and delivering a seamless payment experience for their customers.
EE, the largest mobile network in the UK, understands how difficult it is to strike the perfect balance between these three key pillars of e-commerce, so they selected Vesta to manage their card-not-present top-up services. Thanks to Vesta's advanced approval enhancement and fraud prevention technology, EE increased its card not present approval rate by over 10% with zero fraud liability.
Vesta also worked within the 3D Secure Framework with 2-Factor Authentication to deploy a proprietary orchestration layer that reduced 3D Secure challenges by 30% while ensuring a frictionless payment experience for EE's customers.
How AI, OpenAI, and ChatGPT impact business and software.
How the UK's #1 Mobile Network Enhanced Its Approval Rate by 10%, with Zero Fraud Liability
1.
2. Who is Vesta
We’re a global Fintech pioneer with 25 years
of expertise in payment fraud protection & digital fraud
detection through the customer lifecycle
3. Who is Vesta
Our guaranteed services eliminate the fear of fraud
empowering ecommerce merchants to grow revenue
4. Advanced Artificial Intelligence Unmatched Consortium Data
Unique customer fingerprint
links sessions together.
General session metrics
(e.g., time spent on session, number of
pages viewed, etc.).
Capture key events
(e.g., registration, login, update profile,
loyalty account interaction, etc.).
Deep Link analysis tracks fraud network and
identifies users when they change devices or
networks. Detect fraudulent and unexpected
events at early stages.
Cutting-edge machine learning algorithms are
trained automatically and are constantly
updated in the online platform for optimal
performance, Patented technology improves
the accuracy of the analysis.
An end-to-end automated Machine learning
pipeline, allowing our data scientist to train
multiple models in hours instead of weeks.
Review alerts to provide labels for training
machine learning models, allowing for faster
fraud detection.
Unmatched Consortium Data.
7. EE is the most popular mobile network in the UK (22%) with more than 30M customers (5.5M
prepaid) and more than 500 stores across the UK
How to migrate more EE prepaid customers
from indirect retail channel(s) to direct
channel(s), maintaining a best in class
customer experience & better understanding
its customer base
Before Vesta
In-house Fraud Management resulted in more than 1 in 10 payment requests being denied due to the fear of fraud
• Manual rules associated with transaction, value and thresholds
• Complex integration with multiple fraud vendors, inputs & latency challenges
• Only domestic cards accepted
• Heavy reliance on 3D Secure v1
• Manual review on MOTO channels (Live Agent & IVR)
• Feature gaps
• Fraud & Chargeback liability
1 2 How to control CNP fraud without negatively
impacting payment approval & denying legitimate
customers
The Challenge
8. A holistic, highly flexible, multi-layered approach to simplify the burden for our business customers
• Responsive HPP for
Web/Mobile
• Hosted IVR
• Hosted CSR UI
• PCI compliant
• Configuration centre
• Omni-channel
Payment Guarantee
against all CNP
transactions)
• Advanced ML models
• Real-time risk analysis
• Standalone 3D
Secure MPI
• Risk based invocation
of 3D Secure
• Leveraging all
available exemption
• Domestic &
International cards
• Apple Pay & PayPal
• New options include
QR codes & Open
Banking
• Text2Pay
• IVR with stored
payment device
• Direct Bundle
purchase
(Simple Payments)
• Account Updater
• One-click payments
for Web & App
• Optimised customer
experience &
conversions
• Webhook Event
notifications
• API (recurring trans)
• Direct flows / Re-
direct flows
• Plug-ins
• Multiple Acquirer set
up (DR/Approvals)
• Failover mechanism
• Conversion/KPI
Analysis
• 24x7x365 Global NOC
9. 1. International Revenue Share Fraud
• Fraud ring purchase SIM cards & top up with stolen cards purchased on dark web
• Prepaid credit used to ring premium rate number (they own) in less regulated region
• Inter-carrier billing/Premium rate terminated calls now monetized & ‘legitimately’ accessible
2. Bulk SIM sales
• Fraud ring purchase 200-500 SIM cards in bulk on eBay
• Stolen cards used to top up SIM cards with high monetary value e.g. £30
• SIM cards sold on high-street or to tourists at discounted price e.g. £15 for cash
3. Account Takeover (ATO) attack
• Account is hacked through phishing/ MITM / Sim Swap fraud
• Authenticated account with stored card on file used to purchase credit for multiple prepaid accounts to be used for use case 1 or 2 above
• SIM cards sold on high-street or to tourists at discounted price e.g. £15 for cash
4. First Party ‘Friendly Fraud’
• Real customer using their own payment card(s)
• Tops up their numbers, friends & family etc. and then looks to chargeback transactions claiming ‘it wasn`t me’ or they had not requested top ups
• Growing trend & behaviour heightened by Covid / economic circumstances
10. Leveraging all available exemptions is key to driving higher approval rates
Low Value exemption threshold e.g. Under £30. Please note that this exemption doesn`t apply if either a customer has conducted either 5x
online transactions since the last challenge or if the total value of transactions since the last challenge exceeds £100. In these scenarios, a
challenge will be invoked
Low Risk payment exemption threshold e.g., Payment provider or bank`s overall fraud rate for card payments do not exceed
0.13% to exempt transactions under £100 | 0.06% to exempt transactions under £250 | 0.01% to exempt transactions under £500
Merchant Initiated transaction (MIT)
e.g., Recurring billing or Instalment based
transactions initiated by the merchant
Mail Order Telephone Order
(MOTO transactions)
e.g., Live Agent/Call centre, IVR, SMS etc.
Real-time Transaction Risk Analysis
Adoption of effective & risk-based analysis to
categorise transaction as low risk