ECOMMERCE ACCOUNT PROTECTION AND FRAUD DETECTION

eCommerce Account Protection and Fraud Detection

THE CHALLENGES WITH ECOMMERCE FRAUD PREVENTION

Fraudsters are becoming more sophisticated, continuously evolving to evade detection mechanisms. By targeting gaps in merchants’ business models they continue to find new ways to execute their attacks, like account takeover, coupon fraud, new account fraud, refund fraud, loyalty fraud and more.

 

THE GAP IN ONLINE FRAUD PREVENTION LEADS TO LATE DETECTION

Traditional fraud detection relies on static data at the point of payment. Data gathered from the device and network, coupled with transaction and historical data means they cannot compete with evolving tactics.

  • Fraudsters evade detection by continuously adapting their attack flows to fly under the radar of known detection mechanisms. 
  • They can take over legitimate user accounts or open fake accounts to age them and enhance reputation. 
  • In order to circumvent velocity based detection, they deploy low activity volumes per device, account or IP address. 
  • Off-the-shelf tools like emulators or anonymous browsers are used to beat device and/or networking detection 

Using static data to block these highly sophisticated attackers just doesn’t cut it.

WHY CHOOSE SECUREDTOUCH?

  • 100s Millions DAU

  • Trusted by Top 10 eCommerce Merchants in the USA and Europe

  • 10x ROI

ADAPTIVE, REAL-TIME FRAUD DETECTION

SecuredTouch provides pre-transaction detection. The solution gathers and analyzes data continuously the moment a session begins and responds in real-time before a transaction can take place. Conscious and unconscious behavioral data patterns identify user intent to detect fraud earlier in the customer journey.

 

eCommerce Account Protection and Fraud Detection Using Machine Learning

Proprietary machine learning algorithms provide coverage for both manual and automated attack vectors. Using rich data sources, the solution balances protection and customer experience.

  • Out-of-the-box models
    Ensuring zero-day detection to provide ROI from the get-go, differentiating between human and non-human behavioral patterns of bots, emulators, cloning applications & tampered devices
  • Tailor-made models
    Supporting the unique customer journey per customer to reveal behavioral anomalies idiosyncratic of manual techniques
  • Behavioral data
    A rich data source providing unique insights into behavioral patterns
  • Data visibility
    Gain insights into WHAT and WHY an ML decision was made
  • Data enrichment
    Fraud indicators and session actions enhance and optimize decision making models
  • Accurate and reliable
    Using granular data sources to support precise and effective responses
  • Always-on
    Continuous monitoring provides a holistic view of the user journey
  • Real-time
    Feedback loop sends immediate alerts the moment suspicious activity is flagged

HOW DOES IT WORK?

  • 1

    SecuredTouch SDKs gather behavioral, device, usage and network data from the moment a session begins

  • 2

    Proprietary machine learning models continuously monitor activities and interactions invisibly throughout the session and return a trust score.

  • 3

    Merchant can fetch the trust score along with rich data indicators at any given time throughout the user journey

  • 4

    Merchant’s risk engine makes decision in real time based on the score and flexible thresholds: good users are seamlessly identified first, bad or suspicious users are either blocked or challenged

SECURED TOUCH - DETECTING FRAUD WITH BEHAVIORAL BIOMETRICS SECURED TOUCH - DETECTING FRAUD WITH BEHAVIORAL BIOMETRICS