3D-Secure 2.0 - User Behavior Analysis to Block Fraud

3D-Secure 2.0 is an advanced version of the additional authentication system designed to increase the security of online payments and reduce the risk of fraud. One of the key features of 3D-Secure 2.0 is the use of user behavior analysis to identify suspicious transactions. Let's look at how this technology works, what data it collects, and how it helps prevent fraud.

1. What is 3D-Secure 2.0?​

3D-Secure 2.0 is an authentication protocol that provides an additional level of security when making online payments. It was developed to replace the older version (3D-Secure 1.0), which required entering a static code (such as an SMS or password).

The main advantages of 3D-Secure 2.0 are:

• Less friction for users: In most cases, authentication happens automatically without the need to enter a code.
• Real-time data analysis: The system analyzes user behavior and other parameters to assess risk.
• Compatibility with modern devices: Support for mobile payments, biometrics and other technologies.

2. How does user behavior analysis work?​

User behavior analysis is the process of collecting and analyzing data about a customer’s actions during a transaction. The goal is to determine whether the current activity matches the cardholder’s usual behavior. If the system detects deviations, the transaction may be blocked or sent for additional verification.

a) What data is collected?​

The system collects a variety of parameters that help assess the risk of fraud. Here are the main categories of data:

1. Device information:
   • IP address devices.
   • Device type (smartphone, computer, tablet).
   • Operating system and browser version.
   • Unique device identifiers (e.g. IMEI, MAC address).
2. Geographic data:
   • User location (by IP or GPS).
   • The distance between the current location and the card registration address.
3. Behavioral patterns:
   • Typing speed (for example, entering a card number or code).
   • Mouse movements or screen touches.
   • Site navigation habits (e.g. how long a user spends on a checkout page).
4. Historical data:
   • Transaction frequency.
   • Regular purchase amounts.
   • Preferred categories of goods or services.
5. Other factors:
   • The time of day the transaction occurs.
   • Using a proxy or VPN.
   • The presence of antivirus or security software on the device.

b) Example of behavior analysis​

• The cardholder typically makes purchases of up to $200 per day.
• Today, someone is trying to make a $1000 transaction from another country using his card.
• The system detects discrepancies in geography, amount and frequency of transactions and requests additional authentication.

3. How does the system make a decision?​

After collecting the data, the system uses machine learning and artificial intelligence algorithms to assess the risk. The decision is made depending on the level of trust in the transaction:

1. Low risk:
   • The transaction is approved automatically without additional verification.
   • For example, if a user makes a purchase from a familiar device and at a familiar time.
2. Average risk:
   • Additional authentication is required (e.g. via SMS code or biometrics).
   • For example, if a user makes a purchase from a new device.
3. High risk:
   • The transaction is blocked or sent for manual review.
   • For example, if the card is used from another country or at an unusual time.

4. Advantages of 3D-Secure 2.0​

a) For users​

• Security: Protection from fraudsters and unauthorized transactions.
• Convenience: Most transactions are completed without the need to enter a code.
• Transparency: Users are notified of suspicious activity.

b) For business​

• Reduced Fraud: Less losses from fraudulent transactions.
• Improved Conversion: Automatic authentication reduces cart abandonment.
• Compliance: Helps meet PCI DSS and PSD2 (in Europe) requirements.

c) For banks​

• Customer Protection: Reduce disputed transactions.
• Cost reduction: Less expense on fraud investigation.

5. Real life example​

Scenario 1: Legal transaction​

• The user makes a purchase on a website where he has already registered.
• The system recognizes its structure, geography and behavior.
• The transaction is approved automatically without requiring a code.

Scenario 2: Suspicious Transaction​

• The fraudster tries to use the stolen card to buy an expensive item.
• The system detects:
  • New IP address.
  • An unusually high amount.
  • Fast data entry.
• The transaction is blocked and the bank sends a notification to the card owner.

6. Technologies used in 3D-Secure 2.0​

a) Machine learning​

• Analyzing large amounts of data to detect anomalies.
• Adapting to new fraud methods.

b) Biometrics​

• Use fingerprints, face recognition or voice recognition for authentication.

c) Geolocation​

• Determine the user's location to check for a match with map data.

d) Contextual analysis​

• Taking into account the time of day, transaction history and other factors.

7. Conclusion​

3D-Secure 2.0 is a powerful fraud prevention tool that combines user convenience and a high level of security. User behavior analysis allows the system to accurately identify suspicious transactions and minimize risks for all participants in the payment process.

If you want to learn more about how 3D-Secure 2.0 works or how to protect yourself from fraudsters, write!

How does 3D-Secure 2.0 work to protect against fraud?​

3D-Secure 2.0 is an advanced online payment authentication system that replaces the outdated 3D-Secure 1.0 (with one-time SMS codes). Its key feature is real-time user behavior analysis to block suspicious transactions.

How 3D-Secure 2.0 works​

1. Dynamic authentication​

The system evaluates the risk of the transaction and selects one of the scenarios:

• Seamless authentication (without entering a code) - if the risk is low.
• Two-factor verification (SMS, biometrics) - if the risk is high.

Example:
You buy a phone in a familiar store from your device → payment goes through without a code.
A stranger tries to buy an iPhone from a foreign IP → confirmation is required.

2. Behavior Analysis (Risk-Based Authentication)​

The system checks 100+ parameters, including:

• Device: Screen resolution, OS, browser, IP address.
• Behavior: Typing speed, usual purchase amounts, geolocation.
• History of transactions: Frequency of transactions, suspicious stores.

How does this prevent fraud?

• If the card is usually used in London, and here is a payment from Nigeria → blocking.
• If a user always spends $1000/month, and here it’s $10,000 per hour → confirmation is required.

3. Difference from 3D-Secure 1.0​

How does 3D-Secure 2.0 block carding?​

1. Automatic refusal in suspicious cases:
   • Purchasing digital codes (Steam, iTunes) from new devices.
   • Multiple transactions in a short time.
2. Integration with banking systems:
   • If the card is marked as stolen, the payment is declined even with the correct code.
3. Security for business:
   • Stores using 3DS2 do not suffer losses due to chargebacks.

Tips for users​

• Activate 3D-Secure 2.0 in your bank (if not activated automatically).
• Use trusted devices for payments - this reduces the risk of being asked for a code.
• Turn on transaction notifications in your bank's mobile app.

Important: The system is not perfect - some fraudsters still bypass the protection, but 3DS2 has reduced the success rate of attacks by 80% (Visa data, 2023).

What to do if the payment is blocked?​

1. Check your SMS/banking app - confirmation may be required.
2. Call your bank - sometimes they block by mistake.
3. Do not try to bypass the system - this may result in your card being blocked.

Need more details about secure payments? Ask!

3D-Secure 2.0 (3DS 2.0) is an updated security protocol for online payments that significantly improves transaction security and reduces the likelihood of fraud. One of the key features of 3DS 2.0 is the use of user behavior analysis and transaction context to make decisions about approving or blocking a transaction.

How does 3D-Secure 2.0 work?​

1. Transaction context analysis:
   • The 3DS 2.0 protocol collects transaction data such as the user's geolocation, the device from which the purchase is made, IP address, purchase history and other parameters.
   • This data is used to assess the risk of a transaction. For example, if a user makes a purchase from a new device or from an unusual location, the system may request additional authentication.
2. Authentication without interruption:
   • Unlike the previous version, 3DS 2.0 can automatically approve low-risk transactions without requiring a password or other action from the user.
   • This is achieved through the use of artificial intelligence and machine learning, which analyze user behavior and determine whether it is within the norm.
3. Additional authentication if required:
   • If a transaction appears suspicious, the system may request additional verification, such as entering a one-time password (OTP) or using biometric authentication (fingerprint scanner, facial recognition).

Benefits of 3D-Secure 2.0​

• Fraud Reduction: By analyzing transaction behavior and context, the system can effectively identify suspicious transactions and block them before completion.
• Improved user experience: Users are less likely to be prompted to enter passwords, making the payment process more convenient.
• Mobile Compatibility: 3DS 2.0 is optimized for use on smartphones and tablets, which is especially important in the era of growing mobile commerce.

Conclusion​

3D-Secure 2.0 represents a significant step forward in online payment security. By analyzing user behavior and transaction context, the protocol helps reduce fraud while improving user experience. This makes it an important tool for protecting both consumers and businesses in the digital age.