Velocity abuse has become a pervasive issue in the Fiserv and FinTech industries. With fraudsters employing increasingly sophisticated tactics to exploit vulnerabilities in financial systems, it is crucial for stakeholders to implement robust preventative measures. As product managers, developers, and security experts in the financial technology and services sector, your objectives are to enhance security, protect user data, mitigate fraud, and retain user trust in your systems. This article will introduce the top 5 strategies to combat velocity abuse in the Fiserv and FinTech sectors.

Understanding the threat of velocity abuse is the first step towards devising protective countermeasures. Velocity abuse refers to fraudulent activities executed at high speeds, often through automated means, such as bots that exploit system vulnerabilities. This can manifest in various forms, like repeated login attempts, rapid account creation, or multiple fraudulent transactions. Failure to address these threats can lead to substantial financial losses, reputational damage, and a heightened risk of data breaches.

To help you navigate this challenge, we have identified the top 5 strategies for combating velocity abuse in Fiserv and FinTech. These approaches include device and browser fingerprinting, 3D liveness, IP geolocation and impossible travel, emulator and virtual machine detection, and advanced captcha and bot behavior biometrics AI. Each strategy has its advantages and limitations, emphasizing the need for an integrated approach to safeguard your systems against this growing threat.

The following sections will offer an in-depth analysis of each strategy, exploring their mechanics, pros and cons, and tactical implementation recommendations tailored to the Fiserv and FinTech context. By equipping you with this knowledge, our aim is to assist you in developing a comprehensive security plan that not only addresses velocity abuse but also effectively mitigates other potential risks to your platform.

In conclusion, combatting velocity abuse is an essential task for professionals in the Fiserv and FinTech sectors. By implementing the top 5 strategies outlined in this article, you can build more robust, secure systems that inspire user trust and reduce vulnerability to fraud. As threats continue to evolve, it is critical to stay informed about emerging trends, innovate continuously, and customize your security strategy to meet the specific needs of your organization.

Strategy 1: Device and Browser Fingerprinting

What is Device and Browser Fingerprinting

Device and browser fingerprinting is a technique used to uniquely identify users by analyzing the characteristics of their devices and browsers. This information can be utilized to track and authenticate users, as well as detect potential fraudulent activities, such as velocity abuse.

How does it work

1. Unique device and browser characteristics identification: Device and browser fingerprinting collects and analyzes information of various attributes, including hardware and software configurations, operating systems, browser versions, installed plugins, screen resolutions, and other unique features of the user's device.
2. Environment tracking: The collected data is then used to generate a fingerprint that is unique to the user's device and browsing environment. This fingerprint can be tracked across different sessions to monitor user activities and detect potential fraudulent behavior.

Pros & Cons

Pros:

• Mitigating credential stuffing attacks, ATO attacks, and social engineering attacks: By identifying deviations from a user's normal fingerprint, security systems can flag and block suspicious activities, such as repeated login attempts, account takeovers, or unauthorized transactions.
• Enhancing user experience: Fingerprinting can help streamline the login and authentication processes for customers by recognizing returning users, reducing the need for cumbersome authentication steps.

Cons:

• Limited effectiveness against sophisticated fraudsters: Fraudsters employing advanced evasion techniques can manipulate device and browser characteristics to generate fake or altered fingerprints, potentially leading to false negatives.
• Privacy concerns: Device fingerprinting may raise privacy concerns for some users who are uncomfortable with invasive tracking methodologies.

Tactical Implementation

1. Incorporate fingerprinting libraries/frameworks into platforms: Choose a reputable device and browser fingerprinting solution that meets your specific security requirements. Several open-source and commercial fingerprinting libraries, such as FingerprintJS or OWASP Amass, offer rich feature sets and customization options for integration.
2. Monitor for deviations from normal user behavior and detect device anomalies: Establish baseline behavioral patterns for your users based on historical fingerprint data. Leverage monitoring tools and analytics to track real-time user activities and detect any anomalies or deviations from their established patterns, flagging suspicious events for further investigation and potential countermeasures.

Strategy 2: 3D Liveness

What is 3D Liveness

3D Liveness is a biometric authentication technique that leverages advanced computer vision and machine learning algorithms to identify genuine human faces in real-time. The technology analyzes a user's facial structure and other unique attributes, ensuring that the person interacting with the Fiserv or FinTech platform is physically present and not using a static image, video, or mask to deceive the system.

How does it work

3D Liveness works by capturing a short video or sequence of images of the user's face during the account registration or authentication process. The algorithm then extracts unique 3D facial features, such as skin texture, depth, and contours, and compares them with the stored profile to determine if the subject is a legitimate user or an imposter.

Furthermore, 3D Liveness ensures that the user's face is captured under varying illumination settings, angles, and expressions to add an extra layer of security and robustness to the verification process.

Pros & Cons

Pros:

1. Effectiveness against synthetic identity fraud: By ensuring that users are physically present and possess unique facial features, 3D Liveness makes it difficult for fraudsters to create fake accounts using stolen or synthetic identities.

   
   

2. Prevention of fake account enrollment: The technology helps in limiting the number of falsified accounts, thereby reducing the potential for velocity abuse as well as fraud-related losses.

   
   

3. Continuous authentication: 3D Liveness can be integrated across various stages of the user's journey within the platform, increasing overall security without compromising the user experience.

   
   

Cons:

1. Hardware and software requirements: Implementing 3D Liveness requires users to have devices with the necessary hardware, such as front-facing cameras and high-resolution screens. Furthermore, users need to ensure that their devices support the latest software and security updates.

   
   

2. Privacy concerns: Some users may be concerned about the privacy implications of sharing their biometric data with Fiserv or FinTech providers.

   
   

Tactical Implementation

To integrate 3D Liveness into your Fiserv or FinTech platform, consider the following approaches:

1. Implement SDKs/APIs of 3D Liveness solutions: Several vendors offer robust and ready-to-use software development kits (SDKs) and application programming interfaces (APIs) that can be easily integrated into your existing platform. These solutions include facial recognition, liveness detection, and data encryption to protect user information.

   
   

2. Develop a custom mobile app or web interface: Depending on your platform's specific requirements and target audience, you can opt to develop a custom mobile application or web interface that incorporates 3D Liveness technology. This approach ensures a seamless user experience while maintaining a high level of security and robustness in the system.

   
   

3. Test and refine the technology: To increase adoption rates and maintain user trust, it is crucial to test the 3D Liveness solution extensively before deployment. Conduct user testing to identify potential usability issues and fine-tune the technology to improve its accuracy and reliability.

   
   

4. Stay abreast of the latest advancements: 3D Liveness technology is continuously evolving, with new research and techniques being developed to enhance its effectiveness and accuracy. Stay informed of the latest developments and best practices to ensure that your implementation remains up-to-date and effective against the ever-evolving threats.

   
   

Strategy 3: IP Geolocation and Impossible Travel

What is IP Geolocation and Impossible Travel

IP Geolocation is the technique of determining the geographic location of an Internet Protocol (IP) address. In the context of Fiserv and FinTech, IP Geolocation, along with Impossible Travel analysis, can be used to detect and prevent velocity abuse attempts by identifying instances where transactions are made from implausible geographical locations or at a rate that is physically impossible.

Impossible Travel refers to situations where a user appears to have traveled long distances within a short time frame, based on their IP geolocation data. This method can help detect unauthorized access, compromised accounts, and other fraudulent activities.

How does it work

IP Geolocation and Impossible Travel work by monitoring the IP addresses, geolocations, and velocity patterns associated with users' transactions. Various IP intelligence datasets and user behavior analytics can be integrated into the monitoring process to check for anomalies that could indicate fraud.

First, an IP geolocation dataset is used to map users' IP addresses to their approximate geographical location. Then, algorithms are applied to detect instances where a user has logged in from multiple geographical locations within a short time frame, suggesting that it's physically impossible for the user to have traveled between those locations. This could indicate that an attacker is attempting to gain unauthorized access to the user's account or conduct fraudulent transactions.

Pros & Cons

Pros:

1. IP Geolocation and Impossible Travel analysis can help prevent and detect real-time transaction tampering, distributed denial of service (DDoS) attacks, and account takeover (ATO) attempts, which are commonly associated with velocity abuse.

   
   

2. By identifying unusual patterns of user behavior that do not align with their usual geolocation data, this method can provide early warning signs of potential fraud or account compromise.

   
   

Cons:

1. There could be instances where geolocation data generates false positives, such as in cases of shared IPs, virtual private networks (VPNs), and roaming users. This can lead to legitimate users being flagged as potential fraud risks, which could negatively impact customer experience and trust.

   
   

2. Relying solely on IP Geolocation and Impossible Travel as a preventative measure may not be sufficient to address the full range of velocity abuse techniques employed by sophisticated fraudsters.

   
   

Tactical Implementation

To implement IP Geolocation and Impossible Travel analysis, follow these steps:

1. Subscribe to a reputable IP geolocation dataset provider. Make sure to choose one with comprehensive and accurate data, as well as regular updates. Some popular providers include MaxMind, IP2Location, and Neustar.

   
   

2. Develop algorithms to analyze geolocation data and detect unusual patterns. This would typically involve calculating the time difference between consecutive logins or transactions, and comparing it to the approximate travel time between the associated geographical locations. Set thresholds for acceptable time differences based on industry best practices and your organization's specific risk tolerance.

   
   

3. Integrate the IP geolocation dataset and the developed algorithms into your existing fraud detection and prevention system. This could involve enhancing your current fraud rules engine, or incorporating the IP geolocation and Impossible Travel detection into a machine learning-powered fraud detection solution.

   
   

4. Continuously monitor and adjust the effectiveness of the solution, taking into account evolving fraud tactics and potential changes in user behavior. This may involve tracking false positives, refining the algorithms, and considering additional data points to improve the overall performance of the system.

   
   

Strategy 4: Emulator and Virtual Machine Detection

What is Emulator and Virtual Machine Detection

Emulator and Virtual Machine (VM) Detection is a cybersecurity technique for identifying the use of emulators and virtual machines that attempt to impersonate legitimate users. Fraudsters often employ these tools to carry out velocity abuse, automated attacks, and the creation and operation of fake accounts on Fiserv and FinTech platforms.

How does it work

Emulator and VM detection work by examining system behavior, library calls, device characteristics, and response times to identify the subtle differences between legitimate users on actual devices and those using emulators or VMs. The detection system then flags or blocks suspicious activity, as appropriate, to prevent fraudsters from abusing the platform's resources and compromising user accounts.

Pros & Cons

Pros:

• Counters fraud tactics involving bot usage, automation, and fake account creation, which can erode user trust and damage platform reputation.
• Enhances the effectiveness of other security measures by targeting unique aspects of fraudster strategies involving emulators and VMs.

Cons:

• Complex implementation can make maintaining and updating the detection mechanism challenging, potentially impacting the system's effectiveness.
• False positives may occur if the detection algorithm incorrectly identifies a legitimate user as utilizing an emulator or VM, potentially leading to user inconvenience.

Tactical Implementation

To incorporate emulator and VM detection into your Fiserv or FinTech platform, follow these implementation guidelines:

1. Identify appropriate Emulator and VM detection libraries and tools tailored to your platform's unique needs. Some popular open-source and commercial options include BlueStacks Detection, Memu Detection, Xamarin Detection, and VMWare Detection tools. Research the available options in the context of your platform to find the best fit.

   
   

2. Integrate the selected tools into your platform's existing architecture, taking care to identify potential conflicts with existing security measures. Coordinate with your platform's development, security, and operations teams to ensure a seamless integration process.

   
   

3. Continuously maintain and update the detection heuristics to keep up with evolving fraud techniques. Fraudsters constantly adapt their tactics to bypass security measures, and staying informed about emerging trends and adapting your defense strategy is vital.

   
   

4. Regularly monitor and analyze detected activity to assess the effectiveness of the implemented emulator and VM detection system. Adjust the system's configuration and detection algorithms as needed to minimize false positives and maximize accurate detection.

   
   

5. Collaborate with industry partners and security community members to share information about emerging threats and techniques related to emulator and VM abuse in Fiserv and FinTech environments. This collaborative approach can help keep your platform prepared for new threats and ensure comprehensive protection against velocity abuse.

   
   

Strategy 5: Advanced Captcha and Bot Behavior Biometrics AI

What is Advanced Captcha and Bot Behavior Biometrics AI

Advanced Captcha systems are the evolution of traditional Captcha tests, which aim to differentiate human users from automated bots by presenting tasks that are easy for humans but difficult for machines, like solving a puzzle or recognizing objects in images. Bot Behavior Biometrics AI, on the other hand, is an emerging technology that analyzes user interaction patterns, such as mouse movements and keystrokes, to determine the possibility of bot activity.

Integrating Advanced Captcha systems and Bot Behavior Biometrics AI into a Fiserv or FinTech platform can significantly increase the system's resilience against automated attacks and velocity abuse.

How does it work

To implement Advanced Captcha and Bot Behavior Biometrics AI, Fiserv and FinTech professionals need to:

1. Integrate Captcha tests to user interfaces (UI) where sensitive user interactions occur, such as account creation, login pages, and high-volume transactions.
2. Utilize AI models and machine learning algorithms that analyze user behavior patterns, including input sequences, timings, movements, and more, to detect subtle differences between human and bot activities.

By combining Captcha tests with Bot Behavior Biometrics AI, the platform can enhance security measures and more accurately filter out bots from genuine users.

Pros & Cons

• Pros:

  
  
  • Advanced Captcha and Bot Behavior Biometrics AI can effectively block a majority of bots and automated attempts to access Fiserv and FinTech systems, thus reducing velocity abuse and potential security breaches.
  • These technologies continuously adapt and improve, making it increasingly difficult for fraudsters to bypass them through the use of sophisticated bots and scripts.
  
  

• Cons:

  
  
  • Integrating Captcha tests can sometimes reduce the user experience by adding extra steps in the user's interaction with the platform and potentially causing accessibility issues for users with disabilities.
  • False positives can occur, and legitimate users may be misclassified as bots, leading to unnecessary friction in their interaction with the platform.
  
  

Tactical Implementation

In order to implement Advanced Captcha and Bot Behavior Biometrics AI in a Fiserv or FinTech platform, professionals need to consider the following steps:

1. Select and integrate a Captcha library or tool: Several libraries and APIs are available for adding Captcha functionality to your platform. Choose one that fits your needs and integrates it into your platform's UI where necessary. Examples include Google's reCAPTCHA, hcaptcha, and the Distil Bot Defense API.
2. Implement machine learning models for bot behavior biometrics AI: Utilize AI models that analyze user interaction patterns and detect subtle differences between human and bot activities. Train the model on historical user data and update it regularly to improve accuracy.
3. Monitor and optimize AI performance: Continuously monitor the AI model's performance and fine-tune the parameters to minimize false positives and maximize detection rates.
4. Combine Captcha challenges with other security measures: When suspicious behavior is detected, implement additional verification steps, such as two-factor authentication, to further ensure the authenticity of the user.

By following these guidelines and integrating Advanced Captcha and Bot Behavior Biometrics AI into your platform, you can significantly reduce the risk of velocity abuse and protect your business and users against fraudsters and attackers.

Final Thoughts and Next Steps

In conclusion, the top 5 strategies to prevent velocity abuse in Fiserv and FinTech are:

1. Device and Browser Fingerprinting
2. 3D Liveness
3. IP Geolocation and Impossible Travel
4. Emulator and Virtual Machine Detection
5. Advanced Captcha and Bot Behavior Biometrics AI

Each of these strategies has its pros and cons, but combining them can create a robust solution that addresses a wide range of threats. To ensure maximum effectiveness, companies should:

• Adopt an integrated approach: Implement multiple security tactics to create a comprehensive and layered defense against velocity abuse and related fraud tactics.
• Identify company-specific needs: Tailor strategies to the company's unique requirements, considering factors such as user base, platform complexity, and specific fraud risks.
• Stay informed about emerging fraud trends: Regularly monitor industry news and attend conferences on cybersecurity to stay up-to-date on the latest tools and techniques for combatting velocity abuse and other online threats.
• Encourage continuous innovation: Foster a culture of innovation within your organization, and invest in research and development to stay ahead of the curve in protecting your users and maintaining trust in your platform.

By following these guidelines and implementing the top 5 strategies, Fiserv and FinTech professionals can effectively prevent velocity abuse and safeguard their users' data, ensuring a secure online environment for everyone.