Vonage fraud protection with network API and generative AI | Amazon Web Services

Summary

The video script introduces Fraud Defender, a solution by Vonage, which leverages AWS AI and generative AI to combat identity theft and telecommunications fraud. It discusses challenges faced by organizations and details a cloud-native, serverless architecture that enhances security without adding user friction. The system uses Amazon Bedrock for feedback on transactions, silent authentication, and Amazon Recognition for facial verification, integrating network APIs for real-time insights to protect against fraud while making the authentication process smarter and more secure.

Takeaways

• 🌟 Vonage is partnering with AWS to introduce Fraud Defender, an innovative solution leveraging AWS AI/ML and generative AI technologies.
• 🛡️ The primary goal of Fraud Defender is to tackle challenges in identity theft, account takeover, and telecommunications fraud within the financial sector.
• 💡 Vonage's solution uses a cloud-native, serverless architecture deployed on AWS, offering customization and ease of purchase through the AWS Marketplace.
• 🔍 Fraud protection is enhanced by real-time network insights provided by Vonage's APIs, which are based on the Camara Network APIs.
• 🤖 Amazon Bedrock, a generative AI and large language model (LLM), is utilized to analyze transactions and provide feedback on their legitimacy.
• 🔄 The system creates a feedback loop, using insights from Amazon Bedrock to refine Fraud Defender's responses to fraudulent activities.
• 📞 Phone number verification is a key component, checking against Fraud Defender's knowledge base to identify potentially fraudulent numbers.
• 📍 Device location verification ensures that the user's claimed location matches the actual location data from telecom networks, adding a layer of security.
• 🔑 Silent authentication offers a secure method to replace one-time passwords, reducing the risk of social engineering attacks.
• 👤 Amazon Recognition uses facial recognition for user authentication, including a liveness check to prevent the use of stolen photos or videos.
• 🔄 The integration of generative AI allows for continuous improvement of security measures, adapting to new threats and maintaining an optimal balance between user convenience and fraud prevention.

Q & A

What is the role of Chad Hrin in the context of the script?

Chad Hrin is the Principal Solutions Architect with AWS, focusing on Communications as a Service (CaaS) and generative AI. He introduces the partnership with Vonage and their solution, Fraud Defender.

What is Vonage known for in the context of the script?

Vonage is known for being an innovative and progressive partner that offers Communication Platform as a Service (CPaaS) solutions and has developed Fraud Defender, a solution that leverages AWS AI and ML technologies.

What challenges does Vonage's Fraud Protection Solution address?

The solution addresses challenges related to identity theft, account takeover, and telecommunications fraud, which can result in financial losses and brand damage for organizations.

What is the significance of generative AI in the Fraud Defender solution?

Generative AI plays a crucial role in Fraud Defender by providing real-time insights and feedback on transactions, helping to identify fraudulent activities and improve the system's response to such threats over time.

How does the architecture of the Fraud Defender solution benefit customers?

The architecture is cloud-native and serverless, deployed on AWS, allowing customers to purchase through the AWS Marketplace and benefit from its customization and advantages.

What is Amazon Bedrock, and how does it relate to Fraud Defender?

Amazon Bedrock is a generative AI and large language model (LLM) that provides feedback on transactions to determine if they were fraudulent. This feedback is used to enhance Fraud Defender's capabilities.

What is the purpose of the silent authentication process in Fraud Defender?

Silent authentication is a secure process that can replace one-time passwords, preventing social engineering and providing a better guarantee of the phone line used for user authentication.

How does Amazon Recognition contribute to the user authentication process?

Amazon Recognition contributes by performing user authentication based on facial recognition, including a liveness check to prevent fraudsters from using stolen photos or videos for authentication.

What are the three Network APIs mentioned in the script, and what do they provide?

The three Network APIs are number verification, SIM swap, and verify location. They provide real-time insights into the telecommunications network, helping to identify fraudulent activities.

How does the Fraud Defender solution reduce user friction while increasing security?

By using mechanisms like silent authentication and facial recognition, Fraud Defender reduces user friction while increasing security only when necessary, based on insights indicating a potential fraudulent attempt.

What is the long-term impact of using generative AI in Fraud Defender?

The use of generative AI in Fraud Defender allows the system to become smarter, more intelligent, and more predictive over time, leading to increased security and fine-tuned parameters that match the perceived risk on the network.