It’s safe to say that the customer support industry—also referred to as customer success—has undergone a significant transformation with the advent of generative AI (GenAI). This technology has not only improved customer experiences; it has also streamlined operations for businesses overall.
At the same time, the identity verification (IDV) sector has seen parallel advancements, leveraging AI to enhance security and user experience. Let’s explore five ways generative AI has reshaped customer success and draw comparisons to its impact on identity verification.
1. Personalized interactions
In customer support, generative AI excels at creating tailored responses to individual customer inquiries. Through the analysis of past interactions, purchase history, and specific requirements, AI can generate highly personalized messages that resonate with each customer. This level of customization inevitably leads to improved customer satisfaction and loyalty.
By that same token, in the IDV industry, generative AI enables an end user’s verification process to be completely personalized. The technology adapts the verification steps based on the user’s risk profile, device, location, and historical data. For instance, a returning user from a trusted device might experience a streamlined verification process, while a new user from an unfamiliar location might face additional security checks.
2. Automated task handling
GenAI has significantly reduced the workload on human customer support agents by automating routine tasks. It can handle common inquiries, process refunds, and update customer information without human intervention. This automation allows human agents to focus on more complex issues that require a human touch—empathy and critical thinking.
In the IDV world, generative AI automates numerous verification tasks. It can process identity documents, extract relevant information, and cross-reference data with external databases in seconds. This automation accelerates the onboarding process for legitimate users while maintaining the highest possible security standards.
3. Real-time insights & proactive support
AI-powered customer support systems can analyze vast amounts of data in real-time, providing insights that help anticipate customer needs. This capability allows businesses to offer proactive support, addressing potential issues before they escalate into more complicated issues.
The IDV industry benefits from similar real-time analysis capabilities. Generative AI can continuously monitor user behavior patterns and transaction data to detect anomalies that might indicate fraud attempts. This proactive approach allows IDV systems to flag suspicious activities and trigger additional verification steps when necessary, enhancing security without significantly impacting the user experience for legitimate customers.
4. Multilingual assistance & access
Multilingual capabilities powered by GenAI technology enables customer support teams to offer assistance in numerous languages without large multilingual teams, facilitating global reach and cost-efficiency. AI-powered systems have the ability to maintain consistent quality across languages.
In IDV, multilingual AI allows for universal access, accurate processing of documents in various languages, and improved user guidance. It can additionally aid in fraud detection by identifying linguistic inconsistencies and help navigate multi-jurisdictional regulatory requirements. This technology is breaking down language barriers, engendering a more inclusive digital ecosystem in both sectors.
5. Predictive analytics for anticipating needs
Generative AI’s predictive capabilities allow customer support teams to anticipate customer needs based on historical data and current trends, thereby enabling businesses to prepare resources, adjust strategies, and offer timely solutions before customers even reach out.
The IDV industry leverages predictive analytics in a similar manner to anticipate and prevent fraud. Using patterns it identifies in user behavior, transaction history, and known fraud attempts, AI can predict potential security threats. The predictive power of this technology allows IDV systems to implement preemptive measures, such as adjusting risk thresholds or implementing additional verification steps for high-risk scenarios.
Synergy unlocked
The parallels between AI’s impact on customer success and identity verification highlight a broader trend in technology adoption. Both industries aim to balance user experience with security and efficiency. In customer support, the goal is to provide quick, accurate, and personalized support while managing large volumes of inquiries. In IDV, the objective is to ensure secure and accurate identity verification while minimizing friction for legitimate users.
Generative AI has proven to be a powerful tool in achieving these goals. It enhances personalization, automates routine tasks, provides real-time insights, facilitates natural language interactions, and leverages predictive analytics to anticipate needs and threats.
With generative AI advancing by leaps and bounds, we can expect even more sophisticated applications in both customer support and identity verification. Future developments might include AI systems that can seamlessly switch between customer support and identity verification roles, providing a unified experience for users across various digital interactions.
Changing with the times
The transformation brought about by generative AI in these industries underscores the importance of embracing technological advancements. Simply put, companies that effectively integrate AI into their customer support and IDV processes will hopefully see improved customer satisfaction, enhanced security, an improved regulatory posture, and increased operational efficiency.
The parallel advancements in customer success and identity verification demonstrate the versatility and power of generative AI. As this incredible technology continues to evolve, it will in turn give rise to further innovations to both industries, shaping the future of digital interactions and security.
About the post:
Images and videos are generative AI-created. Prompt: Ultrawide shot, a child looks out from inside of a glass elevator over a vast, multistory ultramodern hotel lobby. Tools: Midjourney, Luma.
About the author:
Lisa Hern is IDVerse’s Head of Customer Success for North America. With over 15 years of experience in customer support, she is a proven leader in the space. A relentless customer advocate and cultivator of relationships, Lisa has also been certified as a naturalist in the state of California. She is based in Sunnyvale, CA.
