Money20/20 Vegas 2026: ElevenLabs' Lauren Kiefer on AI Voice in Banking

Quick Summary

As consumer demands for instant, multilingual support grow, financial institutions are turning to advanced artificial intelligence to bridge the gap. Lauren Kiefer of ElevenLabs explains at Money20/20 Vegas 2026 how the company's V4 model is delivering expressive, human-like voice interactions that allow banks to scale their customer service without increasing headcount.

How is AI voice technology evolving for financial services?

The launch of the V4 model represents a significant leap in AI capabilities, moving closer to passing the Turing test for voice. Lauren Kiefer notes that the technology has reached a point where it can meet the rising demand for 24/7 answers in any language. For banks, this means being able to serve a global customer base efficiently. The ElevenLabs stack is built to prioritise high quality and low latency, ensuring that the AI feels helpful and useful rather than acting as a traditional, frustrating automated system.

What real-world results are banks seeing from AI agents?

Financial institutions are already seeing measurable improvements in efficiency by deploying these agents into their systems of record. Lauren Kiefer highlights several examples:

• Admirals Bank: By using AI for loan settlement quotes, the bank reduced the process time from five minutes to just two and a half minutes.
• Customers Bank: The firm is using AI to handle customer enquiries 24/7 and is expanding the technology into internal coaching and enterprise-wide use cases.
• Revolut and Klarna: These brands have successfully integrated ElevenLabs technology by focusing on high-impact, high-volume use cases to drive business results.

How does ElevenLabs manage risk and compliance?

Guardrails are essential when deploying AI in a regulated environment. Lauren Kiefer explains that ElevenLabs uses a rule-based system to ensure that agents follow specific industry and bank-level regulations. Furthermore, the company maintains a human-in-the-loop approach, where complex or highly sensitive cases are always escalated to human staff. Before any agent goes live, it is rigorously tested in a sandbox environment or against a small percentage of the population to mitigate risk and ensure compliance.

What should banks consider before an agentic transformation?

For a successful deployment, Lauren Kiefer suggests that firms must first ensure their data is ready, as AI performance is heavily dependent on the quality of the input. She recommends that banks:

• Start with a narrow use case, such as frequently asked questions, where instant resolution provides the most value.
• Keep risk and compliance teams involved from the beginning to define tight guardrails.
• Ensure the firm retains control over the technology rather than treating it as a black box solution.
• Partner with vendors who provide embedded partnership and training for internal teams.

FF NEWS TAKE:

The transition from rigid phone trees to fluid, expressive AI agents marks a turning point for banking accessibility. By halving the time for complex tasks like loan settlements, ElevenLabs is proving that AI voice is no longer just a cost-saving tool for basic FAQs, but a sophisticated driver of operational speed. As trust in these systems grows through better latency and accuracy, the expectation for instant, human-like resolution will likely become the standard for the entire financial services industry.