5 Best Voice AI Agents for Banking in 2025

5 best voice AI agents for banking in 2025

Banks are under mounting pressure to transform their customer service operations. Financial services make up 25% of total spend on all global contact centers and over $100 billion in annual business process outsourcing (BPO) spend, yet traditional approaches struggle to keep pace with rising call volumes and customer expectations for instant, personalized service.

70% of banking executives predict agentic AI will have a "significant" impact or be a "game changer" that will have a profound effect on the future of banking and financial services. As compliance requirements tighten and operational costs climb, the right voice AI agent can mean the difference between leading the market or falling behind.

This guide evaluates the top five voice AI platforms transforming banking operations in 2025, examining their infrastructure, latency, compliance capabilities, and pricing models to help you select the solution that best fits your institution's needs.

Why banks need voice AI agents now

The shift to voice AI in banking isn't just about automation, it's about fundamentally improving how banks serve customers while managing risk and costs. The Voice Assistant market was valued at USD 4.18 billion in 2024 and is expected to grow from USD 4.85 billion in 2025 to USD 25 billion by 2035, with a CAGR of 16.08%. Meanwhile, the banking sector's spending on AI and generative AI reached $31.3 billion in 2024, up from $20.64 billion in 2023.

Three factors drive this adoption: cost reduction, customer experience improvement, and regulatory compliance. Banks using AI report dramatic efficiency gains.

Evident, a platform tracking AI in financial services, recorded over 160 use cases from 50 of the world's largest banks this year. Their findings include:

• A U.S. bank increased credit memo productivity by up to 60% using AI agents
• An Indian digital bank now monitors 100% of collections calls, up from 4%
• A European bank tripled marketing click-through rates with personalized AI campaigns
• A U.S. investment bank improved deal execution using AI-powered knowledge management

For decision makers evaluating voice AI, the question isn't whether to adopt, it's which platform delivers the performance, security, and scalability your institution requires.

Top 5 voice AI agents for banking

1. Telnyx: Full-stack infrastructure with ultra-low latency

Telnyx stands apart by owning every layer of the voice AI stack, from the global telephony network to GPU infrastructure for AI processing. This integrated approach delivers measurable advantages for banking operations.

By colocating dedicated GPUs with telecom points of presence (PoPs), Telnyx achieves sub-second latency without sacrificing compliance or security. Banks get carrier-grade reliability with the flexibility to deploy voice AI at scale, all while maintaining predictable costs at $0.06 per minute including transcription, text-to-speech, and AI processing.

Key advantages for banks:

• Sub-200ms latency through colocated infrastructure
• Licensed telecom provider in 30+ markets with PSTN calling in 100+ countries
• Single platform for provisioning numbers, managing SIP trunks, and building AI agents
• SOC 2, HIPAA, and GDPR compliant-ready infrastructure
• Transparent, all-inclusive pricing without hidden fees

Telnyx integrates seamlessly with existing banking systems and supports open-source models, allowing institutions to customize AI agents for specific compliance requirements while avoiding vendor lock-in.

2. Retell AI: Developer-focused platform with strong analytics

Retell AI stands out for its focus on knowledge integration and real-time updates, making it particularly valuable for banks that need to frequently update compliance information and product details.

The platform delivers approximately 800ms latency and supports 31+ languages with automatic language detection. Retell's modular architecture allows banks to bring their own LLMs and integrate with existing telephony systems through SIP trunking.

Banking-specific features:

• Post-call analytics with sentiment detection
• Knowledge base integration for real-time data updates
• Support for warm transfers between AI and human agents
• HIPAA and PCI compliance options
• Pay-as-you-go pricing starting at $0.07/minute (base cost)

While Retell offers powerful developer tools, implementation requires technical expertise, and total costs can escalate when adding premium voices and advanced language models.

3. Synthflow: No-code solution with predictable pricing

Synthflow targets institutions seeking rapid deployment without extensive technical resources. Synthflow features a true no-code interface with live agent testing, version control, and LLM debugging, enabling business teams to build and iterate on voice agents independently.

The platform bundles all features (voice, transcription, and CRM integrations) into flat-rate pricing at $0.08/minute. This transparency helps banks avoid the budget uncertainty common with modular pricing models.

Standout capabilities:

• Latency under 500ms
• Support for 50+ languages
• Voice cloning for consistent brand experience
• Real-time sentiment analysis with automatic escalation
• ISO 27001, SOC 2, HIPAA, and GDPR compliance

Banks report deployment times under 30 minutes for basic agents, though the platform's simplicity may limit customization for complex workflows.

4. Vapi: API-first flexibility for custom integrations

Vapi appeals to banks with strong technical teams seeking maximum control over their voice AI implementation. The platform's API-native architecture enables deep customization and integration with multiple AI providers simultaneously.

Vapi integrates with multiple TTS providers, including ElevenLabs, providing flexible voice options. Banks can swap models, adjust latency settings, and scale to thousands of concurrent calls through the platform's modular framework.

Technical advantages:

• WebRTC streaming for ultra-low latency
• Function calling for real-time backend actions
• Support for on-premises deployment
• Multilingual capabilities in 100+ languages
• Starting price of $0.05/minute (before add-ons)

The flexibility comes with complexity. Vapi requires significant development work and costs increase quickly as banks add transcription, voice, and telephony services.

5. ElevenLabs: Premium voice synthesis for brand-critical interactions

While not a complete voice AI platform, ElevenLabs deserves mention for its industry-leading text-to-speech capabilities. ElevenLabs develops its TTS and STT models in-house, offering better latency and control.

Banks focused on maintaining premium brand experiences often integrate ElevenLabs voices with platforms like Telnyx or Vapi for customer-facing applications.

Voice quality features:

• Emotional range and tone control
• Voice cloning from short recordings
• Support for 30+ languages
• Usage-based pricing from $0.06/1,000 characters

ElevenLabs excels at voice generation but requires pairing with telephony and orchestration platforms for complete voice AI deployment.

Comparison: Key features for banking deployments

Implementation considerations for banking

Successful voice AI deployment in banking requires careful attention to security, compliance, and integration requirements. AI will autonomously resolve 80% of common customer service issues by 2029, but the implementation approaches vary significantly.

Start by identifying high-volume, repetitive tasks that don't require complex decision-making: balance inquiries, transaction history, branch locations, and appointment scheduling. These use cases deliver immediate ROI while building organizational confidence in voice AI.

Consider your technical resources carefully. Platforms like Telnyx and Synthflow enable rapid deployment with minimal coding, while Vapi and Retell offer deeper customization at the cost of longer implementation timelines.

Integration with core banking systems remains critical. Ensure your chosen platform supports real-time API connections to your CRM, authentication systems, and transaction platforms. The ability to perform warm transfers between AI and human agents proves essential for maintaining service quality during complex inquiries.

Security and compliance requirements

Banking voice AI must meet stringent regulatory standards. All platforms discussed offer baseline compliance certifications, but implementation details matter significantly for financial institutions operating across multiple jurisdictions.

Critical compliance frameworks:

• PCI DSS Level 1: Essential for any platform handling payment card data during voice interactions. Look for vendors with attestation of compliance (AOC) documentation and clear scoping guidelines
• SOC 2 Type II: Demonstrates ongoing security controls and operational effectiveness over time, not just at a single point
• GDPR and regional data protection laws: Particularly important for banks with European operations, requiring explicit consent mechanisms and data portability features
• TCPA compliance: For U.S. operations, ensuring proper consent for outbound AI calls and maintaining do-not-call list integration

Key security considerations for voice AI deployment:

Data residency and sovereignty requirements vary by region. European banks must ensure voice data stays within EU borders, while Singapore requires financial data to remain in-country. Platforms offering regional infrastructure deployment provide the flexibility to meet these requirements without compromising performance.

Call recording and retention policies must align with both regulatory requirements and internal governance. Most banking regulations require 5-7 year retention periods for customer interactions. Your voice AI platform should support automated retention policies, encrypted storage, and audit trails for access and deletion.

Voice biometric authentication adds security but introduces additional compliance considerations. Ensure your platform can handle biometric data separately from general voice recordings, with explicit opt-in processes and alternative authentication methods for customers who decline biometric enrollment.

Real-time fraud detection capabilities should integrate with existing security infrastructure. Modern voice AI platforms can detect unusual patterns (i.e. calls from new locations, changes in speaking patterns, or requests outside normal behavior) and trigger additional authentication steps automatically.

Making the right choice for your institution

The voice AI platform you choose will shape your customer experience and operational efficiency for years to come. McKinsey envisions a future where banks operate with AI-first infrastructure, and early adopters are already seeing dramatic results.

Telnyx emerges as the strongest option for most banking deployments, combining infrastructure ownership, ultra-low latency, and transparent pricing. The platform's full-stack approach eliminates the complexity of managing multiple vendors while delivering the performance and compliance banks require.

For institutions with specific needs, whether no-code simplicity, maximum customization, or premium voice quality, alternatives like Synthflow, Vapi, and ElevenLabs offer compelling capabilities. The key is matching platform strengths to your operational priorities and technical resources.

Voice AI in banking has moved from experimental to essential. Institutions that act now will set customer expectations and capture efficiency gains that compound over time. Those that delay risk falling behind as customers migrate to banks offering faster, more intelligent service.

Ready to transform your banking operations with voice AI? Explore how Telnyx's full-stack platform can help you deploy secure, scalable voice agents that deliver measurable results from day one.