Conversational AI for Banking and Financial Services
Financial institutions use Rasa to deploy conversational AI for banking that handles account servicing, transactions, fraud-related interactions, and lending journeys across voice and digital channels. Rasa enables teams to turn customer needs into safe, meaningful action with full control over execution, deployment, and data handling. Organizations including N26, ERGO Group, and nib Group use Rasa to automate high-volume service while maintaining compliance, infrastructure ownership, and visibility into how decisions are made.
How it works
Connect to your banking systems
Rasa integrates with core banking platforms, CRMs, payment systems, authentication services, fraud tools, and enterprise knowledge sources. AI agents operate within your existing infrastructure, not alongside it.
Orchestrate governed banking workflows
Design AI agents that guide customers through account support, transactions, authentication, fraud handling, and lending journeys. Every step is controlled, inspectable, and aligned with your policies, so actions are taken safely across systems.
Deliver one continuous experience across channels
Run the same underlying capability across chat, voice, IVR, mobile apps, and web. Customers move across channels without losing context, and teams avoid rebuilding logic for each touchpoint.
Built for high-value, high-stakes conversations
Customer Account Support & Self-Service
Secure Transactions & Payments
Authentication & Fraud-related workflows
Proactive Service and Customer Engagement
Knowledge Search & Answer Resolution
Loan & Credit Application Support
Patented dialogue system
AI behavior that is both natural and reliable
Rasa provides a dialogue system designed for enterprise AI agents, combining natural interaction with structured execution. Teams can define how conversations behave, while ensuring outcomes remain consistent across high-stakes workflows.
- Support natural conversations while maintaining predictable outcomes
- Guide users through multi-step interactions like transactions or applications
- Maintain shared context across multi-turn interactions
- Keep full visibility into how decisions are made and executed
On-prem / private cloud deployment
AI you can operate in regulated environments
Rasa runs within your environment, giving full control over infrastructure, data handling, and model usage from day one.
- Deploy in private cloud, on-prem, or hybrid setups
- Choose your LLM provider and control data boundaries
- Meet compliance and security requirements without compromise
- Avoid reliance on vendor-managed infrastructure
Multi-agent orchestration
One system for complex financial workflows
Rasa connects multiple agents and backend systems into a single coordinated system, enabling end-to-end execution of complex financial workflows.
- Connect account servicing, payments, fraud, and lending workflows
- Share state and context across agents and channels
- Enable clean handoffs between systems and teams
- Expand from single use cases to interconnected systems without fragmentation
Open framework and ownership
Full control over how your system evolves
Rasa gives teams direct access to the components that define system behavior, so they can extend and adapt the platform over time.
- Modify prompts, policies, and business logic directly
- Integrate with internal tools, APIs, and data sources
- Evolve capabilities as business needs change
- Maintain long-term ownership of your AI system
With Rasa, we at ERGO are completely rethinking how we build customer support experiences. It’s about developing faster and cheaper, and at scale. Rasa helps us to realize these goals.
Rasa’s platform enabled us to customize and scale our AI assistant’s capabilities, ensuring it evolved with changing member needs and organizational goals.
N26 transitioned from concept to production in just four weeks, deploying the AI assistant within their secure cloud environment to maintain full data control.
Resources
N26: Scaling Multilingual Customer Support with Rasa
20% automation of customer service, deployed in four weeks, operating in five languages.
nib Group: Transforming Member Engagement with AI-Powered Assistant
4M+ queries handled, 60% reduction in digital support needs, $22M+ in operational savings.
ERGO Group: Enhancing Customer Service with AI-Powered Assistance
30%+ request automation, agent-assist model, strategic investment in autonomous AI.
Leading financial institutions trust Rasa to automate their most critical conversations.
See How Rasa Works for Financial Services.
Book a personalized demo and see how account servicing, transaction automation, fraud support, and customer engagement work in practice.
Frequently asked questions
What types of customer interactions can Rasa automate in banking?
Rasa enables banks to automate high-volume and high-stakes interactions such as account servicing, payments, authentication, fraud handling, and lending workflows. These are not just responses, but complete, policy-compliant actions executed across backend systems.
How is Rasa different from traditional banking chatbots or AI assistants?
Traditional chatbots focus on answering questions. Rasa enables AI agents that take action across systems, using orchestrated capabilities that follow business rules, maintain context, and execute real workflows end to end.
Is Rasa compliant for financial services use cases?
Yes. Rasa supports SOC 2 Type II compliance, on-premise and private cloud deployment, data residency controls, and full audit logging for every automated interaction. This makes it suitable for environments with strict regulatory and compliance requirements.
Can Rasa handle voice interactions for banking?
Yes. Rasa provides a single agent system across voice, chat, mobile apps, and web. Context is maintained across channels, so users can switch touchpoints without restarting their interaction.
How does Rasa integrate with banking systems?
Rasa connects to core banking platforms, CRMs, payment processors, authentication services, and fraud detection systems through open APIs and pre-built connectors. Teams use Python logic and custom connectors to integrate with proprietary tools without vendor lock-in.
How does Rasa ensure safe and compliant AI behavior?
Rasa separates language understanding from execution. AI models interpret user input, but all actions are governed by structured, versioned logic that enforces policies, validation steps, and approval paths. Every decision is traceable and auditable.
How much control do teams have over AI models and system behavior?
Rasa gives teams full control over model selection, prompts, orchestration logic, and execution paths. Every part of the system is configurable and observable, so teams can adapt behavior without relying on vendor-controlled black boxes.
What financial institutions use Rasa?
Enterprise financial institutions including N26, ERGO Group, nib Group, PayPal, and Bank of America use Rasa to automate customer interactions across account servicing, transactions, fraud support, and engagement. Rasa powers production deployments handling millions of interactions.
How is Rasa different from other conversational AI platforms for banking?
Rasa is built for organizations that need control, extensibility, and long-term ownership. Instead of limiting customization or hiding logic behind vendor systems, Rasa provides a platform that teams can operate, extend, and govern as part of their core infrastructure.
How does Rasa support fraud detection and authentication?
Rasa supports structured authentication and fraud handling by integrating with existing security systems. It can enforce identity checks, trigger step-up authentication, and route sensitive interactions through governed workflows without relying on model-generated decisions.
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AI that adapts to your business, not the other way around
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