Interactive Chatbot Built for a Global Bank to Improve Customer Support at Scale
Delivering secure, always-on customer assistance across 2,000+ branches
Meaningful Conversations
Security
Containment Rate
Client Overview
The client is a globally recognized banking institution with more than 2,000 branches serving customers across multiple regions. With millions of customer interactions each year, the bank required a customer support model that could scale without compromising security, speed, or service quality.
Challenge
- High dependency on manual support teams, resulting in longer response times during peak periods
- Repetitive customer questions, which consumed agent capacity without adding proportional value
- Limited after-hours support, affecting customer experience across time zones
- Strict security and compliance requirements, leaving no room for compromise in authentication or data handling
Our Approach
Sthenos designed and implemented an interactive AI chatbot focused on practical problem-solving rather than scripted responses.
Understanding Customer Intent
The chatbot was built to recognize customer intent and common query patterns, enabling it to respond accurately to frequently asked questions and routine service requests.
Secure Identity and Access Handling
Customer identification and authorization were integrated directly into the conversational flow using secure authentication mechanisms, ensuring sensitive information always remained protected.
Multi-Channel Accessibility
To extend reach and convenience, the solution was integrated with voice assistants such as Alexa and Google Assistant, allowing customers to interact through familiar platforms.
Scalable and Resilient Architecture
The backend services were designed to handle large interaction volumes reliably, ensuring consistent performance even during high-traffic periods.
Technical Spotlight
- Context-Aware Conversations: The system was built to understand user intent and conversational context rather than relying on fixed decision trees. This allowed the chatbot to respond naturally to varied customer queries while maintaining accuracy across thousands of interactions.
- Secure Identity Management: Customer identification and authorization were handled through OAuth-based authentication. This ensured every interaction followed strict access controls and complied with enterprise banking security standards.
- Voice Assistant Enablement: To improve accessibility and convenience, the chatbot was integrated with Amazon Alexa and Google Assistant. This allowed customers to interact using voice commands while receiving the same level of accuracy and security as text-based channels.
- Scalable Serverless Architecture: AWS Lambda enabled the chatbot to scale automatically based on demand. This ensured consistent performance during high-traffic periods without the need for constant infrastructure management.
- High Availability and Reliability: Deployed on a Linux-based environment with a Node.js and Express backend, the system was built for resilience and uninterrupted service, even during peak usage.
Solution Delivered
- Customers received real-time responses, 24/7, without waiting for agent availability
- Around 70% of incoming queries were fully resolved without human involvement
- For complex cases, the chatbot captured relevant context and routed requests to the appropriate support teams
- Agents received better-prepared tickets, reducing resolution time and customer frustration
Results
- 4,000+ meaningful customer interactions handled efficiently
- 70% containment rate, significantly reducing pressure on customer service teams
- 100% adherence to security and compliance standards
- Faster response times and improved agent productivity
Tech Stack
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