Implementing an AI-powered multilingual chatbot for
financial assistance
2023-ongoing
4 experts
Financial Services
USA
Summary
Business challenge:
Enhancing customer support efficiency, scalability, and cost-effectiveness while enabling 24/7 multilingual assistance.
Zoolatech approach:
Implementing an AI-driven chatbot powered by OpenAI and Langchain to provide seamless multilingual support, automate FAQs, and assist with loan pre-qualification forms.
Value delivered:
Reduced operational costs, improved customer experience, increased scalability, and enhanced reliability.
Technologies:
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About the Client

Our client is a leading fintech company committed to delivering seamless digital financial services.

Business Challenge

The company sought to enhance customer support efficiency and scalability while reducing operational costs. Traditional human-based support was resource-intensive, prone to delays, and affected by factors such as fatigue and emotional bias.

To improve the user experience, the company aimed to provide 24/7 multilingual support and optimize assistance for routine tasks such as FAQs and loan pre-qualification forms.

However, developing a custom AI/ML model from scratch was considered too time-intensive and costly, which called for a faster, scalable, and cost-effective solution that could deliver immediate value.

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ZoolaTech Approach

To address these challenges, ZoolaTech implemented an AI-powered chatbot solution leveraging OpenAI and the Langchain framework. The chatbot was designed to:

  • Enable multilingual support: Provide seamless support in multiple languages with the ability for users to switch languages mid-conversation.
  • Streamline customer interactions: Handle FAQs, assist users in filling pre-qualification forms for loans, and offer 24/7 automated support. Future enhancements include expanding support for additional loan types and integrating the chatbot into platforms such as the company blog and community spaces.
  • Improve efficiency & accuracy: Deliver faster responses, handle multiple customer queries simultaneously, and eliminate human errors or inconsistencies.
  • Enhance internal communication: A Slackbot version was deployed to assist internal teams with quick information retrieval.
Tech implementation
  • Frontend: ReactJS-based widget embedded across the company’s websites.
  • Backend: Python-based FastAPI service managing business logic.
  • AI logic: The Langchain framework preprocesses user messages before forwarding them to OpenAI, ensuring better contextual understanding, accuracy, and adherence to predefined guidelines. The chatbot analyzes initial user input to determine the domain area and provide relevant support.
  • Tech stack: Python, FastAPI, ReactJS, MySQL, Langchain, OpenAI.
Challenges and how we solve them
Limited control over AI responses

Since OpenAI operates as a black box, refining responses requires continuous prompt optimization and updates to ensure accuracy and relevance.

Solution: Implemented an iterative prompt engineering process, continuously testing and refining prompts to align chatbot responses with business requirements.

Testing constraints

Due to the AI model’s variability, end-to-end testing is challenging, as responses could not always be predicted.

Solution: We established extensive manual testing and validation processes, ensuring responses meet quality standards before deployment.

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Value Delivered

The chatbot has been successfully deployed across multiple platforms, delivering measurable benefits:

  • Cost efficiency: Reduced reliance on human support, leading to lower operational costs.
  • Enhanced user experience: Faster, grammatically accurate, and consistent responses.
  • Scalability: Supports multiple customer interactions simultaneously, without the limitations of human agents.
  • Reliability: Eliminates human factors such as fatigue, emotional bias, and response inconsistencies.
  • Future-ready infrastructure: A scalable foundation for expanding to new platforms and financial services.

By implementing this AI-powered chatbot, ZoolaTech enabled the client to provide superior customer support while driving efficiency, scalability, and long-term cost savings.

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