We partnered with one of America’s strongest community banking institutions to enhance customer experience standards and forge stronger brand connections through LLM-powered conversational solutions.
Business Goals
This client is a community banking major in the USA, operating over 100+ branches in 20+ states. Their business is thriving with increasing account openings and loan offerings. They sought to solidify their customer experience strategy to accelerate their business growth further and strengthen their market position. So, achieving excellent CX was the goal, and they required interactive and extensively personalized chatbot systems to drive online customer engagement with the following requirements.
- A fully functional and scalable conversational platform to enhance customer service and operational efficiency.
- 24/7 chat support and helpline providing high-quality and actionable results for customer queries.
- Providing instant support for customer queries through natural and human-like conversations.
Solution
We reviewed their community banking business offerings, service protocols, and online footprint for customer engagement. The available online Chatbots were more one-dimensional and incapable of delivering personalized engagement to their customers. We introduced a 24/7 personalized AI assistant backed by a strong LLM base that has comprehensive intelligence on product offerings, customer queries, and service guidelines.
We explored potential challenges and risks, such as AI bias and hallucinations, and implemented proper risk mitigation strategies. By training with high-quality data, continuous testing, and model updating, we achieved significant linear improvement in chatbot responses.
Focusing on banking security guidelines, we fine-tuned the AI model to ensure a sufficient security level, data privacy, and elimination of the possibility of data leaks.
Key Highlights
- Leveraged more sophisticated language processing mechanisms to analyze user queries and precisely identify user intent.
- Utilized well-curated parameter clarification techniques that prompt users to share more relevant information with the Chatbot.
- Post parameter clarification, a back-end call is triggered to execute the user queries with the most suitable answers and solutions.
- Fortified security standards achieved through MFA, data moderation, and end-to-end encryption, so there is no data residual within the AI model.
Outcomes
- 17% reduction in physical visits of customers owing to online service success.
- 20% increase in number of queries with a new conversational chatbot.
- Multi-lingual support to ensure ease of use for multicultural customers.
- Significant reduction in customer-service TAT and service operation expenditure.
Technologies Used: Python, LLM, API integrations
