Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
Financial services firms require strict standards of accuracy, reliability, and regulatory compliance in their digital experiences. A leading North American financial services firm came to WillowTree to create a next-gen chatbot experience in just eight weeks, and our successful delivery paved the way for our GenAI Jumpstart accelerator — a safe, secure, modular architecture we can adapt to any industry.
“This is amazing, in terms of how fast you have put this together. Kudos to you guys.”
In just eight weeks, WillowTree's prototype blew older intent-mapped chatbot capabilities out of the water with its human-like conversational abilities and more expansive range of responses. Importantly, our financial services client gained confidence that generative AI could be deployed safely and responsibly within regulatory requirements.
Our eight-week effort formed the basis for our GenAI Jumpstart accelerator program, a crucial prototyping step in our client’s journey toward deploying a safe and compliant public-facing virtual AI assistant.
“Following a successful delivery with a major financial services institution in North America, we codified our GenAI Jumpstart offering to provide eight weeks of AI development around a particular use case that a client brings to us, viable across any industry.”
Our client, a leading innovator in financial services, wanted to leverage generative and conversational AI to create a sophisticated banking chatbot for their users. Balancing open-ended conversational abilities with strict security was paramount. They needed a solution that could:
Traditional bank AI chatbots (that tend to annoy users) rely on intent mapping: a process that offers a limited set of around 250 predefined options and responds with hardcoded messages mapped to those user “intents.”However, intent mapping is rigid and restricted. This limitation makes typical intent-based chatbots frustrating for users wanting to ask natural, open-ended finance questions that don't fit neatly into pre-scripted buckets. For instance, when customers inquire about comparing credit card products or ask for personalized account recommendations, legacy chatbots falter.
“Our product owner was hoping this effort would prove that large language models were superior to their existing intent mapping chatbots in every way, and he told us verbatim that our team blew intent mapping out of the water.”
On the other hand, deploying open-ended conversational AI in banking poses serious challenges. Financial institutions deal with sensitive customer data and face complex compliance requirements from regulatory bodies like the SEC and FINRA. In general, two primary risks emerge when integrating sophisticated conversational AI assistants: Hallucination and Jailbreaking.
So, while conversational AI assistants enable personalized banking experiences, their open-ended nature differs enormously from rigid predefined chatbots limited to narrow topics. Safely adapting generative AI for regulated industries is an immense challenge.
The stakes were high: balancing sophistication and security necessitated tradeoffs and a multilayered technical approach spanning data readiness, large language models (LLMs), systems architecture, and UX/UI design.
WillowTree happily stepped up to the challenge.
WillowTree implemented a modular bank chatbot architecture with two key components: Retrieval Augmented Generation, and “Supervisor” LLM.
This dual-model approach contained the conversational range and specificity of our client’s products and services while allowing sophisticated discussions beyond the limits of predefined chatbot intent mapping.
"I can't sing your praises enough. You got me to drink the kool-aid on WillowTree."
