Conversational banking uses natural language processing (NLP), which is a fancy way of saying AI for words. Like any other chatbot, we built the NLP model using intents, expressions, entities and flows.
When a user asks a chatbot a question, we refer to that as an expression. For example, the user asks, “How do I cancel my credit card?” The bot processes the user’s expression and compares it to the different expressions within its NLP model. Each expression within the NLP model is associated with a specific intent, or answer to an expected question.
The bot then assigns a confidence score to each intent, and based on the different thresholds and rules that we define, it responds to the user with the appropriate answer.
Banking is the perfect business case for conversational AI because banks and insurance providers have thousands of customers who use their services multiple times a day. This inevitably leads to problems that need solving and questions that need answering.
Most of the incoming questions are repetitive, easy to recognize and easy to answer. This is the trifecta for conversational AI automation, making it a win-win for banks and customers.
On average, banks implementing a basic chatbot save between 10-20% of an agent’s time. The customer support agents can repurpose their saved time to focus on more complex cases that need human attention.
Humans make mistakes; it just happens sometimes. Whereas a chatbot follows standardized, pre-programmed logic, making it almost impossible to make mistakes.
A chatbot can live almost anywhere: on your website, in your app, WhatsApp, Instagram, Twitter, etc. By placing your chatbot where your customers already are, you widen your customer reach and reduce the barrier to connect.
Instead of spending time answering the same question 20 times a day, a customer support agent can delegate these types of tasks to a chatbot. They then have the time to focus on resolving complex client issues and upselling clients.
A chatbot is available 24/7 and can answer a user’s question in seconds. This is a significant contrast when compared to more traditional question-and-answer approaches. For example, think about when a customer had to wait on the phone line for 10-30 minutes for a representative to pick up or send an email and wait a few days for a response. With a chatbot, your customers ask whenever is most convenient for them and they receive an instant response. There are no opening hours, no queues and no waiting times.
It’s easy to connect your chatbot to your CRM system. This allows you to identify your customers and tailor the conversation to their needs and profile. For example, if you’re logged into your banking app and trying to file an insurance claim, the bot can look up your existing policy and respond with an answer tailored to your insurance policy. Each user’s experience with the chatbot is customized and unique.
It’s much more enjoyable and efficient to have an interactive conversation rather than trying to fill out a form that doesn’t allow you to express your problem or fighting with an IVR system that doesn’t understand your request. Chatbots are flexible and trained to solve problems and answer questions.
We can place a chatbot on almost any channel, making it much easier for your customers to connect with you via the channel that they prefer. This allows them to seamlessly switch between channels and makes it a more convenient experience for everyone.
Like any other industry, a chatbot can support all types of departments and roles. Here are some different implementations for banking chatbots:
Banks will inevitably continue adopting conversational AI to automate frequently asked questions, execute transactions and streamline processes. Financial institutions that don’t make this switch won’t be able to sustain the increasing volume of incoming questions and remain competitive.
Are you interested in implementing a chatbot at your company?
Reach out to Alexis for a quick chat.