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How to decide on the right chatbot for your banking institution

The burden on the banking care ecosystem in 2020

The COVID-19 crisis has been tough on the US banking sector. As the pandemic dominated its spread across the nation in March, call centers for US-based banks collectively saw a substantial increase, with the larger US banks getting a 40% increase in call volume. These call volumes, coupled with longer wait times, have led US banks to rely heavily on their digital channels. Most banking institutions responded by diverting a substantial portion of their customers to conversational chatbots on their platform, notably Bank of America (Erica) and Capital One (Eno), to solve basic banking queries.

The dilemma of choice with conversational chatbots

However, this is a stop-gap solution to the current pressing needs of banking customers. Most banks are still keeping their branches closed, which means customer support teams have to bear all the incoming support load. Banks hence need to step up their technology prowess to address complex customer queries by using AI and machine learning while ensuring customer value. Banks have looked at integrating cloud-based conversational solutions to get ahead of this situation in recent years. However, the pandemic has compelled the C-suite to look at customer support from a holistic perspective.

Selecting a conversational chatbot platform to integrate into existing banking systems is a persistent nightmare. The compliance, security, and privacy considerations involved can complicate the C-level decision-making process. The guidelines listed below can simplify the process of selection and guide the C-suite into making an informed decision on what an effective conversational AI-driven chatbot platform for their needs should be.

chatbot in banking

Meet the customer where they are

Multi-channel engagement

Conversational platforms, homegrown or procured, have traditionally been a function of the channel – web, mobile or social. Most chatbots for customer care are deployed within an app or website, which compels banking customers to navigate to that channel to get the queries addressed. Only a few chatbot platforms have a presence on widely available messaging or social platforms like WhatsApp or Facebook Messenger.

Context Retention

If the platform supports multi-channel integration, it should carry over context seamlessly across channels. A customer can start talking about a fee dispute on their desktop web browser, start traveling, and then chat with banking support over WhatsApp on-the-go. The chatbot platform needs to be able to resume the conversation seamlessly, without losing context.

Related article: Increase Banking CSAT with Conversational AI Chatbots in 2023

Own the customer journey, not just the chat interaction

Most conversational chatbot platforms integrate into existing CRM and banking systems and can surface only pertinent information about support queries in a rule-based fashion. Most complex queries are handed over to a real care agent, who then has to triage the issue behind the scenes with multiple teams. As these teams engage in triaging and resolution, the essential milestones in resolution could be transparently made visible in the chat conversation.

Chatbot platforms should integrate intelligently into the end-to-end customer journey by holding the context of the entire triaging process in the conversation. They should be able to transparently notify the customer in a prompt and regular cadence, thus restoring trust and engagement in the issue resolution process. In turn, such frequent communication leads to an increase in customer satisfaction and engagement scores.

chatbot in banking sector

Be the intelligent concierge to the care agent team

Care agent teams are already bearing the immense load of the call volume in the current crisis. The chatbot platform should be able to learn from past successful resolutions handled successfully by human agents. The platform can then train the chatbot to solve similar issues at scale across multiple conversations and reduce subsequent call deflections to human care agent teams, thus reducing the load.

The platform should also enable human-to-chatbot communication for specific aspects in the issue resolution process, as seamlessly as chatbot-to-human to retain care agent capacity. These 2-way mechanisms would allow the care agent team to focus more on severe issues that mandate their attention and foster better work environments with predictable call volumes.


These guidelines should assist executive decision-making for any banking institution, regardless of size and customer market. As banks try to adjust to a post-pandemic world, a well-chosen conversational chatbot platform would become their crucial business enabler to providing a white-glove customer experience.

Did you find these guidelines helpful? If you are looking for a platform providing all these capabilities, Autonom8 provides the only conversational chatbot platform your bank will ever need – A8Chat.

Are you interested in learning more? Schedule a demo and experience A8Chat today.