The emergence and diversification of the financial chatbot

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Photo by Colin Watts on Unsplash
Photo by Colin Watts on Unsplash

After an eruption of overhype followed by a period of negation, the financial chatbot is enjoying something of a renaissance. In (seemingly) the blink of an eye, a diverse financial chatbot ecosystem has spread across the fintech space.

This fast-paced bot story is still unfolding and shifting. And, though finding their feet, three distinct types of financial chatbot have emerged. The website chatbot, the chatbot app, and the artificial agent have each established their own unique financial services (FS) niche.

Here, we explore the emergence and diversification of FS bots, and look in closer detail at each breakout bot type.

The emergence of the financial chatbot

First, it is important to understand the backdrop against which the financial chatbot has risen to popularity.

Today’s bot upsurge is driven by a shift in consumer preferences. Many of us (and not just millennials) now prefer digital interactions for accessing and managing our financial services. Banking is simply quicker and more convenient to do online.

And, since the COVID-19 outbreak, the need for digital transactions has only soared higher.

So, consumers of financial services have demanded digital options. Meaning, of course, that FS brands must meet digital customer support needs adequately. And chatbots have answered the call for 24/7/365 assistance through the comfort of a screen.

As appetite for bots has increased, so too has financial chatbot diversity. Alongside the traditional website chatbot, dedicated chatbot apps and even physical bot manifestations have since branched out. But what is the purpose and value of each FS bot type?

Website chatbots

Website chatbots are the classic bots that brought the initial wave of hype. As the name suggests, website chatbots are the bots that are accessible through your website. In FS, these bots handle banking FAQs and point customers to relevant resources and self-service options.

A common mistake with website chatbots – and one not limited to the financial services sector – is to deploy them as standalone. No matter the industry, standalone bots are of low overall value. They’re rarely able to offer anything more than an ordinary help area can.

The value of website chatbots in FS, then, is best tapped by integrating them into a live chat channel supervised by a human service team. This allows the bot to both support the customer’s use of your digital services, and escalate more complex queries to a human representative.

When it comes to money, issues can quickly become high stress. Having this type of financial chatbot gives your service users the comfort of accessible, speedy help. So, though the web bot is perhaps the most misused variety, its value lies in preventing or reducing money-fuelled stress.

Chatbot apps

The chatbot app is a progression of the basic services provided by a website bot. Unlike website chatbots, this financial chatbot lives in its own application. (Rather than as a part of your website experience.) For example, think Cleo and Plum — services residing on your phone as an AI assistant.

The value behind this type of bot lies in its functionality. Chatbot apps help you track and manage your money, savings, and spending habits. They offer a dexterous tool for finance customers, acting as a free artificial financial advisor. In doing so, chatbot apps bring clarity and understanding to the financial habits and situation of each user.

The value of chatbot apps is also amplified by their mounting popularity. Originally little-trusted, services like Cleo have since entered the mainstream. In response to this consumer traction, it’s reasonable to predict that major banks will also develop their own similar apps.

Artificial agents

Artificial agents are the rarest and most recent breed of financial chatbot. Unlike the other FS bots, artificial agents aren’t text-based. Rather, they have a human-like avatar for customers to engage with verbally. They essentially serve as ‘digital humans’ that can talk to customers and hold a two-way vocal conversation.

Natwest’s Cora, for instance, is an artificial agent. Cora started life as a ‘normal’ web-based text-using chatbot. She then evolved alongside machine learning and other technology to become an in-branch agent.

The true value behind artificial agents is largely speculative, due to their exploratory nature. However, artificial agents may provide a cost-effective way to keep physical banking branches open in a dying high street. They provide a viable alternative to human tellers and can interact with several customers at once.

In other words, artificial agents blur the divide between chatbot and human. They bring the human experience of a real-world interaction into the digital space. And they bring the benefits of chatbots – speed, self service – into physical interactions.

The rise of the financial chatbot

From tried and tested website chatbots, to popular chatbot apps, to emerging artificial agents, the financial chatbot is enjoying widespread adoption and diversification. No matter the flavour, each FS bot brings unique value to the table.

And the rise of chatbots is still gaining pace. Teething issues and overhype phase now behind us, chatbots are now more broadly understood and implemented less haphazardly. (For the discerning brand, at least.) Plus, with language processing technology advancing, chatbot abilities are only set to grow.

But for now, no matter what value you seek from your bot, there’s a financial chatbot to suit your needs.

Originally published at https://www.whoson.com/chatbots-ai/the-emergence-and-diversification-of-the-financial-chatbot/ on September 6, 2019

Niamh Reed
I'm a Keele University graduate and copywriter for digital engagement specialist Parker Software. I graduated with first-class honors in English with creative writing and was also awarded a certificate of competency in Japanese. I can usually be found feverishly writing business technology articles – covering everything from AI to customer service – and drinking too much tea.

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