A Buyer’s Guide to Chatbots in Banking

Most people have used a chatbot before and probably think of it as “that bubble that pops up when I’m purchasing a flight or having trouble processing a return.” What really is a chatbot, though, and how is it used in the banking industry?

What is a chatbot and how does it work?

Conversational artificial intelligence streamlines human interaction with computers. For simplicity’s sake, you can think of chatbots as another Customer Service Rep. Like a human agent, they understand the customer’s input through written or spoken language. Similarly, conversational chatbots are designed to provide answers to complex questions about specific topics and with the historical context of each customer interaction.

Chatbot technology is constantly evolving and adapting to new industries, from the e-commerce contact center to customer service and virtual assistant chatbots for the banking sector. Whether chatbots use speech or text to communicate, they usually rely on AI technologies like machine learning and natural language processing to respond to customer queries.

Interested in buying a conversational AI chatbot for your financial services company? First off: congrats! A chatbot can really transform a company’s communications both internally (for staff and support agents) and externally (for bank customers). 

Given that there are so many types of chatbots out there and numerous reasons to use them, though, you should first take a step back and ask yourself the following questions before making this key purchase:

What will your chatbot be used for in the banking industry?

Chatbot usage can be difficult to pin down depending on the size and structure of your company. So let’s break it down: Ask yourself whether you’ll be using a chatbot for your customers or employees. 

Internal, employee-facing AI assistants can automate employees’ questions about various HR and IT matters. If you plan to use your AI bot externally (for banking customers), consider the product or service that your company provides. For instance, a financial institution could use them to help a customer check their account balance and make transfers. Or they could leverage them for educational/customer engagement purposes with personalized recommendations and financial literacy content. When choosing the solution for your organization, prioritize a conversational AI chatbot that already supports the use cases you’re seeking with proven success in the banking industry.

How much do you want to spend on a chatbot?

Now let’s talk about money. How much you want to spend will depend on your business goals and use cases. If you have a sophisticated tech team, you can create your own AI chatbot in-house. If you go this route, you might have to purchase some additional tools, hire additional engineers and/or sacrifice other projects for chatbot development.

Alternatively, you can use a 3rd-party vendor to create and implement a conversational banking chatbot on your behalf. Often, these companies have broader product suites, so in addition to a chatbot, you can potentially bundle other products into your purchase, such as onboarding software, live chat, or innovative phone technology. If you use a vendor, you’ll have to pay an upfront implementation fee and then an ongoing monthly license. 

Additionally, be wary of chatbot technology that seems too good to be true, whether it doesn’t have an implementation fee or isn’t super pricey; this most likely signals that these bots won’t integrate with your broader systems and aren’t built upon advanced machine learning or natural language processing.

While an “in-house” route may seem more appealing, it is important to consider the technical aspect of this decision. To create the best banking AI chatbot for your company, you’ll need to train the AI on your data for it to perform to your needs. This means that by the time you hire engineers, build your bot and deploy it, it could take close to 6+ months. On the flip side, having an agency-made chatbot may seem more expensive, but the time and energy saved by paying a vendor generally make it a better option.

Finally, keep in mind when you want your chatbot available for customer support. Do you want to offer 24/7 access during working hours or after hours as well? Sometimes, bot availability might affect pricing.

Does the chatbot have industry experience and domain knowledge?

“Garbage In, Garbage Out” is a key phrase in machine learning; it basically means that an AI company is only as good as the data it’s built upon. Since chatbots are trained on company and/or customer data, it’s crucial to clean this data thoroughly so that the bot can accurately, efficiently and naturally answer users’ questions. 

You should really ensure that the chatbot you’re purchasing is trained in your industry’s data. There are a lot of chatbots out there that work across industries; while this industry agnosticism is good for the breadth of their businesses, it’s not great for the depth of their products. If you work in financial services, you want your chatbot to be a finance expert, understanding all the terms and acronyms of the business, not to mention the recent regulations and protocols.

Can the chatbot work with existing software?

You’ll also need to consider whether your AI bot will be “in front of the pin” or “behind the pin.” In front of the pin means that the bot will simply sit on your website, answering basic FAQs about brand hours and ATM locations, for example. “Behind the pin,” as you can guess, means that the bot is integrated with your broader systems and technologies so it can execute actual workflows. 

An example of a “behind the pin” solution would be a banking AI chatbot that integrates with a financial institution’s core and digital banking systems, gaining access to members’ Personally Identifiable Information (PII) so that it can greet members by their name, verify their balance, make transfers or put travel freezes on their card, for example.

If you want a more integrated and, thus, effective banking chatbot, you should ensure that it will integrate with your other systems. More specifically, you should seek chatbots with open API suites, which means they can integrate with any API-friendly system.

Depending on the complexity of your existing software, you should also ask prospective clients how long their chatbot will take to integrate with your systems. If you want an “in front of the pin” chatbot, integration may only take a few weeks, but a “behind the pin” chatbot integration can take up to over 12 weeks.

Finally, regarding the technical infrastructure of your prospective AI bot, you should consider if it is omnichannel (i.e., works across web, mobile, SMS and phone technology) and if it works with cloud, on-premise and hybrid integration environments. Equally important, you should ensure it complies with privacy and security standards.

How is the chatbot engineered?

The scalability of a chatbot depends heavily on how it’s engineered. If purchasing a bot from an outside source, be sure to ask how the bot is developed. A chatbot that is created with advanced machine learning and natural language processing (NLP) will generate the best customer experience. 

Natural language processing finds patterns and relationships between computers and human language and gives the machine the ability to understand given input. NLP enables a better understanding of user intent, which provides a correct assessment of the information given to the bot. Chatbots engineered on just basic triaging and flowcharts are robotic and frustrating for end-users, whereas bots built upon machine learning and NLP are far more human-like, able to understand linguistic nuances and execute complex tasks.

Can the chatbot be personalized to your company?

Depending on the service you want your chatbot to perform, personalization can be key. To personalize your chatbot, look for vendors that have Content Management Systems. Some vendors crowd-source frequently asked questions or desired workflows from industries and enable you to pick and choose which questions and workflows you want to create. You can then brand your chatbot in your colors and with your logo as well as adjust the content to include your company’s name, hyperlinks and style of speaking. 

You can further personalize your bot by having it integrate with your customer data so that it greets users by their name and knows their backstory (i.e., their date of birth or recent spending history) before beginning to converse with customers. If you’re instead building your bot in-house, you can create your own content by consulting your sales, marketing and customer service teams to unearth customer requests and trends to ensure the most personable and comfortable experience possible for users.

Can the chatbot seamlessly hand off to a live agent and display analytics?

While considering which banking chatbot to buy, you should ask about success metrics, prioritizing solutions with a high (over 90%) containment rate (the percentage of customer questions that the bot can handle individually without involving a human agent). Given that all bots will require at least some human assistance, you should then determine if a chatbot works in tandem with live support. To create the best customer experience possible, your business must find a chatbot that allows both parties to support the customer without frustration. 

As soon as a customer asks to speak with a live agent, the bot needs to be able to connect them to not just any agent, but the correct agent. The bot should also retain enough information from the conversation to direct a customer to an agent in the correct department at the company, contextualizing the conversation up until that point so that the customer doesn’t have to repeat themselves.

To enact seamless handoff, the chatbot can either integrate with a live chat vendor (e.g., Glia, LivePerson, Oracle) or instead create a ticket. Creating a ticket entails notifying an employee in real time that a specific customer has a question that the automated bot can’t answer and needs to be called or emailed about ASAP. This smooth exchange can dramatically enhance the customer’s experience with the bot.

An additional feature you should seek in a chatbot is analytics; you want a chatbot that comes with an analytics dashboard or email digest so that you can track its performance and your return on investment (ROI).

Conclusion

At this point, you may have already made up your mind about whether you want an AI chatbot and which version you prefer. If you’re still struggling to decide which solution is best for your company, though, consider speaking with your customers and/or employees who will actually be using the tool to get a better idea of what they genuinely want and need. 

If you already have a chatbot-like system being implemented, ask if it’s satisfying the needs of the users or if you should consider a more innovative solution. Regardless of what stage your company is at, hopefully, this gave you a great framework to think about bots and conversational AI!

Sources:

[1] https://www.capgemini.com/2018/10/what-to-look-for-when-choosing-a-bot/

[2] https://haptik.ai/blog/ultimate-cmo-guide-how-to-buy-chatbot/

[3] https://chatbotslife.com/7-key-factors-to-consider-before-choosing-a-chatbot-platform-dfc4c8f3a3fa

[4] https://chatbotsmagazine.com/5-core-considerations-for-choosing-your-chatbot-4f4bb0856ead

[5] https://sproutsocial.com/chatbots/#the-value-of-chatbots

[6] https://mobilemonkey.com/blog/chatbot-pricing/