Regardless of the industry your business operates in, customer experience always proves to be a game-changer. Between two businesses that provide the same products at similar price-points, the one with superior customer service tends to be the preferred brand. And with the heightened demand for financial services, particularly from customers trying to manage their finances at home because of the effects of COVID-19, the competition has never been tighter.
This competition has led to an increasing number of chatbots in financial services industry in an attempt to provide the best service to as many customers as possible. The market is evolving, and chatbot technology is evolving along with its users. Let’s look at why banks and other financial institutions are starting to deploy chatbots at an ever-growing rate.
Most chatbots you see on different websites, and social platforms seem a bit too basic to transform business processes in a meaningful way. However, if planned and programmed correctly, chatbots in the financial services industry can offer banks the following benefits:
Unless a bank can afford a team of agents that work 24/7, its customers might have to wait until the start of business hours for replies to their inquiries. A chatbot will reduce the waiting time and keep the customer engaged and informed, even on weekends and evenings.
Chatbots can go beyond answering FAQs, too. They can also be programmed to upsell or cross-sell financial products based on previous transaction history and transfer more complicated queries to a human agent. Besides chatting with customers, they can disseminate bank updates or financial advice to customers as they browse through the website.
Unless the bank strictly implements it, gathering customer feedback usually is not part of the transaction process. Some customers hesitate to provide feedback due to privacy concerns or a feeling that it won’t make any difference. When they do give feedback, they prefer a conversational approach rather than answering a questionnaire.
A chatbot with customer feedback gathering capabilities could help convince customers that the bank will protect their personal information and take feedback seriously. When you combine a chatbot with AI and big data, it can identify common customer pain points and alert decision-makers about the need for changes.
The cost of a chatbot might vary according to what you want it to do. If you plan to deploy a chatbot for updates and FAQs, the development cost will be relatively low. But for more complicated transactions, such as money transfers or balance inquiries, it will be more expensive.
The platform you’ll use will also play a role in determining the cost: a chatbot built on Facebook Messenger will cost a few thousand dollars, while a dedicated chatbot for a business website might cost up to ten times as much. However, no-code technology makes it possible for even the smallest business to create a chatbot in just a few minutes!
All in all, though, compared to the expenses involved in hiring and training a team of customer service associates, chatbot development costs are much lower, especially if the chatbot is cloud-based or uses existing technology. And a chatbot never takes a day off or gets sick!
You might be wondering why we’re comparing a single chatbot to a team of customer service agents. It all boils down to capacity and speed — a chatbot can accommodate hundreds, even thousands, of transactions at any given time. At the same time, an agent can concentrate on only one customer call. The level of customer service remains at the same level, even if the chatbot handles multiple inquiries at one time.
In addition, robotic process automation (RPA) technology makes it possible for chatbots to reduce the time needed to process certain transactions drastically. A bank in Singapore, for example, used a chatbot to reduce the average home loan repricing time from 45 minutes to just one minute, which allows the bank to process many times more loan repricing requests in less time.
One can see the effect of chatbots on a typical employee timesheet. Instead of being bogged down with routine tasks that add little value to the company, an employee can instead devote their time to more complicated tasks that require a human touch while the chatbot takes over smaller tasks.
It’s hard to imagine that industry experts were still debating whether chatbots in financial services industry would ever replace mobile apps only a few years ago. Now, it’s difficult to think of a bank that doesn’t have some type of chatbot technology built into its app or website.
Here are some examples of chatbots that banks have built as part of their customer experience strategy:
The Chinese banking market is growing fast, and established industry players frequently need to hold off attempts by startups that specialize in disruptive technology. Unknown to many, chatbots have been in use in China since 2013, when Tencent announced a bot platform based on its popular WeChat app. The technology became popular rather quickly as companies used it to engage with their customers 24/7.
However, banks and other traditional financial institutions were slow to embrace this trend. It wasn’t until 2018 that banking giant HSBC launched its own chatbot, Amy. Packaged as a virtual assistant, Amy provides instant answers to customer queries in three languages — English, Traditional Chinese, and Simplified Chinese — and is available 24/7, even on public holidays.
While Amy is still little more than an information help desk for HSBC customers, the bank is keen on using AI to improve the chatbot’s learning process and expanding its skillset to include basic transactions.
Since it was first rolled out in 2018, Bank of America’s Erica chatbot has gained over 10 million users. The first phase of the project involved essential banking functions, including card activation and deactivation, money transfer, transaction history, bill payments, and appointment scheduling.
Besides the features above, BofA announced Erica Insights, a personal financial management toolkit powered by AI. It includes a FICO score tracker, bill and recurring charge reminders, and weekly snapshots of month-to-month spending.
It also features a balance tracker that warns users when their spending patterns are on course to take their balance to below $0 within seven days. These tools help users make more informed financial adjustments and identify savings opportunities, like spotting if a customer has duplicate Netflix subscriptions.
Erica has helped BofA increase its base of mobile app users. While more than 40% of Erica users are millennials who are already familiar with the mobile app, 16% of Erica users come from the Baby Boomer generation, who are drawn to how the chatbot makes the mobile app more comfortable to use and the types of insights it provides.
Bank chatbots have also been deployed in Australia, where Commonwealth Bank, one of the country’s largest financial institutions, has launched a chatbot called Ceba. As of 2018, Ceba was assisting customers with over 200 tasks, including getting account balances, making payments, activating loans, and opening a new account.
However, Ceba’s strongest point is its AI and natural language processing technology, which the bank predicted would allow it to learn more than 500 activities within a year of its launch. Commonwealth Bank expects the chatbot to eventually understand over 500,000 questions to account for the thousands of ways its customers ask questions.
For example, the chatbot should be able to interpret “I want to open a new account”, “New account,” and “Can I open a new account,” among others, as calls for the platform’s account opening feature. This kind of learning allows Ceba to provide personalized service that detects a user’s intentions, regardless of the precise vocabulary they use.
Part of the customer experience is what happens when they’re not on the phone with an agent. In fact, we can argue that back-office operations are just as crucial as customer-facing activities because they dictate the results customers get.
For example, one of the most common complaints among bank customers is having to wait too long for a loan application to be processed, only to be told that they’re not qualified for one.
While most of the chatbots we’ve discussed here are customer-facing, JPMorgan Chase’s COIN solution is different. It makes life easier for thousands of lawyers and loan officers who spend more than 360,000 staff-hours each year on routine tasks such as reading and interpreting loan agreements.
The chatbot uses machine learning to cut the time needed to review loan agreements to just a matter of seconds. In addition to saving time, JPMorgan can also reduce mistakes due to the lower level of manual intervention in the process. And because the chatbot resides in the bank’s own private cloud, customers’ personal information is safe and secure.
Chatbots are increasingly becoming cheaper and easier to deploy, and even the smallest banks and financial services companies will soon be able to afford their chatbot. In fact, we predict that the presence of a chatbot in a bank’s mobile app will soon be one of the critical factors that convinces a customer to open an account with that bank.
We’re only beginning to see what chatbots in financial services industry are capable of, especially when they’re combined with other technologies such as big data, AI, machine learning, and natural language processing.
The possibilities are endless. Whether it’s combining a chatbot with virtual reality to illustrate savings and expenditures, using facial recognition for zero-touch banking, integrating mobile apps and chatbots with the Internet of Things for voice-powered transactions, or even providing real-time blockchain or cryptocurrency updates.
But at the end of the day, all of these new technologies should serve just one purpose: to elevate the customer experience. Customers know if a chatbot is there just for show or if it actually helps that purpose.