There’s a significant change underway. Finally we have a technology that encourages you to talk to us to find out what problems you have, that anticipates your needs and informs you of what is happening with your products and services.
It starts with a “bot”. “Short for “web robot”, a bot is a software application that executes simple, repetitive tasks (or scripts) over the Internet. Bots help when playing online games, scheduling meetings, checking the weather, or getting updates. The power of bots lies in the high speed with which they execute small routine tasks, so functions such as web crawling that humans would execute too slowly are automated and effective.
Things get more interesting when the bots are paired with a language interface that allows human interaction. The result is a “chatbot”, or a software application that completes tasks while communicating with users through chat, messaging, or natural language (voice) processing. If done well, chatbots make consumers feel like a real person is handling their requests through exchanges of words that mimic dialogue.
A chatbot can ask personalized questions, take orders, anticipate problems, and even suggest appropriate solutions. In essence, then, it can simulate experiences like shopping with an assistant in a retail environment.
If any of this sounds vaguely familiar, you’re right. Bots and chatbots have existed in some form since the dawn of the Internet. However, two factors are changing the profile and potential of chatbots. Their increasing sophistication means that chatbots are emerging as online tools to drive customer engagement, sales and service in ways that some think have the potential to revolutionize e-commerce. In addition, the rise of messaging applications and the availability of sophisticated artificial intelligence (AI) systems have paved the way for chatbots (both text and voice) to work.
There are two critical factors that contribute to the growth of chatbots. One factor is the growing dominance of messaging services. Messaging applications such as Facebook Messenger, WhatsApp, Slack and Telegram have overshadowed social networking in customer usage. The new generation of consumers is quite fluent with messaging as the main means of communication. Logic suggests that, if they are comfortable interacting socially through messaging applications, they may be equally comfortable interacting with banks through the same channels. It only makes sense that, to build an effective online business strategy, you go where the consumers are, and where the consumers are now is within the messaging applications.
The other factor driving the evolution of chatbot is the advancement of artificial intelligence. We are entering a new world of human-machine interactions based on natural language processing (NLP). The next generation of NLP algorithms is based on machine learning, which takes advantage of large volumes of data to build communication rules based on statistical inference. The power of these algorithms is pushing us towards ever higher levels of accuracy in the syntactic analysis of the machine and in the understanding of spoken or written requests.
The great potential of these conversational interfaces is their ability to help users perform all kinds of tasks, as they are able to understand the specific vocabulary and extract the correct meaning or intent from the statement.
The potential of chatbots, therefore, is their ability to provide individualized guidance, sales support, customer service and other business-related functions, and they do so anytime and anywhere, so that they integrate seamlessly into the life of the consumer.
In fact, in today’s world of connected consumers and commerce, business tasks that used to be scheduled at home are often done on the fly — waiting for the mic, enjoying a few minutes’ rest between meetings?
Working from the park while supervising the kids? There’s no reason not to shop, bank, book flights, order dinner or perform other functions as easily as if you had a personal assistant helping you.
Some have called this chatbot capability “conversational commerce” and see it as the platform for a paradigm shift in the way consumers interact with their brands. In fact, many companies are now jumping on this bandwagon, including liquor brands, sports franchises and consumer packaged goods companies. For example, Taco Bell is testing its “TacoBot” to allow customers to order and pay for tacos online.
Financial institutions are also jumping on the chatbot bandwagon. At Xentric we are working with BCI and Banco Santander, using both messaging and voice bots using chatbot technology. And experience is showing us that banks are well positioned to benefit from bots. In an increasingly mobile world, where banking is becoming virtual and moving away from the traditional brick-and-mortar branch, financial institutions must be prepared to help customers with their financial needs, wherever and whenever they occur. In this environment, digital engagement with customers becomes key.
So our bots can and are conducting routine conversations between a bank customer and the bank’s customer service staff. It is a growing trend that will only accelerate and help banks serve their customers with routine requests faster and at less cost than human staff, provided they are used properly and dialogues are established intelligently.
However, banks face special challenges when entering the chatbot arena. Not all chatbot experiences are created equal. As we have noted, bots are simply software applications; they are only as good as the data, software and systems behind them. Therefore, leveraging advanced data intelligence can give banks the ability to anticipate the major questions that consumers ask based on our data patterns, which in turn helps banks to respond quickly. A bot based on insufficient data, outdated platforms, poor integration or an inefficient architecture will provide a customer experience that reflects those gaps.
In fact, many of the bots launched to date have fallen short of expectations, or offer a poor experience (e.g., due to latencies in telephone communication). And while a poor customer experience is an inconvenience for any business, the stakes are higher in financial services. It’s one thing for your weather application to give you the wrong weather forecast and it’s another thing for your bank’s chatbot to get your checking account details wrong.
That’s why at Xentric we developed technology that incorporates AI from voice generation, understanding to syntax and sentimental analysis of conversations
The current state of chatbot development therefore offers banks an enigma as well as an opportunity. Chatbots are clearly a state-of-the-art customer service technology. However, they are a next generation technology with growing pains. Like other retailers, banks are looking at the possibility of going in the pool.
Is it smarter to be an early adopter and invest in chatbots with their current limitations, or to wait until the technology has evolved and risk being left behind by competitors?
The answer depends on the agility of your technology environment and customer service needs. At Xentric, we believe banks could be wise to invest in “preparing for the best robots to come — and ultimately, a fully automated yet high quality customer experience. ”
Whether a given bank decides to use bots or not, there are three key things it can do to take advantage of opportunities and minimize risks.
1. Decide which chatbot application is best for your situation. Chat bots can fit into many modes of customer engagement, including social media, mobile applications, instant messaging, text or voice. Bot technology can enhance a bank’s consumer touch points.
However, it makes sense to find the engagement platform that best suits your customer’s lifecycle. Some customer segments will prefer voice bots for collections, others will prefer WhattsApp
In addition, you need to design the point of contact that best suits your use case. What is your optimal distribution strategy? It may be wise to focus on something specific, such as collections or designing a financial concierge bot.
2. Be prepared to update technology and processes.
New procedures may need to be added or existing processes redesigned to better support new applications and mobile sites. Bank staff may also need training to effectively engage with new mobile tools for client engagement. The optimized user experience will require natural language processing as well as the data intelligence to support it.
In addition to understanding the vocabulary and intent of consumer questions, backend data models must provide the right answers. This is where data intelligence is key. By adopting state-of-the-art data intelligence solutions, banks will be able to provide users with a personalized chatbot experience through intuitive answers to the most frequently asked personal financial questions.
Bots offer the illusion of simplicity for the customer, however, much complexity is used to create that great customer experience. At Xentric we integrated an RPA into our solution, but have had experiences where the Bank already had another RPA but an inadequate implementation.
Users will be impressed by the way the chatbot can model different financial scenarios based on their custom information. A chatbot could even congratulate the user for getting a new job to further customize the experience (for example). By using machine learning and data intelligence, the chatbot is able to identify that the direct deposit was from a new employer, and why the user had stopped receiving deposits from their old employer.
The tool can remind users that a new job is a good time to review and optimize their APV or investment assignments. The Bank can provide the option of connecting with a financial advisor or account executive to discuss options, promoting the customer’s financial well-being and cross-selling additional products and services that benefit the user.
The challenge of a conversational text interface is that it puts a blank text box in front of the consumer. That is why at Xentric we have gone above and beyond and interact with the customer through all media or channels. Voice, web bot box, virtual phone assistant, SMS messaging or whattsapp are all part of the same experience of communicating with the institution.
We have seen that customers are less governed by the rules that computers and can ask questions that are beyond the capacity of response of the application, but today we handle a huge case that grows every day by learning about 300,000 conversations per month at the time of writing this document.
We are always thinking and redefining the scripts and logic of the existing system. We manage with an unambiguous vocabulary and with the expected questions that lead to obvious answers.
3. Understanding that context is key to the chatbot experience. “Context” refers to everything that makes the client feel that he is having a personal interaction with someone who knows him. That customer information includes account information, past behavior, current location, environmental factors, recent transactions, and user preferences. The more consumer data available to a chatbot, the more effective the interaction and service will be. Data intelligence and personalization are key.
And we have integrated all experience supporting institutions with topics ranging from collection (voice or text) to service bots and many other applications.
Don’t forget to give us your 👏 !