Typically, Banking Chatbots generate very better results and superior customer experiences for the banking industry and other financial institutions. For instance, they can assist bank customers to get the status of account balances. As well as transfer funds, apply for personal loans, credit cards, pay bills, check credit scores, and update financial profile information.
Routine customer interactions can be either fully or partially automated by introducing a digital assistant or banking chatbot that is available 24/7. The shift from traditional to digital banking, accelerated by the pandemic, has driven up demand for superior digital experiences.
An example of a limited Bot is an Automated Banking Bot. Not to mention, Chatbots in banking was one of the first adoption areas for Chatbot Technology too. And it’s one of the more sophisticated sectors in advanced Chatbot implementations.
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In that case, do you remember old Chatbots – originally incapable of anything but offering pre-scripted spam ads? The “Ask, and you shall receive” concept hasn’t actually worked until recent days. The progressive advance of technology has seen an increase in various businesses.
Whilst, moving from traditional to digital platforms to transact with consumers. Numerous businesses are also implementing AI techniques on their digital platforms too. One AI technique that is growing in its application and use is Chatbots.
Some examples of chatbot technology are virtual assistants like Amazon’s Alexa and Google Assistant as well. Not forgetting, some messaging apps, such as WeChat and Facebook Messenger too. That said, let’s learn more about these tools below.
What are Chatbots?
Chatbots are computer programs that simulate human conversation through voice commands, text chats, or both. Basically, a Chatbot, short for Chatterbot, is an Artificial Intelligence (AI) feature that can be embedded and used through any major messaging application.
There are a number of synonyms for Chatbot. Including “Chat Robot,” “Talkbot,” “Bot,” “IM Bot,” “Interactive Agent,” or “Artificial Conversation Entity,” etc. These tools help add convenience for customers — since they are automated programs.
So, they interact with customers like a human would and cost little to nothing to engage with. In most cases, Chatbots interact with customers like a human would and cost little to nothing to engage with. They also attend to customers at all times of the day and week.
This makes its implementation appealing to a lot of businesses that may not have the manpower. Or even financial resources to keep employees working around the clock. Some key examples are Chatbots used by businesses in Facebook messenger, or as virtual assistants, such as Amazon’s Alexa.
A Brief History of Chatbots
For your information, the first chatbot was developed in 1964 at MIT. Named ELIZA, it was the brainchild of computer scientist Joseph Weizenbaum.
It was an early example of a Natural Language Processing computer program designed to simulate human conversation. ELIZA was pretty basic compared to today’s AI-powered Chatbots. It used a basic pattern-matching algorithm to give the illusion of understanding but couldn’t actually contextualize events.
In the same fashion, it set the standards of how we interact with customer service chatbots, virtual agents, and virtual assistants today. As well as laying the groundwork for the future of human-machine communication.
In the 2019 report, ‘Competitive Landscape: Virtual Assistant Platforms, Worldwide’, Gartner outlined three common Chatbot architectures. Eventually, that most conversational agents you will come across on the internet are built on.
The Common Types of Chatbot Technology
Understanding the difference between the key Chatbot Technologies will help you make the right decision on which one is right for your business. Keeping in mind, the ideal characteristic of Artificial Intelligence is its ability to rationalize. As well as take actions that have the best chance of achieving a specific goal.
A subset of Artificial Intelligence is Machine Learning. It refers to the concept that computer programs can automatically learn from and adapt to new data without being assisted by humans. Deep Learning techniques enable this automatic learning. Through the absorption of huge amounts of unstructured data such as text, images, or video.
Today, these Artificial Intelligence Systems that communicate with people through messaging, text, or speech, are greatly evolving. While turning into a necessity in certain industries. After all, the major players in the field like Google, Apple, Microsoft, Amazon, Slack, etc. are building Bots too.
Generally, the common types of Chatbot Technology are either rule-based programming, computational linguistics, or rather machine learning (conversational AI). Let’s consider the 2 commonly used below.
Set Guidelines Chatbot
A Chatbot that functions with a set of guidelines in place is limited in its conversation. It can only respond to a set number of requests and vocabulary and is only as intelligent as its programming code. An example of a limited bot is an automated banking bot that asks the caller some questions to understand what the caller wants to be done.
The bot would make a command like “Please tell me what I can do for you by saying account balances, account transfer, or bill payment.” If the customer responds with “credit card balance,” the bot would not understand the request and would proceed to either repeat the command or transfer the caller to a human assistant.
Machine Learning Chatbot
A Chatbot that functions through machine learning has an artificial neural network inspired by the neural nodes of the human brain. The bot is programmed to learn alone as soon as it’s introduced to new dialogues and words.
In effect, as a chatbot receives new voice or textual dialogues, the number of inquiries that it can reply to and the accuracy of each response it gives increases.
A variety of sectors use such Bots. Some are also built for other purposes like retail bots (designed to pick and order groceries). Weather bots that give you weather forecasts of the day or week. And simply, friendly bots that just talk to people in need of a friend.
The Fintech sector also uses chatbots to make consumers’ inquiries and applications for financial services easier. Think of a small business lender that uses a virtual assistant to provide customers with 24/7 assistance through Facebook Messenger. Or a small business hoping to get a loan from the company. It only needs to answer key qualification questions asked by the Bot.
How Chatbots Work
Technically, Chatbots tend to operate in one of two ways — either through machine learning or with set guidelines. The operation of some chatbots is based on sophisticated Natural Language Processing (NLP) systems. But, many simpler systems scan for keywords within the input.
And then, these systems create a reply, using the most matching keywords or the most similar wording pattern, from a database. However, a Chatbot that functions with a set of guidelines in place is limited in its conversation. Since it can only respond to a set number of requests and vocabulary.
The Chatbot is programmed to work independently from a human operator. It can answer questions formulated to it in natural language and answer as a real person would. In addition, it is only as intelligent as its programming code.
Fundamentally, a Chatbot allows a form of interaction between a human and a machine. Whereby, the interaction happens via written messages or voice.
A Chatbot interacts through instant messaging, artificially replicating the patterns of human interactions. In that case, let’s consider the following user-based case scenarios. So, that you grab a dipper meaning of their workability in our daily lives.
- Machine Learning: Allow computers to learn by themselves without programming.
- Natural Language: A computer’s ability to understand human speech or text.
Originally, Chatbot communication was only text-based. However, as the technology improves, this interaction paradigm now extends to other input methods too. Including the touch and voice methods.
Likewise, they are also a form of the primary customer service channel. Simply, because they allow consumers 24/7 access to the brands they care about in a way that’s instant, familiar, and conversational. Thanks to Artificial Intelligence, the 21st-century Chatbot has really evolved.
It has evolved beyond simple question-and-answer logic into a swiss-army knife of automation and self-service. All in all, that can enhance not just customer support and service, but an organization’s operational efficiency, too.
How AI Chatbots Drive Business Value
As Microsoft CEO Satya Nadella says, chatbots are the new apps. In the modern world of business, Instant Messaging (IM) Apps like Pinngle are becoming more and more popular in terms of marketing, ecommerce, customer service, and sales.
Messaging apps like Pinngle allow businesses and brands to provide around-the-clock interaction and support. Such as instant responses, quick answers, complaint resolution, and more. In the real sense, messaging apps and chatbots are gaining more popularity for business purposes.
Chatbots offer a variety of benefits over legacy customer service channels such as phone, email, and live chat. With the help of artificial intelligence, enterprises can utilize the technology to not only empower customer self-service but also boost employee productivity and reduce operational costs.
In order to meet the requirements of larger organizations like banks, insurance companies, and telcos, Chatbots need Artificial Intelligence so badly. In order to enhance their ability to understand human language and perform more complex tasks and transactions.
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In relation to Chatbots, the larger organizations branch of artificial intelligence is called Conversational AI. Whereby, basic Chatbots are useful for handling a very limited number of tasks. They use rule-based programming to match user queries with potential answers, typically for basic FAQs.
Where basic chatbots show their limitations is if they receive a request that has not been previously defined. And as such, they’ll be unable to assist, and spit back a “Sorry, I don’t understand.” response. Below are some considerable facts you should know about.
Consider the following:
- Gartner: 70% of white-collar workers will interact with a chatbot daily by 2022
- Chatbots Life: Chatbots cuts down operational costs by up to 30%
- Juniper Research: Through Conversational AI, by 2023, there will be more than $112 billion in retail revenue
- Drift: There has been a 92% increase in usage of Chatbots since 2019
NB: Get the ultimate guide to Chatbots for the enterprise. Go ahead and download the comprehensive guide to learn everything you need to know about launching an AI chatbot for your business. Whether you’re just curious about automation or getting ready to deploy your 8th chatbot project (go, you!), you’ll find everything you need in ‘The Enterprise Chatbot Guidebook’.
Having said that, below is a list of key areas where Chatterbots can drive value to both businesses and consumers.
Consider the following:
- Respond to customers instantly eliminating the need for them to wait on hold
- Increase revenue by leading customers to the key products and services
- Keep costs down by doing the work of multiple employees
- Increase employee efficiency, freeing them up to focus on high-value customer interactions
- Open up new channels for sales, service, and support without tying up additional resources
- Bolster brand loyalty through dynamic and memorable self-service experiences
NB: You can download the full guide to learn more about how AI chatbots can improve your customer experience!
Conversational AI uses various technologies such as Automatic Speech Recognition (ASR), Natural Language Processing (NLP), Advanced Dialog management, and Machine Learning (ML) to understand, react and learn from every interaction. You can read and learn more about Conversational AI in detail.
Skills & Technologies Driving Chatbot Innovation
Surprisingly, Chatbots aren’t new in the tech world, though they have hit the mainstream only in 2016. In contrast to Chatbots of the past, the most sophisticated of today’s chatbots have the ability to carry on a real organic conversation.
For example, Enterprise Chatbot Solutions offer rich sources of data for further analysis. With the help of this data, brands are able to become more perceptive towards their customers’ needs. And by delivering personalized products and services, businesses optimize engagement, gain better relevance, and higher revenue.
Consider the introduction of ATMs almost sixty years ago to the first wave of online banking in the early 1980s. Technology-led innovation has made banking more convenient and more automated. Technologically, Internet Banking has gradually replaced the main street banks.
Learn More: 4 Great Examples of How Banking Chatbots Generate Better Results and Enhanced Experience
Most recently, there’s the introduction of mobile banking. Where interactions take place remotely through touchscreens, keyboards, clicks, and swipes on either the bank’s mobile app or website.
In reality, messaging apps simply outstrip other types of applications. The primary driver that stood behind 2016’s Chatbot outbreak decreased user interest in social media and messaging apps. Why? Since users don’t need hundreds of apps on their mobile devices to support each separate brand.
Messaging applications solve this problem – they are simple, easy, and fast. Thereafter, businesses follow their audience. At the moment more people are using the main messaging apps than social networks too. You can read and learn more about the leaders of modern AI tools and products in detail.
Clearly, in this era of technological advancement, there are numerous messaging apps that subscribers can choose from. Mainly, the messaging apps used for chatting. They make communication easy with respect to such as instant messaging and voice calls.
Perse, the majority of messaging apps are easy to install on smartphones. Regardless of the smartphone operating system. Bearing in mind, there are mobile devices that use Windows, Android, or iOS operating systems. Currently, apps are easy to download on the smartphone and chat straight away.
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However, it is important to acknowledge that different messaging apps have different features. Some of the common features of these apps include the ability to make voice and video calls. With add-on features for instant messaging and photo sharing. Most of them are also free!
Having said that, you can see the full list of the most popular messaging apps globally. And that’s all for now! So, do you think Chatbots are useful? Which ones have you used before? Let us know in our comments section below. But, if you’ll need more support, you can Contact Us and let us know how we can help you.
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