Reasons Why Chatbots Can Take Over Banking

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Not many people are comfortable letting others know the state of their finances – their current-account balance, size of mortgage, loans, even how much they earn.

Money is, after all, private. Which is why chatbots are going to be big in banking.

A chatbot is the closest channel we have to going into an actual branch to talk to a member of staff.

It’s one-on-one, private and – when done well – the conversation is held not only at a level appropriate to the customer, but also in their style of language and at a time convenient to them.

It’s a universal interface, too – so no one has to learn how to use it – and they tend to sit within an existing chat platform such as Facebook or WeChat.

All this is important. For the customer, its intimate nature ticks the privacy box; the appropriate level of communication and language tick the personalisation box; and the lack of differentiated interface and the fact that you don’t need to install them tick the ease-of-use box.

From the banks’ point of view, it opens up a direct line of communication that can be used to build a deep relationship – one less likely to be thrown over by a rival.

Chatbots are AI-enabled, text-based communication tools. They learn users’ language styles, picking up their words and expressions rather than remaining stuck with a vocabulary compiled by the programmer and bank’s marketing department.

So if you say “pay the gas man”, it knows to transfer money to the gas supplier; similarly, if you say “move three grand to savings”, it knows to move $3,000 to your savings account.

It’s much more like talking to a human than using a menu could ever be.

The quality of a chatbot will be measured by how quickly and how well it learns to understand the account holder.

And a good chatbot service will get more personal and more proactive over time.

The payback for banks is clear: as anyone in sales knows, mirroring the target’s speech patterns and language builds empathy that helps clinch the deal.

This is exactly what Cleo does. An AI-enabled chatbot from London, Cleo sits discretely within the Facebook platform – although Facebook has no access to Cleo chat or a user’s bank data.

Messages pop up from Cleo about a user’s finances and with information that the user might find useful – when their salary has come in, or overspending in a category like entertainment.

Notifications can be viewed by users at their convenience.

Although this information may be available from the bank’s mobile or internet service, Cleo is more proactive and engaging by making interactions much more timely and relevant to the individual user’s circumstance.

Cleo allows the user to be in control. It is the user who sets the frequency and tone of contact. The user can also initiate contact, asking questions or giving instructions.

As chatbots develop, their role will expand to become more proactive – helping users achieve goals, avoid fees and better manage their money.

For example, they will track spending, spot when it is lower than normal and suggest the difference is moved into savings.

Over time, this proactive role will deepen, so that with prior consent, chatbots could move money between accounts, pay invoices, set up direct debits for regular bills and find the best deals for savings accounts, credit cards, utilities and maybe help with automated switching of products like Flipper does for utilities.

The chatbot Finn from JPMorgan Chase also already does some of this. It acts as a savings coach, prompting users to round up transactions to save faster.

For this to work, the user has to give the bank consent to act on their behalf – something that will become as common as a user giving consent for apps to access phone features. And it will mark an important watershed.

When banks have users’ consent, they will be able to take a truly holistic approach to managing users’ money.

Their role will not be limited to advice. Once informed of a customer’s goals, banks can automate many of the decisions or tasks customers have to perform to manage their finances.

Keeping the customer informed of actions and the reasons why the action was taken will then become as key as getting consent for actions.

This type of service will develop hand-in-hand with ecosystems featuring different companies, services and sectors.

If banks get their chatbots right, they will be at the heart of these ecosystems.

Not only will banks be able to help people save for and buy a house, but they will also find that house, rate it environmentally, suggest lawyers, surveyors, builders, and assess whether it’s priced fairly.

Intelligent bots might also be able to warn clients when they are overspending or encourage them to save for a forthcoming holiday – which the bot knows about because it scouted the best deals, booked the flights and hotels, suggested suitable excursions and ordered the taxis to and from the airport.

People are always likely to want their financial affairs to be private and personal.

Private banks have excelled at satisfying this need for the few. With chatbots, all banks will soon be able to play such a role for everybody.

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Chatbots Using Artificial Intelligence are Selling Insurance in 2019


In fact, over $2B is estimated to be invested throughout 2019 in these InsureTech companies. Artificial Intelligence, Automation, and Blockchain are driving technology disruption in the insurance industry. They are making insurance shopping experience much better for consumers.

Meanwhile also improving service for policyholders who need help with renewals, claims, and add-on products and services. This is great news for just about everyone, while some insurance agents are getting really worried. Fear of losing their job due to technology is a valid fear. But the good news is that great insurance agents are not going anywhere. Even though AI chatbots are selling insurance and assisting policyholders in 2019, they will always come back by a great insurance agent.

Why Insurance Chatbots?


Well, technically insurance chatbots have already been around for some time.

Insurance Giants like Geico and Allstate have already been using them in their business.

Here are a few more reasons chatbots are being developed and used:

  • Next-gen chatbots are becoming more and more utilitarian. The term “utility” in this context means something we find so useful that we turn to it on a daily basis without hesitation. The focus would be on improving the competence of the chatbot to execute specific tasks flawlessly, rather than try to be a catch-all conversationalist and source continued engagement.
  • Chatbots are personalizing customer experiences. Successful chatbots will work to understand using machine learning over time to learn and understand the nuances of the user’s requests and improve the first-contact resolution. The greater the ability to personalize responses will make the customer experience even greater.
  • Chatbots are now specialized. Users need to know exactly what the chatbot
  • does and be confident that it will do these things well. For example, Leadsurance’s chatbot for insurance agencies does very specific insurance tasks, flawlessly. First, it segments a user into either an existing policyholder who needs assistance or a consumer looking for a quote. And then it executes the quote needed or provides the assistance requested. This means customers can get 24/7 help through the bot instead of trying to connect with an insurance agent.

So, now you can see why chatbots are more than just a fad.

They are actually really useful to consumers, policyholders, and insurance companies.

Saving everyone time, improving the experience for everyone, leading to better relationships and better business. Resulting in serious disruption in the insurance industry.

How the New Technology Works


Although many of these new tech companies aren’t about to give out their secret recipes, here are some things we learned about the new technologies while demo-ing products.

  • Chatbots can integrate with a wide variety of existing insurance marketing and CRM systems. Even legacy systems being used by old insurance companies can be integrated with Leadsurance’s chatbot for example.
  • Chatbots can be customized for your agency. Just about every aspect can be customized so that your chatbot is fully branded and even represents the messaging your agents would use in a conversation.
  • They don’t sleep. Your website will be monitored 24/7 to assist your existing policyholders while also quoting new prospects.
  • They’re clever. You can customize them to do and say just about anything. Want to collect people’s emails before starting a convo? No problem. Want to wait till the end and then also politely ask for a phone number? That can be done. You can even have the bot take the user to different pages on your website and continue the conversation helping them through forms and other activities performed on your website.

What We Thought About the Bots

So, as you can see, we didn’t get to view the code under the hood.

However, from the chatbot products that we test drove, we can tell that the tech is already powerful. When we talked about future roadmaps and plans for these technologies, we realized that these bots really are the next big thing in the insurance industry. Admittedly, there was something cool about being greeted by a little humanoid thing on the screen, that quickly warmed me up and learned my name.It then proceeded to give me a personalized conversation and experience shopping for life insurance quotes.

It was engaging. It was quick. It was easy. All important things to the modern consumer, especially in 2019. But like we already said, even though AI chatbots are selling insurance and assisting policyholders in 2019, they will always come back by a great insurance agent.



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How The Development Of AI Has Advanced The Technology Available For Chatbots


Artificial intelligence (AI)-powered chatbot platforms are taking the world by storm and revolutionizing diverse industries, but before AI was commonplace in chatbots, they were powered by different technologies that were not necessarily intelligent. Chatbots existed as early as the 1960s, and they have rapidly evolved since the development of AI. Today, chatbots are capable of performing incredible feats that come very close to human thinking and thought-processes.


This mimicry of the human thought-process comes from a chatbot’s ability to set goals and pursue them autonomously without any specific instructions — an ability referred to as a chatbot’s agency. This ability (AI) is the reason why chatbots are making a splash in areas such as customer service and sales today.

Chatbots Revolutionizing Customer Service And Sales

I think chatbots are the future, especially in customer service and sales. Here’s why:

1. Intelligent Chatbots Can Provide Preemptive Customer Service

Feeding on thousands of chats and their data, smart chatbots can be trained to recognize important patterns that indicate distress, frustration and annoyance and respond to issues before they escalate.

2. Smart Chatbots Can Reduce Training And Operation Costs 

While human customer service agents need to be trained from time to time, based on new products and emerging customer behavior trends, intelligent chatbots need to be trained only once. They are self-learning and update knowledge autonomously.


3. Autonomous Chatbots Can Handle Customer Service 24/7 

With human customer service agents, you have to hire in shifts to enable 24/7 customer service, which can double your operations and training costs. Autonomous chatbots can enable the same quality of service at no extra cost.

4. Intelligent Chatbots Can Scale The Volume Of Customers Served

From a logistics perspective, human customer support agents can face bottlenecks with support queries. Chatbots, on the other hand, can attend to customers simultaneously without deteriorating the quality of service provided.

5. Smart Chatbots Can Personalize Support With High Accuracy 

Sales managers may fear adoption of chatbot technology because they assume that bots take away the human touch and lack personalization. The opposite is actually true. Intelligent chatbots have the potential to greatly personalize conversations, based on their vast stores of highly-organized data that humans can’t compete with.

Stages Of AI, And How They Can Be Applied In Chatbots Of Different Kinds

Over the years, bots have evolved in their intelligence and abilities, shedding old avatars for newer and more advanced ones. To understand what AI technology’s development has done for chatbots, you have to be exposed to the stages of AI’s evolution and what each stage had to offer in terms of abilities.

Stage One: Cue Readers

Chatbots in stage one have no real ability to understand what you’re saying and simply pick up phrases from your speech that they then match to an internal database before spouting scripted answers. However, such chatbots have the interesting ability to insert amusing fillers in conversations to prevent their lack of knowledge from betraying their limited capabilities. That’s why developers don’t fully ignore stage one and give it some importance, as the later stages pay little attention to emotion and personality in conversations.

Stage Two: Form Fillers

Chatbots in stage two are designed to perform very specific tasks such as making a restaurant reservation or ordering food for delivery. These chatbots have built-in forms that specify all the information that they need to receive from customers and continue making conversation with people until they have filled all the blank spaces. Such chatbots not only go by important phrases but also follow certain rules written by their programmers.

Stage Three: Intent Readers

Chatbots in stage three are akin to talking encyclopedias and are trained to run search queries for the information they need to converse. Such chatbots are constantly indexing information in massive databases from which they pull facts when needed. These bots can do much more than just state facts — they can also identify the part of speech being used by customers and accordingly generate answers to satisfy those queries.

Stage Four: Connection Makers

Chatbots in stages one, two and three are inept at holding long-running conversations with customers. This is because they typically read each sentence of a conversation separately without making interconnections between sentences. Bots in stage four, however, store histories of conversations and can draw from them to make highly coherent and relevant answers. Such bots are even capable of learning based on previous conversations and can constantly improve their ability to have conversations.

Stage Five: Problem Solvers

Chatbots in stage five understand the core problem that a customer is trying to solve. While you could program bots in stages one to four to search for solutions based on certain phrases, bots in stage five can solve such problems more efficiently. For instance, if a customer wants to catch a bus to a destination at a certain time, bots in stages one through four can check if such a bus is available and relay the information, but bots in stage five can suggest alternatives if such a bus is not available.

Stage Six: Companions

Chatbots in stage six are what developers dream of and sci-fi authors write about. Built somewhat like the robot Sophia, chatbots in stage six should have the ability to maintain dynamic and broad conversations that are not limited by subject or depth of any sort. Such bots can replace humans completely in most situations that require autonomous-thinking.

Autonomous chatbots are changing the world every day, and I think a future where such bots run most business tasks is not far away, considering the continuing development of AI and the technology that supports chatbots.


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Can AI and Chatbots really transform customer support?

Chatbots are changing the way companies and customers interact: two billion-plus customer-company conversations in Facebook messenger can’t be wrong. Join this FB Live event to find out how to create engaging human-to-AI agent experiences, and leave with actionable ideas on implementing AI-powered customer support.

Here’s a wild, off-the-cuff guess: You might have heard that AI is ride-or-die for companies that want to stay competitive (possibly also somewhere on this very site). You might have also have heard that it’s expensive, complicated, too difficult to implement or too hard to control.

But for consumers, there’s a growing interest in chat interactions with companies — look at both the two billion conversations companies conduct with their customers over Facebook Messenger every month; look at the study that found 49 percent of customers would prefer to interact with companies via automated methods than any other medium. And companies like Marriot, Sephora, Coca-Cola and 1–800 Flowers are starting to see returns.

Credit the growing sophistication of AI-powered tools and machine-learning bells and whistles that support an engaging, civilized chatbot-customer interaction. Add to this the number of popular consumer platforms that support business chatbots, from Facebook Messenger again to WhatsApp, WeChat, Slack, and more. But building your own sophisticated in-house solution is also easier than ever.

With chatbots, you can answer basic customer queries in minutes ( reports that most issues are handled in five minutes or less, via their chat agents). Just think about the 80/20 rule which often applies in customer service: the same questions are asked 80 percent of the time. Integrating chat into this equation can bring not just significant ROI, it also means your human customer service agents are engaged in handling the more important, business-critical issues that arise (and happier doing more complex, meaningful work, too.).

Chatbots never sleep, so someone with insomnia and a pressing question, or global customers across a spectrum of time zones, will always be able to contact your company and get their basic queries and requests handled.

And chatbots armed with AI-enabled personality can even help uphold your company image.

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Survey Clearly Shows That AI Can Greatly Improve Revenue

Image result for aiAI, although fundamental for customer insight, cannot function effectively if it can’t harness the correct data across the business.

But companies have challenges when implementing new marketing techniques — especially in light of the General Data Protection Regulations (GDPR), which comes into force on May 25.

San Francisco, Calif.-based AI marketing company Blueshift has released a report detailing the current use of AI and future plans for its use across businesses.

It worked with SurveyMonkey company TechValidate in February 2018 to survey 200 business-to consumer companies about use of AI, access, and use of customer data.

It wanted to see the types of AI techniques being used, challenges encountered with customer data, and the major obstacles to AI adoption across industries. Its study shows that 64 percent of brands want to increase their use of AI in the next 12 months.

Companies are working out that the ‘right data’ to use is first-party data, gathered from their own customers acquired with the customer’s consent and trust. This is in contrast to third-party data that has been packaged and resold.

This data is usually acquired in the course of doing business with a customer, who has provided explicit consent to its use by the brand, as long as it is not sold or used by others.

This seismic shift toward first-party consent has ramifications across the industry, as brands pivot their businesses to ensure they capture relevant data — direct from the customer.

The study showed that 64 percent of businesses have started to use AI to expand their audience base, and for product recommendations and campaigns. Most brands anticipate increased usage of AI in the near future.

However, only 6 percent of brands reported using advanced AI and predictive capabilities to its fullest extent.

Almost all respondents (92 percent), said that one or more of three factors — analysis, access or unification — was a major challenge that prevented them from making better use of customer data.

Over half (54 percent) saw analysis as a top challenge, followed by access at 46 percent and unification at 41 percent.

Yet, activating more customer data, and using real-time data to frequently segment customers, was reported to have a significant impact on revenue performance

Survey shows that three quarters of businesses improve revenue with AI ZDNet
(Image: Blueshift)

Respondents reported a 1.4-times uplift in revenue goals when using 75 percent or more of customer data compared to companies that used 75 percent or less.

Activating more customer data for AI-powered outreach is important for enterprises. Putting your customer data to work using AI will give you real-time behavioral data that your customers generate.

You can then use your engagement and transaction data across multiple touch points and channels to ensure the maximum possible conversions for your brand.

AI and machine learning can produce background checks on people and companies in minutes instead of days.

IT pros are not confident their organizations have the skills to take advantage of AI

Although enterprises want to implement chatbots in the workplace, privacy concerns are an issue for some.

Qordoba adds AI emotion scoring to product content to improve user experiences

The ability to gauge emotion in product content helps brands measure that the brand is on message across all products.

This article was originally posted on zdnet –