Chatbot banking is gradually inching in on the modern banking space, as banking organizations continue to leverage Artificial Intelligence as the solution to most modern-day banking issues.
In this short period, banking chatbots have stood as a viable market solution, by significantly reducing various running costs and steadily meeting the need of the increasing populace of tech-savvy consumers.
In many instances, chatbots were deployed to facilitate a much better two-way communication, between banks and customers without the use of channels like phone, email or text.
Chatbot Baking objective is to provide customers with quicker support.
At present, banking bots are equipped to undertake some basic tasks like bank account details, balance inquiry, loan queries, and more. For customers, this cuts down waiting time significantly, leading to a more positive banking experience.
In future, artificial intelligence (AI) and other new digital technologies soon to come, will provide more expanded forms of engagement between the bank and customers, we may probably see a move beyond bots into digital voice interactions.
For banks, the projection is that chatbots will be responsible for over $8 billion annual cost savings by 2022.
The financial sector is one giant puzzle of data, beginning from the consumers down to CXOs and vice-versa. Fostering a better communication link between customers and bank is pivotal to the survival of the banking industry. On that note, forward-thinking banking institutions have taken to chatbots to help with the prompt delivery of ‘contextual insights’ to individuals in need, through various channels.
With the ever-increasing growth in AI technology, and the conversational approach through which bots communicate with consumers investors are beginning to see chatbots as new-age contact centre executives, helping to minimize TAT and costs along the way.
Functional chatbots can answer questions such as:
Financial institutions across the globe are continually accessing the possibility of deploying chatbots for varied objectives
In a bid to proactively deliver insights to their digital-savvy customers in real-time and based on preferences, financial institutions are now testing out new and innovative technological approaches to communicating with customers, with chatbot coming out on top.
Some of the issues these innovations seek to address are:
As Firms keep experimenting with chatbots that allow customers to make authentication based on voice samples which then helps complete transactions quickly, it is safe to say that the days of communicating via multiple options input on an interactive voice response (IVR) system are numbered.
30% of the typical senior management time is spent on operations and other miscellaneous tasks. Out of this 30%, over 60% is occupied by getting the desired metrics from different MIS/IT teams and departments and follow-ups.
With chatbots, the time spent by CXOs on operations will be reduced drastically. Information will be provided quickly to various parties, resulting in more focus on other strategic business objectives.
As banks seek to provide a plethora of services to their customers, not every service can have the correct taker for it. Thus, to give customers these personalized services, banks can accomplish their particular goal by deploying chatbots. The delivery of customized services can improve the overall rates of conversion by 25%.
Chatbots provide a host of significant benefits to employees that help increase work productivity and save their time.
Some of the activities include personal details assessment, payroll details, live application, contact info update, performing a detailed review of timesheets and much more. This aid in increased productivity during work hours by employees.
With new-age financial services companies and FinTech companies giving others a run for their money, banks have joined the race to promote a new form of engagement between them and their customers.
While using several channels to engage with the customers is fast becoming the norm, the challenge is in getting the right value out of each channel.
Instead of developing communications solutions for each channel like website, mobile app, Text Messaging service, automated emails, social media messenger, etc., banks can now develop a single bot that can ride across the platforms offering a holistic communication channel across all platforms. Quite simply, the customer can choose the channel that suits them but will get the same experience.
Chatbots are quickly arriving at a point where they will be unable to handle queries requiring knowledge outside their programmed domain suitably. It is, therefore, vital for financial institutions to begin to enhance chatbots capabilities.
These improved capabilities will provide a completely different experience for customers as they will be benefiting from combined knowledge across relevant segments.
A new level of conversational banking is expected to arise from this, as queries are answered instantly through real-time conversations, thus enabling better decision making for customers.
When a customer logs into his/her account, they can get a warm greeting or information on customised offers for her/him, adding a new dimension to the power of ‘personal touch’ and massively enhance customer delight and loyalty, rather than the conventional pop-up notifications or banners that is noticeable in most valuable real-estate.
During the conversation, the chatbot will be able to use advanced speech, natural language processing techniques, sentiment, and analytics to offer solutions that are correctly customized to the customer and the general context of the conversation.
Such an enhanced level of customer engagement and will provide another sense of customer satisfaction, thereby increasing customer loyalty without the need for manual interaction.
Chatbots could be designed to develop ‘insights-driven bank.’ A typical use of such innovation would involve accurate and instant better decision-making process that is driven by data-based analytics.
Chatbots can be designed to respond to various kinds of requests and queries ranging from sales and marketing, to impact of global trends, new product launches, and internal metrics such as employee attrition and sales targets.
Some examples include:
AI technology provides an avenue for real-time responses to such queries through predictive analytics and recommendations based on prescriptive analytics; this can significantly enhance the decision-making process of any firm.
Financial institutions can now seek newer ways to partner with technology firms and leverage innovative technologies, having achieved a certain degree of maturity in chatbot deployment in recent years.
Here are a few potential areas of exploration:
It is therefore imperative to think beyond what’s observable currently to create use cases for chatbots in the future.
Since the start of 2017, RBS has deployed a text-based chatbot called ‘Cora’ which customers can access through the RBS online help pages.
At present, Cora can answer 200 basic banking queries and has 100,000 regular conversations each month. In recent months, taking advantage from advances in artificial intelligence and computing power, Cora the digital human was built to provide a more life-like digital human presence where customers can have a two-way verbal conversation on screen.
Cora can provide answers to basic verbal questions like “How can I login to online banking?”, “How can I apply for a mortgage?” and “What do I do if I lose my card?”
The technology relies on using audio and visual sensors, which are standard in modern computers and mobile phones.
HSBC: one of the worlds largest banking and financial services have multiple chatbot proof of concepts across the globe in action.
We’re currently working with HSBC US to increase operational efficiency and help customers get swift and effective answers to their queries. HSBC engaged Filament.ai to develop AiDA (automated immediate digital assistant), which now provides the first layer of Customer Service on the HSBC US website.
AiDA went live at the beginning of June 2018 and is on a path of continuous improvement, with ongoing monitoring and re-training daily and a number of new flows and intents planned for the near future.
As well as the core bot development, Filament.ai supplied HSBC with Enterprise Bot Manager.
This portal contains enhanced analytics and deployment capabilities, empowering HSBC to analyse AiDA’s performance and make continuous improvements in-house. So far, calls handled by the banking chatbot have been reduced by 90%. Originally costing $7.50 down to $0.62
There is also a chatbot in Hong kong: Amy.
Amy is of Chinese origin but is also available on mobile and desktop in English, and Traditional & Simplified Chinese.
The technology incorporates an embedded customer feedback mechanism that allows Amy to continually learn and enrich her knowledge to cope with the increasing number of broad queries. There are plans of upgrades where Amy will be integrated into live Chats with humans, to help with seamless intervention on more complex questions.
Amy provides 24/7 instant online support to customers with inquiries and is available on several product pages with hopes of a broader coverage in the nearest future.
KAI is a MasterCard banking chatbot built to run on various bank’s messaging platforms and devices (mobile and desktop inclusive).
KAI is built upon years of industry-specific knowledge and aims to help customers with payments, account insights, transactions, and finance management.
Using AI reasoning, natural language processing, and speech recognition technology, Kasisto claims that KAI is capable of intelligent, human-like conversations via text and voice, and can extract meaning and intent in communication.
KAI can also be deployed to multiple channels such as messaging, mobile, and websites. the company claims through its website that KAI can also be used on Internet of Things devices, but has not specified or demonstrated this function
In the first six months of Eva’s deployment, it successfully addressed over 2.7 million customer queries to become the country’s largest banking chatbot.
According to reports by HDFC Bank, ‘EVA’ (Electronic Virtual Assistant) was launched in March 2017 on the banks’ website and has interacted with over 530,000 unique users since then, holding over 1.2 million conversations and addressing approximately 2.7 million queries with ease.
According to a statement by Shridhar Marri, co-founder and CEO Senseforth, “‘Eva’ currently handles 50,000 plus semantic variations for thousands of banking related intents, tracks, and analyses everyday customer issues and gains a deeper understanding of their behaviour patterns,”
Reports from the bank were recorded to attribute an accuracy level of over 85% to Eva and an uptime of 99.9%.
Helping with Branch addresses, IFSC codes, loan and interest rate information are a few of the things that EVA does.
Credomatic is a full-service bank chatbot that serves customers across these six Latin American countries: Panama, El Salvador, Costa Rica, Nicaragua, Guatemala, and Honduras.
As technology continues to advance rapidly, affecting the banking industry, only by responding to customers’ needs can financial institutions stay ahead of the curve, which is why in a bid to consolidate its position as a leader in banking in Central America, BAC Credomatic has taken a proactive approach by migrating its website to a far more robust and responsive customer management system to enhance the user experience (UX).
Rather than going after trends, BAC Credomatic is setting the pace in the digital banking landscape across the Central American region.
Wells Fargo’s chatbot incorporates artificial intelligence and Facebook Messaging into one to communicate with costumers in natural language. Queries such as how much money you have in your accounts, and where the nearest bank ATM is can be answered in seconds.
Wells Fargo Facebook integration sets an introductory path for banking organizations to follow since this is what most customers use chatbots for.
The process starts with a simple registration, after which customers can query the chatbot for their account balance, how much they spent on food last week, most recent transactions, the nearest ATM, among other things. The chatbot employs a Request by request method and provides answers immediately.
Wells Fargo’s banking chatbot for Facebook Messenger is the company’s latest effort to engage and serve customers directly on through social media; the chatbot works via desktop, smartphone, and other mobile devices — through an artificial intelligence-powered chatbot.
Cleo is a London-based start-up that offering AI-powered chatbots as a replacement for your banking apps. Cleo began quietly offering its service to UK customers in 2018 and signed approximately 1,000 users per-day.
In the US, there is a similar version of Cleo available too. It is described as the “alpha version,” by the chatbot itself, and support 647 banks and counting across the states. Cleo employs the same conversational interface as its UK version; however, it tries to replicate the American dialect into its conversation pattern.
Cleo provides various queries such as your spending across multiple accounts, and credit cards, transactions based on merchant or category.
Also, Cleo provides help with your decision making on several actions, based on the financial data it has gathered from you.
Cleo also features Facebook integration where you can send money to your Facebook Messenger contacts; you can also donate to charities of your choice, setup spending goals, and create alerts on other financial obligations.
Cleo’s primary targets are tech-savvy millennial. It hopes to introduce a more accessible and intelligent way to manage money and ultimately become the default financial control centre for most millennials. Some other services offered by Cleo include: recommending ways to save money and an automatic switch to the best value products when making decisions, whether that be financial or other services such as utilities.
From our experience, banks come across these 5 challenges when implementing chatbots:
We write more about this in our article: “what does it take to implement a chatbot?” here
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