7 potential use cases of chatbots in banking AI Technology

Despite the increase in online banking, banks hadn’t expected not having face-to-face contact with people for a prolonged time or not having employees working in their offices. Banks are consequently preparing themselves to meet these challenges in the future and to not fall for the same mistakes. This means responding efficiently to challenges such as outbreaks and finding solutions that can guarantee business continuity regardless of any crisis.

Banking chatbots may be realized within dedicated mobile banking applications or be an integral part of banks’ websites. Custom AI assistants are generally more effective and secure as they are developed using precise specifications and under the strict supervision of a particular financial organization where the bot will be integrated. Ready-made solutions are generic bots that are built with maximum versatility in mind but still allow a certain degree of customization.

Benefits of Chatbots in Banking Sectors

There are several programming languages that can be used for developing chatbots for mobile or web apps. These languages include, for example, PHP, Java, Ruby, Closure, and some others. However, Python tends to excel in this area due to its impressive set of advantages and an extensive set of libraries and frameworks. More importantly, Python also has a number of useful libraries for machine learning to combine with language processing.

Fintech companies are already leveraging AI to improve the customer experience, especially in providing them with products and services that are catered to their needs. When accessing their bank account through chatbot, customers can use the conversational interface to complete basic transactions. This includes basic tasks like transferring money between accounts and making bill payments. We’ve seen how introducing a banking AI chatbot allows banks to automate customer inquiries, but they can be used to do so much more. In this section, we’ll look at some of the most popular tasks and queries that bots can handle in banking and financial institutions.

Chatbot Use Cases in Banking #1. Checking account/card balances

Users are increasingly looking to manage their money quickly, easily, and efficiently on a daily basis, and it is important for banks to meet these expectations. Anirban Guha is a seasoned Inbound Marketing & Communications professional currently working with Kore.ai, an enterprise-grade chatbot platform. He is a keen observer of the latest technology trends and loves to write about them. Yes, you can deliver an omnichannel experience to your customers, deploying to apps, such as Facebook Messenger, Intercom, Slack, SMS with Twilio, WhatsApp, Hubspot, WordPress, and more.

The main purpose of chatbots in banking is providing a better customer experience. However, they also help the staff and prevent stressful situations that arise from direct communication with clients. Businesses today come across a wave of customer service inquiries on a daily basis. Most people today express contempt for banking hours and there’s a genuine reason for that. For years now, artificial intelligence and machine learning has played an important role in digital banking customer service.

The Rise Of Conversational AI in the Finance Industry

One of the biggest concerns in the financial services industry is the data privacy. You can set bots to flag up any suspicious activity and stop the damage before it happens. They monitor the customer’s account and identify any warning signs of fraudulent activity. If bots identify a problem, they alert the bank as well as the client of the suspicious activity.

On the other hand, it is also imperative for the firms to recognize the possible pitfalls and employ sound controls over the technologies like AI to prevent and mitigate possible future problems. In the financial sector, AI is omnipresent and there are more obstacles, including legal, political, economic and social barriers. The global financial ecosystem is also continuing to be subject to new complexities.

CONVERSATIONAL AI

According to the research done by Accenture, nearly 57% have accepted that chatbots can bring significant ROI without much effort. According to statistics, banking agents save 4 minutes of their time for every query handled by a chatbot. Once they are installed, they use the provided data to solve multiple customer queries simultaneously while collecting more data from customers to update information and improve the quality of service. The use of virtual assistants by financial institutions to help banking customers save money, manage their bank accounts and XYZ is on the rise. Customers increasingly expect effortless and proactive customer support and banking bots are delivering the experience that customers expect. With AI and machine learning technology, banking agents can save up to 4 minutes per query when utilizing a chatbot.

The information is extracted from the legacy systems, and it is then verified by financial specialists. RPA has the ability to integrate data from numerous legacy systems and efficiently process it, having no faults. The integration and interaction of legacy systems is one of the key advantages of applying RPA in financial services. AI’s ability to sift through big chunks of data will aid banks in providing wiser strategies and exceptional customer experiences. In the event of potentially fraudulent account activity, chatbots can be a great way to alert customers. Since customers may not always be available by phone, it’s important to reach customers quickly via other channels so that they can validate or deny any suspicious activity.

Chatbot Use Cases in Banking #7. Exchange rate or stock price questions

Since chatbots can resolve more than 91% of chats from start to finish without human intervention, they also create additional support capacity for agents handling complex issues. With chatbots handling simple customer inquiries, agents can more quickly respond to complex issues that need human intervention. We use an Agile development process using sprints, releasing features little and often to meet the story features. We work closely with our clients, always testing, improving the bot flow, the conversational knowledge base, the bots personality and the overall user experience.

• Branching from artificial intelligence, natural language processing (NLP) refers to an applications’ ability to understand and recreate text or spoken word with human-like qualities.
• You can now track your expenses and see reports of them without having to contact the bank each time you need this information.
• Fintech organizations are using AI-enabled conversational interfaces to interact with customers instantly by replicating the patterns of human conversations.
• While chatbots might serve as a starting point, customers generally want to transfer to a human advisor.
• Due to Artificial Intelligence, chatbots can pursue and continue a conversation.
• Banking chatbots are revolutionizing the way consumers interact with their financial institutions.

Banks have not fallen behind in providing digital services and have been catering to customer demands for self-service for some time now. With many customers preferring to carry out transactions on their own, without needing to queue to meet a bank employee or respect working hours, banks provide self-service capabilities like Kiosks or ATMs. Customers can benefit from receiving personalized assistance on the channel and language of their choice, but so too can employees. The wide variety of banking use cases for chatbots continues to offer direct cost savings to institutions, helping to lower the average 1$ trillion dollars spent on customer service calls. As a result of rapid digital transformation, chatbots are a clear example of how technical solutions create numerous business operation benefits within the financial sector. As machine learning increases in its technical capabilities, expect chatbots to solve customer service requests with greater accuracy and improved speed, further delighting customers.

How Banks Can Add More Value with Tech Advances in the World of AI?

Book a demo today and one of the Unblu team members will reach out to offer advice. As a consequence, the customer experience radically improves and satisfaction levels climb significantly, which directly influences loyalty and retention levels. When customers have a simple task, any delay can be frustrating and receiving prompt answers makes all the difference. The inclusion of AI in digital banking processes is no longer the future but the present. And over time, this area will develop even more rapidly, offering previously unseen innovative opportunities. There are all preconditions that AI will soon transform absolutely all aspects of the financial sphere into a modernized and much more advanced model.

• Today, we live in a fast-paced world where it will be senseless to expect your customers to wait for hours before your support team finally turn up and resolve the issues users have.
• While their progress is unrelated, it has certainly led to a merger as more banking financial institutions are exploring AI applications to improve their services.
• However, this is nothing to fear about since most of the changes enabled by AI in the banking industry are for the betterment of the industry.
• This not only saves time but also helps to increase productivity as the employees have to spend less time looking for documents they need.
• Within the case of a talking interface, this is often considered the primary level of processing because of the absence of the requirement for audio-to-text conversion.
• AI-based banking chatbots offer a viable alternative to human personnel in providing a whole spectrum of information for company services and latest propositions.

Built with IBM security, scalability, and flexibility built in, Watson Assistant for Banking understands any written language and is designed for safe and secure global deployment. Use the conversational interface of chatbots to boost customer engagement and gather valuable customer feedback. Leverage the user inputs in the easiest way possible to improve the delivery of banking services. Amy is an advanced multilingual AI chatbot in a customer service platform at HSBC Hong Kong. Clients of the bank can access Amy via the official website and use the bot for various kinds of financial services or request support in terms of mobile banking.

Complexity vs Effort Based Estimation

Criminals can create their own chatbots to impersonate these programs, tricking customers into providing sensitive data. Wells Fargo uses Facebook messenger as well as AI chatbots to respond to user queries. It provides information like which is the nearest bank ATM and their account balance.

Checking account or card balances is a top user request, as 36% of Americans check their balance daily. Not only can conversational banking chatbots resolve issues in a prompt metadialog.com and efficient manner, but they can also help generate qualified leads. During a conversation with a customer, they can suggest particular banking products and gauge interest.

• Just a few questions to answer, a quick credit score check, and approval in seconds.
• The strategy should also take into account changes in the frequency and complexity of the request.
• Chatbots in banking can help streamline transactions like money transfers and account balance checks via a conversational interface so that customers are constantly guided through their actions.
• What’s Going On in Banking podcast, Ron is ranked among the top fintech influencers globally and is a frequent keynote speaker at banking and fintech industry events.
• According to the SemRush report, the forecasted AI annual growth rate between 2020 and 2027 is 33.2%.
• In combination, the benefits of AI and RPA create a prominent competitive advantage, which will inevitably result in the growth and prosperity of your enterprise.

Banks need to improve the quality of their customer service without sacrificing time to redundant user queries. Subsequently, they now understand the importance of automation and 24/7 services that are not only convenient to them, but to their customers. This means seamlessly providing scalable 24/7 customer support on multiple channels and languages. For years, customers have been demanding more from their financial institutions. Covid-19, and the consequences that came from the pandemic only accelerated these customer demands. Consumers expect immediacy, personalized, and flawless interactions with their favorite brands and they expect the same from their banks.

So you can rest easy knowing that your customer data is always secure with Teloz. The program provides end-to-end encryption, guaranteeing that only individuals with the proper authorization can access client data. Call center finance safety measure is essential for preserving the privacy of banking data. In addition,  Our Contact Center Software’s encryption technology is updated frequently to stay ahead of new threats. Apart from account balance, users can also ask regarding other details of the accounts, like recurring payments and expenses, card reward points, and money transfer limits. One can also recover their account details and make changes such as updating their current address or phone number.

The study adopted mixed methods where qualitative and quantitative data was collected using interview schedules and questionnaires respectively. Quantitative data was analyzed descriptively and results were presented using tables. The target population included experts in the field of AI in two telecommunication firms in Kenya.