Welcome to our in-depth guide to chatbots in the banking industry — 2023 and beyond
The banking industry is in the midst of a digital revolution, and it's important for both small and large financial institutions to undertake a successful digital transformation. A recent McKinsey report highlights that banks who achieve their digital transformation enjoy “better business outcomes, including higher balances for current account savings accounts, lower cost-to-income ratios, increased customer acquisition and retention rates, and faster time to market.”
Thanks to the recent excitement around ChatGPT, chatbots have risen to the top of the digital priority list for financial institutions. For good reason, as today’s bank chatbots are increasingly able to enhance the customer experience and improve employee engagement efficiency — increasingly important needs as financial institutions face ongoing hiring challenges and staff shortages.
Here’s what you need to know about the evolving role of chatbots in the banking industry in 2023 and beyond.
How chatbots are changing the banking industry
Today’s conversational chatbots are a few steps beyond the more limited first-generation models. Put aside any conception of chatbots being too impersonal, cold and limited in scope — today’s chatbots in banking have several specific functions, unlimited scalability, are capable of more natural sounding conversations and can adapt to thousands of topics.
These advanced chatbots, also known as virtual agents, offer numerous benefits to both customers and financial institutions. By leveraging natural language processing (NLP) and machine learning artificial intelligence (AI), banking chatbots can enhance the user experience by promptly answering customer queries, streamlining outdated processes, delivering updates and notifications, developing comprehensive customer profiles and facilitating more interactive and personalized conversations between customers and banks.
Because chatbots excel at simplifying time-consuming banking tasks that traditionally required extensive paperwork and hours of processing, they can save both customers and banks valuable time and effort. They can assist customers in completing tasks, such as opening bank accounts, retrieving balance information or accessing specific account details, as well as helping bank employees be more efficient and productive, leading to several important benefits.
Benefits of chatbots in banking industry
While it’s easy to think of chatbots as only an external-facing resource, they can bring important benefits to internal operations as well. When employed across all departments, financial institutions can experience:
- Enhanced customer service: Banking chatbots help to reduce long waiting times by offering 24/7 customer support, and by providing more accurate responses to customer questions, making it more likely customer issues are resolved within that first interaction. Chatbots also offer a helpful and instant means of handling sensitive matters where a customer may not want to talk to a human agent, like when making late payments. By continuing to improve customer service, banking chatbots help to build loyalty and secure customers’ business for the long term.
- More personalized customer service: Rather than just pulling from a list of predetermined answers, today’s chatbots can instantly retrieve information about a client’s account, including their history, purchases and any notes. This allows the chatbot to provide more personalized interactions through directed offers or targeted assistance with specific issues, like during client onboarding. Conversational AI-powered chatbots provide a more natural interface to take and answer customer questions as they arise, and can even pick conversations back up immediately if the customer has to step away from the interaction.
- Increased value for employees: Banking chatbots can provide major internal benefits as well, as bank employees can use virtual agents as tools to assist with higher-value tasks. For example, if the chatbot is integrated into the bank’s call center solution through its API, it can act as an efficient lead generator. Through their personalized interactions with customers, the banking chatbot can gather and save important customer details. Should a customer express to a chatbot that they’d like to buy insurance, the chatbot would send a notification to an appropriate sales agent as well as the information necessary to contact the customer.
- Improved cost effectiveness: Because Al and machine learning-based chatbots are self-updating, they’re capable of continuously collecting more data to update their information and improve the quality of service. This makes it extremely cost effective to improve the chatbot’s efficiency and capabilities over time, requiring less direct oversight from programmers, and instead only guidance from AI trainers.
- More overall efficiency: As they operate, chatbotscontinually collect, sort, update and store customer data. This makes every interaction a valuable source of insights to develop more personalized interactions, directed product recommendations and relevant financial advice. Employees can also interact directly with chatbots for their own tasks, instantly retrieving information as needed, asking for and receiving recommendations and recording conversations.
Chatbot applications in the banking industry
As for how banks can realize these benefits, here are common applications for banking chatbots.
- Personal banking assistants that aid customers in making payments, setting up or canceling transactions, tracking monetary transfers and opening or closing accounts. They can also provide customers with information about their account balance, recurring payments, expenses, card reward points and money transfer limits.
- Customer advisors that answer customers’ questions about their accounts but also offer information on banking products and services. They can suggest self-service options, send alerts about spending limits, offer reminders about payment deadlines and share financial education and tips for good financial habits.
- On-time notifications and reminders to alert customers and employees alike. Customers can receive notifications about important banking activities such as bill payment deadlines, loan offers and other account-related updates. Employees can receive alerts about important tasks or the need to follow up with co-workers or clients.
- Real-time location tracking by leveraging mobile GPS to track a user's location and provide real-time, location-specific answers and services. Clients can receive specific directions to local branches and services and receive notifications and alerts specific to their location, ensuring personalized and relevant information.
- Priority resolution of urgent but non-complex issues by assisting customers with tasks like unlocking or locking cards, resetting credentials, checking bank statements and completing fund transfers promptly.
- Task assistance for banking personnel to save time by handling repetitive queries and menial tasks. Chatbots can allow banking personnel to focus on more complex issues or receive on-the-spot training to acquire new knowledge and capabilities. Customer service agents can respond quickly with more accurate information, while financial advisors can gain immediate access to more precise and real-time insights.
Chatbots in banking trends
As the technology powering chatbots continues to evolve, they’ll go beyond the simple function of answering questions and continue to become fully featured virtual agents. These are the current trends driving the evolution of banking chatbots:
- Wide-spread use of LLMs to inform chatbots. The incorporation of large language models (LLMs) (like the one’s powering OpenAI’s ChatGPT and Google’s Bard) already helps chatbots to craft more “human-like” conversational interactions. A lot of the challenges in utilizing LLM models can be circumvented by utilizing a resource with a more limited and specific scope — for example, a bank’s website. This develops a banking chatbot that is able to speak to that bank's specific product offerings and procedures. Leveraging the fine-tuning capabilities of specialized intent models can create more powerful and accurate natural language understanding (NLU) engines that allow chatbots to understand even complex customer queries and easily provide the correct answers.
- Rising use of voice bots. Continued advances in voice recognition and intelligent virtual assistants (IVAs) allow virtual agents to respond to voice commands in natural language, allowing for more intuitive customer service experiences and direct interactions with employees. As conversational chatbots and voice bots become more widely used, they’ll handle even more customer interactions, providing updates on their account balance or handling tasks like a PIN reset. They’ll also be a common tool for internal applications, such as transcribing conversations for future reference, and automatically logging information into the bank’s CRM system.
- Automation of even more tasks. Banking chatbots will be even more capable of handling customer self-service financial transactions and functions. Advanced chatbots can use techniques like optical character recognition (OCR) to actually read documents immediately after they’re uploaded and use entity extraction to extract data to check for inaccuracies, inconsistencies or missing fields. By providing chatbots more control over documentation — ranging from customer applications to internal reports — they can upload the information into the bank’s CRM systems, cross-check that the information on the documents is correct and even offer direct feedback to ensure that all provided information is accurate.
- Greater ease of use. Modern chatbots don’t need extensive or exhaustive programming skills to manage and update. No-code platforms will allow any suitably trained employee of a financial institution the capability to build on top of the original programming framework. There’s no need to wait on a developer to make changes or go back and forth with vendors every time a minor change is needed — AI trainers can utilize powerful and simple API self-service options to customize integrations on their own. Modern chatbots of tomorrow are ready-to-use, out-of-the-box solutions that can be quickly adapted to changing internal processes.
As chatbots continue to become more sophisticated and widely used, they’ll become even more accepted as a resource, platform and even co-worker. It’s possible in the future that advanced virtual agents could even operate as banking advisors, providing in-depth financial advice for clients. The more ways chatbots can assist customers with tasks, the more it frees up bank employees with the knowledge and skills to handle more complex and sensitive matters.
See our free on-demand webinar for additional real-life examples of how chatbot integrations are changing banking:
Examples of successfully implemented chatbots
The best feature of today’s chatbots is that they can handle an increasingly large amount of interactions, be active across all of a financial institution’s locations and be up and running within a matter of days, not months. Here are some examples of how boost.ai has helped banks and credit unions realize their own AI chatbot solutions.
The right application of Natural Language Understanding (NLU) algorithms to power chatbots can allow them to be deployed as a single solution across multiple use cases, and the possibility to meet the scalability requirements of even large banks like Nordea.
Nordea is the leading Nordic bank with operations in Sweden, Denmark, Norway and Finland and currently has 12 virtual agents operating in each market’s local language (as well as English in some countries). Deploying so many virtual agents within Nordea’s system actually increases overall accuracy and efficiency. The experience garnered from developing the Norwegian market’s virtual agent was a valuable resource to the development teams in the other countries. For example, the AI trainer team working on the virtual agent for the Finnish market has more than tripled the number of topics that the virtual agent can answer questions on, allowing it to truly scale alongside the growing demands of customers.
When incorporated into a bank’s system, chatbots can scale to handle all of a bank’s operations.
Norway’s largest bank, DNB, has deployed its virtual agent across eight different business units and has 1,200+ daily active users each asking on average seven questions a day. As a result of this activity, the virtual agent can answer questions on more than 3,400 topics, with each of these then further customized towards seven different areas within the bank, split between Corporate Banking and the Private Market.
The effectiveness of the virtual agent has led to its expansion across various departments within the bank, with plans to introduce it to more business units in the coming times. Its integration into multiple systems enables the virtual agent to automatically monitor the status of the bank's systems, alerting human agents to any problems or outages to enhance customer support. On average, the virtual agent handles around 80,000 conversations each month and responded to over 2 million queries in the year 2022 alone.
Michigan State University Federal Credit Union, the largest university-based credit union in the world with over 300,000 members, managed to launch a virtual agent in just 10 days, resulting in the automation of over 2,000 internal interactions.
MSUFCU’s goal was to assist its employees with automating backend processes, while also improving front-end customer service interactions to assist member support staff. By using boost.ai's no-code conversational AI platform, MSUFCU was able to seamlessly integrate its virtual agent with its own existing knowledge base system, greatly speeding up the integration and training process.
The near future will continue to see an increase in the scope of chatbots, all with better support for multi-level functionality, scenarios and contextual answers. Ernst & Young predicts that most wealth and private banks will provide a “synergetic blend of people and technology” by incorporating “sophisticated digital assistants alongside tech-enabled remote advisors.” As chatbots become more integrated throughout a bank’s department and services, conversational AI chatbots will work in partnership with human agents, truly living up to the term “virtual agent.”