Banking Chatbots Examples and Best Practices for Implementation

March 15, 2024

7 min read

Kate Kopyl

Banking Chatbots Examples and Best Practices for Implementation


Chatbots have become core tools for customer and employee interactions in the banking industry. As convenience and personalisation take centre stage, banks are constantly exploring innovative ways to surpass customer expectations. But in order to deliver exceptional experiences through chatbots, banks have to carefully consider their use and design. 


In this article, we will explore some of the best banking chatbot examples from around the world and delve into the factors that contribute to their success. 

What is a banking chatbot?

A banking chatbot is an AI-powered interface used to interact with customers and provide assistance. Initially designed for FAQs, it now helps customers find information, shop, complete transactions, and troubleshoot issues.

Do banks use chatbots?

Banks use AI-powered chatbots to help customers and improve operations. The chatbots answer questions, provide support, and assist with financial product applications. Other uses of AI agents include lead generation and re-engagement.

How many banks have chatbots?

48% of surveyed banking companies plan to use Generative AI for chatbots. Banks’ GenAI spending will grow from $5.6 billion in 2024 to $85.7 billion in 2030, a 1,430% increase.

Best banking chatbot examples  

Here is a roundup of 5 well-known banking chatbots, setting new standards for the industry. 


1. Ally Assist from Ally Bank 

One of the first banks in the world to introduce a chatbot, Ally Bank launched Ally Assist in 2015 with the goal of providing personalised customer service. It was also one of the first to offer a built-in voice interaction in its mobile app.


Best banking chatbots examples   Ally Assist from Ally Bank 


Top Ally’s advantages: 

  • Connection to Amazon Alexa: Ally Assist is accessible through Amazon Alexa, allowing customers to complete essential functions such as checking their balance or making bank transfers via voice commands.
  • Identifying needs: Ally Assist anticipates customers’ needs and serves relevant solutions using automated intelligence and customer data profiles. Based on interactions and transactional behaviour, the system learns what information is likely to be needed to present context-aware topics and messages to customers. 
  • Improved accessibility and navigation: Convenient navigation allows customers to evaluate their banking accounts in a deeper, more insightful way to better manage their personal finances. Ally has five different mobile apps, one for each of its products – Ally Mobile, Ally Auto, Ally Card Controls, Ally Invest, and Ally Smart Auction – which is convenient for people who only use one or two products, for example, using solely savings accounts.


2. Erica from Bank of America 

Erica is Bank of America’s virtual financial assistant, powered by artificial intelligence (AI). It was launched in 2018 and has since helped nearly 32 million clients with their everyday financial needs. Erica is available 24/7, allowing customers to access banking services at any time and from anywhere. 


Best banking chatbots examples   Erica from Bank of America 


Top Erica’s advantages: 

  • Personalised assistance: Erica relies on AI algorithms to understand customer preferences and customize responses based on them. The virtual assistant can give personalized suggestions and recommendations, improving the whole banking experience. 
  • Improved security: Erica boasts advanced security features that actively protect customers from fraudulent activities. Through constant account monitoring and immediate notifications regarding suspicious transactions, Erica plays a crucial role in ensuring a safe banking environment providing customers peace of mind. 
  • Proactive insights: By monitoring recurring charges, Erica enables customers to cut recurring subscription charges that may have increased unexpectedly. It also notifies customers when they’ve received a merchant refund or have duplicate charges. 


3. Eno from Capital One 

Eno simplifies banking, providing a seamless and convenient account management experience. Its user-friendly interface allows easy access to balances, transactions, and account details. Eno is accessible through various platforms, such as the website, mobile app, and SMS. Powered by advanced natural language processing, Eno understands a wide range of queries, accommodating over 2,200 different ways customers may ask for their balance. 


Best banking chatbots examples  Eno from Capital One


Top Eno’s advantages:  

  • Spending monitoring: Eno helps customers track customer spending by monitoring their credit card account and sending them useful insights when it detects free trials, recurring charges, and more. 
  • Account management: Eno enables customers to manage various aspects of their Capital One accounts through simple conversational interactions. 
  • Continuous learning: Eno learns from customer interactions and adapts to evolving customer preferences, improving its responses and capabilities over time. That ensures a more personalised and effective conversational experience. 
  • Shopping assistance: Through Eno, merchants can create unique virtual card numbers directly through their browser extension, which simplifies access and makes using the site more convenient. 


4. NOMI from Royal Bank of Canada  

NOMI, — a play on the words “know me” — is a built-in intelligence feature available in the RBC Mobile app and RBC Online Banking. Leveraging artificial intelligence, it provides distinct types of customer engagement through alerts, reminders, and tailored insights based on your banking habits so you can make more informed financial decisions.  


Best banking chatbots examples NOMI from Royal Bank of Canada  


Top NOMI’s advantages: 

  • Finance insights: it analyses customer monthly spending, categorises it, providing a detailed picture of how money is spent and how it is set to spend in the future.
  • Assistance with savings: it learns customer transaction patterns, identifies additional funds that customers may not miss and sets them aside automatically for them based on those patterns. 
  • Budgeting: by calculating a personal budget based on customer spending habits, it sends updates and reminders, helping customers stay on track to meet their financial goals. 
  • Finance forecast: By learning from customer transactions and utilising predictive technology, NOMI helps them to better manage finances. It provides a rolling forecast of customer payments and deposits for the next seven days.


5. Cardi from BNP Paribas 

Cardi, a virtual agent for the international insurance provider, provides timely assistance to customers experiencing loss events and need urgent attention. This voice bot allows customers who experienced loss events to swiftly file and insurance claims. 


Best banking chatbots examples Cardi from BNP Paribas 


Top Cardi’s advantages: 

  • Branded avatar: Cardi takes on a distinct identity that aligns with the bank’s brand and philosophy, demonstrating politeness and friendliness like a real insurance specialist. 
  • Prompt claim processing: Cardi accepts incoming calls and guides customers through the claims process, offering support with policy management. 
  • Seamless customer interactions: The chatbot utilises natural language processing and artificial intelligence to engage in intuitive conversations with customers. It answers inquiries, provides information about insurance policies, delivering a smooth and effortless experience for customers. 


Chatbots best practices 

We’ve looked at some world-renowned examples of chatbots that banks are leveraging to provide a modern, frictionless experience for their customers. While these chatbots have unique purposes and designs, they also share common features that serve as best practices for any financial service business looking to implement chatbot systems effectively and ensure their success. Let’s explore these common features and best practices in detail. 


  • Branded avatar. Having a branded avatar also helps in building trust and credibility. Customers are more likely to feel comfortable interacting with a chatbot that reflects the bank’s brand and values. The familiar avatar serves as a visual cue that the chatbot is an official representative of the bank, enhancing the overall perception of professionalism and reliability. 
  • Chatbot competence. A competent banking chatbot is crucial for delivering exceptional customer service. It should have an extensive knowledge base, and the ability to understand context and efficiently resolve issues. Competent chatbots can escalate to human agents when necessary. 
  • Natural conversation. Conversational AI allows banks to create a conversational experience that closely mimics human interactions, making it easier and more pleasant for users to engage with the chatbot. Among the key factors that contribute to natural conversation are language understanding and generation, emotion recognition and error handling.  
  • Personalised customer experience. By tailoring interactions to individual customers, chatbots can deliver a more engaging and efficient banking experience. Chatbots can gather and analyse customer data to build comprehensive profile, including transaction history, preferences, and demographics. By leveraging this data, chatbots can offer personalised recommendations, product suggestions, and targeted assistance based on the customer’s unique needs and preferences. 
  • Continuous learning. By leveraging machine learning algorithms and analysing user interactions, chatbots can continually improve their performance, enhance their accuracy, and provide more relevant and personalised responses. Also, chatbots can learn from their mistakes and improve their error detection and correction capabilities. Continuous learning ensures that the chatbot remains dynamic, relevant, and effective in meeting the evolving demands of customers in the banking industry. 
  • Compliance and security. Because financial information is sensitive and regulated, banking chatbots should strictly follow data privacy regulations. Chatbot platforms should enable secure communication channels to protect data during transmission between the user and the chatbot. The chatbot solution provider must comply with the security standards in the financial sector such as through IBM Cloud validation



Banking Chatbots Examples and Best Practices for Implementation


When banks implement these best practices for chatbot development and deployment, they greatly increase their chances of achieving success. Following them helps banks build chatbots that deliver amazing customer service, improve efficiency, and boost customer happiness. 


How to integrate AI solutions into your financial organisation?  

For those seeking to unlock the transformative capabilities of chatbot technology within financial services, our team of AI experts is at your service. Whether you’re initiating a new project or expanding an existing one, we are here to assist.


The rapid advancement of NLP and AI technology has left many companies uncertain about where to begin their AI journey. In this era, where technological progress outpaces businesses’ adaptability, it’s a common dilemma. Nevertheless, this challenge should not dissuade organisations from exploring the potential of AI to add value.


To navigate these challenges, it is recommended to collaborate with experienced vendors. These vendors should provide state-of-the-art AI solutions and offer essential consultancy services for identifying and evaluating potential AI use cases.


Tovie AI offers its expertise in Conversational AI and Large Language Models (LLMs) to pinpoint potential use cases suitable for deployment in your financial organisation. With a wealth of experience, Tovie AI has successfully delivered AI-focused discoveries for large enterprises globally.


Our consulting services harness Generative AI expertise to recognise your business optimisation potential, converting your data into actionable insights for accelerated growth.


We provide enterprise Conversational AI, Machine Learning/Natural Language Processing (NLP) SaaS platforms, and cutting-edge large language model frameworks.


Tovie AI’s profound understanding of LLMs and its cutting-edge proprietary LLM framework position us as the ideal partner to guide your financial organisation through the seamless integration and optimisation of AI solutions. We will ensure that you harness the full potential of Conversational AI and large language models for sustained growth and enhanced operational efficiency.

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