Exploring Chabots in Nepalese Banks
Laxmi Didi, Sani, Nabina, and more are working for Nepali banks in 2025. You may think these are employees, right? Although they are not technically employees, they do function in a similar capacity. Actually, these are chatbots. Many commercial banks in Nepal have already introduced these digital assistants. This piece will let you explore what they are, how they work, and how powerful they can be.
Digitalization of Nepali Bank
Years ago, we left the Dhadda system behind, but in 2025, digitization is making significant strides. You can now open a savings account or even an FD online without filling out a lengthy 10-page form. Want to apply for an IPO? You can create a demat account from the comfort of your home. You can do video KYC, apply for loans, and get credit or debit cards on your phone. Nepal’s banking sector is stepping into the digital era.
Back then, banking wasn’t that easy. Most tasks were manual, relying heavily on pen and paper. Looking back, Kumari Bank (2002) and Laxmi Bank (2004) paved the way for digitization in Nepal by introducing Internet and SMS banking. Since then, the sector has evolved significantly. Alongside services like mobile banking, internet banking, and digital banking cards, chatbots have now been introduced to further advance the digitization of Nepali banking.
What are Chatbots
Bots, specifically chatbots, are computer programs that simulate human conversation. They interact with users via text or voice, answering questions, providing information, and completing tasks automatically. On banking websites, you’ll usually find them in the bottom-right corner, hidden under a small icon.
Let’s dive a little deeper. What are they made of? First is the UI, which resembles a WhatsApp or Messenger interface; it’s essentially a chat window. The working engine behind chatbots is AI, specifically machine learning. Machine learning is the core technology, allowing chatbots to learn from the data you provide, make predictions, and, most importantly, improve their decisions and accuracy over time on their own.
Chatbot Types Explained
Additionally, machine learning can be mainly classified into two types:
- Rule-Based Chatbot
- AI-Based Chatbot
Rule-based chatbots are scripted and fully programmed. They often use buttons, menus, and keywords to guide the conversation. Keywords form the foundation of these chatbots. For example, if you ask about the process for opening a savings account, the chatbot searches for the closest pre-programmed response containing the keywords like “savings account” and “account opening” and provides that immediate answer.
AI-powered chatbots, on the other hand, are far more sophisticated. Natural Language Processing (NLP) is the technology that makes them smarter than rule-based bots. NLP analyzes conversations in depth, taking into account factors such as intent, tone, conversation logic, and context, which makes interactions feel more human-like.
This sort of chatbot works by understanding the intent (what the user wants) and entities (important details, like the amount or recipient). For example, if a user says, “Send 5000 to Hari,” the intent is a money transfer, and the entities are 5000 and Hari. Chatbots also use tone to match the brand’s personality, maintain context to follow the conversation, and support a smooth dialogue flow with clear logic. They provide accurate and relevant responses, focus on a good user experience, and include fallbacks for situations they don’t understand, such as replying, “I didn’t get that; can you rephrase?”
Chatbots also come in sub-variations, including voice-based chatbots that interact through speech, text-based chatbots that communicate via text, and hybrid chatbots that combine both.
Chatbots in Nepali Banks
Only eight banks currently have chatbots, and seven of them use rule-based bots. As of now, only Sid, from Siddhartha Bank, is an AI-powered chatbot. NBL Mitra serves Nepal Bank Limited as a menu-based chatbot, providing information about banking products, ATMs, and branches, and also guiding users to the relevant contact details.
Floatboat has a rule-based chatbot built for NIC Asia, and its name is Satthi. It works on keywords and additionally provides audio input. Viva, the assistant of Global IME Bank, is also a rule-based chatbot, offering options such as KYC updates, home loans, credit cards, account statements, and more. It includes a language switch option, supporting both Nepali and English, which other chatbots lack. Kumari Bank also has a chatbot that appears to support both text and voice interactions.
Siddhartha Bank has a hybrid chatbot, combining both rule-based and AI-powered features, which sets it apart among Nepali banks. While it’s not very powerful, it is still AI-enabled. Similarly, Laxmi Didi serves as a chatbot assistant for Laxmi Bank, and Sunrise Bank Limited uses a simple rule-based chatbot. Sani, for Sanima Bank, functions similarly to Sunrise as another basic rule-based chatbot. A special mention goes to Palmmind, a Nepal-based IT company that appears in most of the chatbots’ interfaces.
Benefits
Chatbots offer significant benefits for both banks and customers. Despite the lack of official studies in Nepal, browsing bank websites and interacting with these bots demonstrates their effective handling of minor queries. This means customers no longer need to call customer care unnecessarily.
Customers no longer have to wait or repeatedly try calling customer care if the line is busy. Chatbots now assist by handling the majority of minor inquiries. Cost reduction is another benefit for the banking sector. While implementing chatbots requires a significant initial investment, over time they help lower costs by reducing the need for staff.
NIC Satthi displays products as a menu, including savings and deposit products, digital loans, and card services. By showcasing these offerings, anyone interacting with the chatbot can click on an option, leading them along a conversion path. In this way, the chatbot also functions as a lead magnet.
Branding is another tool that banks use creatively. The unique names of Nepali banks’ chatbots are attention-grabbing, and blending the chatbot interface colors with brand colors is a simple yet effective way to influence user perception. Banks can even reinforce their branding through engagement tools, such as EMI calculators or currency conversion features, as menu options within chatbots, just as NICA has done.
Additionally, 24/7 support, quick responses, and multilingual capabilities provide customers with a better experience. On the bank’s side, chatbots help collect valuable customer data, which is always crucial for improving services.
Future of Chatbots in Nepal
The potential of chatbots in the Nepalese banking sector is vast and largely unexplored. Chatbots could have a major influence on the future of digital banking in Nepal. To better understand this potential and how far it can expand, let’s take a look at a few advanced chatbots that banks are using in the West.
Erica, of Bank of America, is exclusively available through the mobile banking app and features continuous learning as part of its AI capabilities. Tasks such as debit card locking can be completed directly through the chat. Erica, functioning as a contextual chatbot, scrutinizes previous transactions and recommends tailored plans for its users. It also offers a wide range of services across saving, spending, and planning, effectively acting as a personal financial agent.
Similarly, Commonwealth Bank’s Ceba asserts its ability to perform 200 banking tasks in 60,000 different ways.
Eva, from the neighboring bank HDFC, also brought impressive features, including handling millions of interactions and facilitating product purchases such as credit cards and loans. Eva functions like a live agent while also resembling a chatbot, allowing users to interact with it through chat.
Analyzing chatbots and digital assistants across the world, it’s clear that Nepali commercial banks are still in the early stages. The future will likely focus on features such as natural language understanding, transactional capabilities, service requests like checkbook and card activation, and personalization based on spending patterns, user preferences, transaction history, and more. Therefore, we still have a significant distance to cover.
Lastly
Chatbots are already installed in many banks, but more than 50% of Nepali commercial banks still don’t have them. Among those that do, most use basic versions, which still function effectively and have led to future advancements. Rule-based chatbots currently manage frequently asked questions and basic product details, but much more sophisticated features are likely to be added in the future. Despite the gradual progress of Nepali banking, its digital presence is enhancing everyone’s banking experience.
Article by: Mr. Binod Raut | Content Editor: Salina Shree
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