Chatbots in banking: the full guide to bot creation

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Today, clients expect to solve many of their problems on the go. Thus, they rely on services and technologies to accommodate their fast way of life. Financial services are one of such areas. These service providers wouldn’t be able to cater to their client’s needs without automation and heavy reliance on technological advances. The technology of natural language processing or NLP for finance was the way to go. 

The new banking chatbots use NLP which is a combination of artificial intelligence and machine learning. Such technology is still rather new. Yet, it is progressing rather rapidly, due to its growing demand and numerous opportunities for the financial world. These new chatbots for banks and financial services can learn human language and process it to form automatic responses and mimic human conversations. 

Not only that, but the NLP can also perform repetitive tasks, analyze large quantities of data, and offer objective insights. In a nutshell, NLP chatbot services can serve as a reliable middleman between humans and computers. 

Just like that, AI in banking is expected to grow 1200% by 2025, with the market size reaching $315 billion. At this given moment, that is less than three years! Such a prediction shows the undeniable tendency of automation in financial systems and banks. Here is everything you need to know about how and why.

Types of Bots in the Financial Services Sector

Currently, the banking system has two options for chatbots. One is a traditional rule-based bot. Another is an AI-based bot as a more modern and advanced alternative. 

Rule-based bots

A scripted or rule-based banking bot is a simple communication tool used in financial services. It’s a common chat option that stands on scripted answers and queries, using specific keywords and commands. Thus, it can respond to a client’s requests only when recognizing at least one of the words in their queries. A message with no trigger word will not receive a requested solution from a bot, affecting the overall client experience.

AI-based bots

Artificial intelligence in banks is nothing new. Most banks already use this technology to analyze big data, predict trends or outcomes, detect any security breaches, and make recommendations to clients based on their behavioral patterns. AI-based bots can help with those functions and more.

These bots use ML and AI technology to analyze and understand given queries. Hence, they can respond autonomously and more comprehensively. They can use client history and previous interactions to improve their answers, prioritize requests, and hold complex conversations. 

The Chatbot’s Role in Banking Growth

Chatbots are used in finance for customer convenience, simplicity of service provision, and lower costs. They can help meet the growing client’s demands for fast and efficient problem-solving via applications. These are five fintech chatbot advantages worth mentioning. 

Twenty-four-seven customer support

A finance chatbot is a perfect way to elevate the customer experience. After all, client work is the primary focus of such chatbots. This tool can provide round-the-clock communication, which is a rather new concept in banking. So, people can solve any arising issues at any time day or night, after working hours, on the weekends, or on holidays.

Selling assistance 

A financial bot can also help banks with selling strategies. Thus, it can analyze customers, pitch their services and products, offer subscriptions, and identify what offers they may want to purchase. Hence, in this case, a chatbot can also benefit the sales team by giving them leads and starting discussions on products and sales. 

Proactive advice

A chatbot can do more for people than they expect from it. Such a tool can also help users manage their finances. For instance, it can give users budgeting advice considering their financial habits and behavioral patterns. It can also offer investment tips, and send alerts or reminders when exceeding their spending limits.

Fraud prevention

Security in banking is the number one priority. A financial bot can spot any abnormal behavior or fraud online. It can keep track of all financial operations and analyze common behavioral patterns to notice any other activity in the system. A bot can also red flag, pause and send notifications regarding any atypical transactions for further investigation by human employees. 

Back-office optimization

Bots can improve banks’ productivity and efficiency by optimizing their back office work and enhancing their front office communication. Such a connected work operation will improve customer experience and lead to a more flexible and faster workflow. 

How to Build a Banking Bot 

Building a bot for a mobile banking app will depend on many factors, such as its type, the nature of your company, its purposes, and so on. Yet, regardless of the project ideas you have for a chatbot, any bot creation will follow these processes. 

Purposes and channels

First, one needs to identify the purpose of the bot and its further role within the company. Thus, it can be as smart, all-encompassing, and integrated as the job requires. Overall, a banking bot can be a part of your selling strategy, client communication, behavioral analysis, and more. 

Banking app UI design

An intuitive and straightforward banking app design is the bare minimum expected by the clients. A chatbot will be their go-to solution any time they face a sudden banking issue, and they expect their online support to be fast go smoothly. UI design and the app’s interface will play a major role in such a type of communication. For example, to facilitate easy connection, such chats should resemble popular messengers with human-to-human communication.  

Data security

Banking cyber security has been a rising concern for bankers and their clients. So, the reliability of bank bots should be based on solid authentication processes, trustworthy providers, and overall security architecture. 

NLP integration

A natural language processing finance bot is essential for enhancing customer experience. Hence, if the bot’s prior role lies in client communication, NLP is the only right approach to bot development. It will ensure flawless messaging, easy and fast communication, and fewer to no errors in reading clients’ requests and generating responses. Meanwhile, it will also collect clients’ data and keep growing with each interaction. 

Development approach

One can choose either a SaaS solution or a custom solution. The latter may be a more costly option. Yet it will fully meet your needs, and be flexible and compliant with changes. The former is a simpler and more budget-friendly solution. Yet it will have certain drawbacks, like complete dependence on the service you build your bot. 

Future of chatbots in banking: forecasts and insights

The bank’s need for chatbots is only rising each year. Currently, AI-based bots are the new norm in finance, as they can offer a wider range of services while also filling any communication gaps banks can’t close otherwise. Besides, as the world leans toward digitalization, clients expect easy solutions in managing their tasks, including banking, via smartphones and applications. 

Such a tendency combined with the constant progress in AI development indicates a bright future for chatbots, especially AI-based bots, in banking. In fact, over 75% of banks are currently investing in AI strategies. Hence, chatbots are only the beginning of AI in banks.


AI in banking and finance can go a long way. NLP technology is only one of many ways to apply AI in the financial world. Yet, even such a simple addition to the communication patterns can significantly improve client satisfaction as well as inside operations and workflow. Overall, chatbots are the new norm in banking that can increase the efficiency and quality of issue responses via chats while reducing the need for human interventions.   

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