Introducing AI Chatbots in FinTech Industry

Introducing AI Chatbots in FinTech Industry

Expansion of Chatbots

Chatbots became quite a hype during the last 3-4 years, especially in the fintech world, and the ongoing “rise of chatbots” is the result of rapidly growing data science and cloud computing with the vast computing power available. On the other side, one of the biggest drivers of chatbot development are the new generations of consumers – millennials and especially “generation Z”, which grew up in the era of computers and smartphones, and prefer chatting and self-service approach over voice calls and e-mails.

Chatbots emerged from the need to automate the massive volume of repetitive tasks, in particular in customer support of the biggest enterprises, dealing daily with thousands of support requests. Adoption of Artificial Intelligence techniques (in particular NLU, Natural Language Understanding) helped to classify huge amounts of data and identify conversational workflows that could be successfully automated by chatbots, which replaced earlier rule-based chat solutions.

Further development of chatbots led to a vast expansion of usage scenarios and business domains, and now the latest generation of chatbots is capable of servicing complicated requests with the context or intent changes during the conversation.

Enterprise AI Chatbot Solutions in FinTech

When compared to other industries, it is generally recognized that financial institutions have access to all the necessary resources to respond to fintech disruption. Consequently, the banking sector is said to be one of the biggest beneficiaries of chatbot implementation. The chatbot usage scenario is not limited to the first line of customer support, now chatbots assist customers in a variety of cases – account, asset, and payment management or even perform as personal financial advisors. Implementation of in-house chatbots for banks and other financial institutions with a vast network of branches reveals additional benefits, such as an easily accessible internal knowledge base, personnel education/training program, and assistance for HR departments.

Many big players in the banking sector developed their own proprietary chatbot solutions (Bank of America, Wells Fargo, HSBC), focusing precisely on the specifics of their businesses and infrastructure. However, such fintech solutions are too specific to be adopted market-wide, so there is a little chance that these solutions can turn into publicly available products.

The other path was chosen by software development companies – they initially focused on building fintech products that could fit business models of multiple banks. In some cases, chatbot serves as a complementary solution to their core software infrastructure (ERP/CRM), but many companies (that mostly emerged during the last 3-4 years) are just focused on building chatbots only. Their cooperation models range from the Service model – “we build a custom chatbot for you” – to the Product model.

The alternative fintech strategy that is worth mentioning is the development of chatbot SaaS platforms, which offer the use of their API and middleware with incorporated AI layer.

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Role of Language in Chatbot Development

Selecting Language for Chatbot Platform

From a linguistical point of view, most of the chatbot platforms focus first on the support of languages with the greatest population and market coverage – these are English and Spanish languages for the Americas, UK, and Australia, and then on other languages depending on regional specifics of the vendor.

Specifics of German Chatbots

There are not so many fintech chatbot platforms focusing at the moment on the German language and DACH market. One of the challenges here is the semantic complexity of the German language as well as many regional differences between states in Germany, Austria, and Switzerland. Although the DACH market is generally big enough, it is far less than markets where English and Spanish languages prevail. Therefore, not so many chatbot-oriented fintech companies focus on this market.

Summary: How to Implement AI Chatbots in FinTech

The most widespread chatbot applications in fintech are:

  • customer support automation (CSA);
  • chatbot-based personal financial advisors;
  • FAQ automation: offering access to the internal company knowledge base through chatbots;
  • employee onboarding & training chatbots;
  • HR bots for employee evaluation procedures, gathering feedback, and collecting intra-company survey responses.

There are two main approaches to chatbot development in banking and finance:

  1. developing own proprietary chatbot solution;
  2. customizing a platform-based chatbot.

Extending the list of languages supported by the chatbot can bring unforeseen challenges to the task at hand. The next points should be considered while building multilingual chatbots:

  • English and Spanish languages are the most popular among chatbots both because of their linguistic simplicity and wide usage.
  • After English and Spanish, fintech companies mostly focus on the local market and select the language based on the regional specifics.
  • French and German chatbots are an untapped market for fintech institutions. However, while being good investment opportunities, they also pose serious challenges for AI Companies to develop such chatbots due to their increased linguistic complexity. Developing French and German chatbots requires unconventional approaches to intent recognition and state-of-the-art methods of natural language processing (NLP).

Abto Software is a trusted provider of AI-driven chatbot development services – our experts will help you build and carry out the most efficient chatbot implementation strategy for your business. Fill out the form below to schedule a consultation or receive a demo of our chatbot solution.

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