Four Prospects for AI Chatbots in Banking
Chatbots offer a wide range of applications for the finance industry. Equipped with Artificial Intelligence, bank employees can efficiently automate customer service with automated answers and processes.
The German Federal Government has identified the relevance of Artificial Intelligence (AI) as well, and further promoted it with the publication of an “AI Strategy” in July 2018. The Government’s goal is to further expand the technology sector by investing in research and development and to lead Germany to the top of the world in this field.
AI in banking
Artificial Intelligence can be used in many different ways in the banking sector. AI can improve efficiency in customer service and thus save both customers and internal support agents time and resources. It can evaluate customer data in regard to the risk profile and thus contribute significantly to the success of risk management. In addition, Chatbots and language assistants are becoming more and more important. Customers can use chats or voice to ask bots for their account balance, incoming bank transfers, or to find out about new products and services.
Increased efficiency in customer service through Artificial Intelligence
Customer service is particularly suitable for AI applications in the banking sector. The challenge for banks has grown due to a constantly increasing number of support tickets on digital channels and increased customer expectations (e.g. new communication channels, 24/7 customer support, self-service). In this context, AI offers the ideal medium to solve inquiries in a scalable and efficient way, while at the same time increasing customer satisfaction.
In the first stage without IT system integrations, AI can answer general questions on existing products and services or on general questions such as FAQs, for example. In the second stage, individual questions, e.g. on standing orders, existing contracts or credit status, can also be answered using interfaces.
Advantages of a hybrid solution
The fear that an AI system will send wrong answers to the customer is unfounded with a hybrid solution. With the so-called “supervised learning” the chatbot learns directly from the customer support employee and there is no danger that the learning process becomes independent and wrong answers are trained. With a hybrid solution, the chatbot learns whenever an answer suggested by the AI is confirmed by the agent. In return, individual answers can be learned if they are no longer relevant.
The AI recognises incoming text-based customer requests, e.g. on websites via live chats, and suggests a response option based on what has been learned and the customer-specific data. After a pilot phase in which the AI system is supported by the call center agents in selecting the correct answers, the AI system then responds automatically according to the desired degree of automation, without a call center agent being further involved. This means that customer service can be significantly relieved at the outset, especially for simpler enquiries, but also for more complex individual enquiries.
Status quo of AI applications
Financial service providers have now recognised the added value of AI-based applications. However, the pace at which they approach the introduction of AI solutions varies. Direct banks are typically much faster and more flexible in their implementation, but major banks also see the potential in this area and are already starting to integrate AI. It is therefore only a matter of time before such systems will also be established at traditional banks.