Imagine a banking app that knows your habits, provides you with personalized financial recommendations, and keeps you on track with your financial goals. It's not a fad but conversational AI. This technology is the opportunity to build superhuman customer service, which, however, doesn't require human interference in most cases. Since consumer needs and problems become even more complex and service expectations are higher than ever, there is a demand for intelligent customer experience automation that becomes possible with conversational AI. It is a constantly learning technology and the ground for next-gen banking.

Understanding conversational AI

Conversational AI is a set of technologies that use Natural Language Processing (NLP) and Machine Learning (ML) to process huge volumes of data to help imitate human interactions, recognizing speech and text inputs, and interpreting meanings in various contexts. The most outstanding examples of conversational AI out there are voice assistants Alexa, Siri, and Google Assistant.  

Machine learning is a field of artificial intelligence based on data sets, algorithms, and features that allow technology to constantly learn and better recognize patterns with experience. Natural language processing is a method of analyzing language using machine learning in conversational AI.

In conversational AI, NLP processes flow into a constant feedback loop with machine learning processes, improving AI algorithms continuously. This technology is built on principle components that allow it to understand a message and generate a human-like response. 

Opportunities of conversational AI in finance

Conversational AI opens up tremendous opportunities for personalization and providing better support to customers. From a banking perspective, it means that your financial app can automatically answer any question much in the same way as a live agent would, but even more rapidly and concisely. What's the most fascinating, it can also be more emphatic.

In all businesses, customer support departments usually work under the heightened pressure of doing more with less. In stressful conditions, providing detailed and empathic responses might be more difficult. Conversational AI solves this problem, leaving only the most complicated questions to be answered by a human agent and providing extra time for more personalized responses. However, the potential of conversational AI doesn't stop here. 

Sentiment analysis

Sentiment analysis is one of those appealing opportunities offered by conversational AI. This kind of exploration provides access to information about the feelings and emotions of users, which is far beyond the simple semantics of words. Sentiment analysis works by assessing the positive, neutral, and negative feelings within user conversations. This data is extremely valuable since it enables chatbots to make conversations with users more natural and empathic. 

Intent interpretation

The intent analysis is way deeper than sentiment analysis, as it captures people's desires, wishes, and attitudes from user-generated texts. It provides a more profound contextual insight and allows understanding real user intentions behind the text. The intent analysis contributes to a better understanding of the text by a machine and generating a more relevant response.

Hyper-personalization

The more experience the technology acquires, the more natural and personalized a response generation process becomes. Combining NLP and machine learning and applying sentiment and intent analysis, conversational AI comprises a superpower that makes a chatbot communicate in almost a human way. In the form of chatbots, voice bots, and intelligent self-help systems, it brings the personalization of customer experience to the next level. With access to the organization's CRM and other databases, conversational AI can instantly get more insight into likely user behavior than a live agent can. 

Customer experience challenges that AI solves

Assisting users

Conversational AI allows building 24/7 customer support and self-service. It processes consumer queries and tries to provide nearly the same answers as the human agent would. Usually, if it cannot, there is an option to contact a live customer support agent. It leads to increased customer satisfaction with service and employee's satisfaction with their job, as the routine pressure is eliminated. 

Assisting live agents

AI can become a super-powerful friend for live agents and their most helpful tool for information search. Interacting with apps via conversational UIs saves a lot of time for agents. It helps them find the answers to customer queries faster and fill a knowledge gap by providing context-sensitive search.

Mining deep insight

AI can process incredible volumes of customer data, including information about past transactions, purchase history, transcripts of voice conversations and chat sessions, etc. Most of this information is stored as unstructured data. Only AI is capable of cross-referencing these pieces of knowledge, finding relations between them, and extracting valuable insight into likely customer attitudes, which can be later leveraged to provide personalized recommendations of offers, deals, purchases, and even investments.  

Building the next-gen banking experience

At Hennii, we dared to rethink current financial experiences and to fill the usability gaps left by major banks and financial companies. Driven by the desire to make financial services more accessible and inclusive, we created the next-gen banking experience powered by conversational AI. We believe that a complicated financial vocabulary which is often seen from traditional banks today can be replaced by a natural conversation with your personal AI assistant that will help you manage your finances more effectively.

“We want to provide cognitive tools to make finance accessible and make financial jargon understandable, which in my opinion, is not very complex but still intimidating many consumers. I think it's time to change this language, and it's time to come up with creative ways of really bringing equality into finance. It was the goal behind building Hennii. It's what has got us to this point. Now, I'm excited to say that we have kicked off the development process and have prototypes working.” - Tauseef Bashir, CEO and Founder of Hennii


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