The key decision points to be considered before engaging in the conversational banking business
As we move to an AI-first world in which interactions with computing become more intelligent and natural, AI becomes the new UI. This points out a real paradigm shift transforming almost every industry. We also witness another disruptive change as the messaging platforms have engaged billions of active users, surpassing the social media platforms. Text and voice based messaging platforms are hosting many businesses that signals the beginning of the «post-app era».
Advancements in AI, specifically in natural language processing and deep learning, and the rise of messaging, have unveiled a new phase in customer interaction in the financial services. Today, conversational banking is considered as the new digital framework, that offers more direct and natural experiences than the existing mechanical channels which involve minimum personalization and humanization level as a digital experience.
Conversational banking is attracting the attention of many banks from various scales focusing on optimizing costs while providing a more direct, simple and natural interface to their customers. Conversational banking promises relevant use cases in 3 basic areas:
– Informational (frequently asked questions, basic personal financial information)
– Transactional (money transfers, payments)
– Advisory (personal finance management, micro-savings tools)
Banks attention to this new phase of customer interaction can be seen in Accenture’s Banking Technology Vision 2017, which is based on a global survey of more than 5,400 business and IT executives across 31 countries.
– 79% of bank executives agree that AI will revolutionize the way they gain information from and interact with customers
– 29% believe it is extremely important to offer their products/services through centralized platforms/assistants or messaging bots
– 76% believe that in the next three years, the majority of organizations in banking will deploy AI interfaces as their primary point for interacting with customers
– 71% believe that AI is capable of becoming the face of their organization or brand
Juniper’s Research “Chatbot Retail, eCommerce, Banking & Healthcare 2017-2022” also predicts the opportunities for financial services companies. Some remarkable ones are as follows:
– The chatbot could save businesses $8 billion annually
– 4 min. – the average time saving per chatbot enquiry compared to traditional call centers
– $0.70 – the average cost saved per chatbot interaction
– 90% – the success rate of bot interactions in banking
These concrete findings led companies to focus on utilizing conversational AI in both customer interaction and internal processes. Although building a conversational platform based on AI involves big potential both in terms of efficiency and enhancement of customer experience, the effectiveness of such a platform depends on the unique circumstances, cultural features and expectations of each and every company.
From this perspective, it can be asserted that a financial services company needs to answer these basic questions prior to its engagement into the conversational AI:
– What is the target group of this platform? – Customers (Which segments) – Employees
– What is the purpose of the platform? – Increasing efficiency – Process improvement – Enhancement of CX
– Which platforms will be included? – Banks’s own channels as website/mobile app – social messaging platforms – voice based assistants
– Will it be cross channel and/or omnichannel?
– Which functions will be realized? – Informational – Transactional – Advisory
– Will it be rule-based or AI-based? Can it understand natural human dialogues? Does it learn from experiences? Will it understand and be able to continue within a context?
– Does it identify the customer or does it provide general public answers? Will it be able to provide a personalized experience?
– If it will involve personalization how will the connection with the data analytics platforms will be sustained?
– Will it be cloud-based or on-premise?
– Will it be text-based or will it contain voice-based interactions?
– What kind of interface features will empower the platform like carousels, graphs, charts, visuals, videos, links etc.?
– Will it be reactive or will it initiate interactions proactively?
– What will be the balance of human and AI? What kind of a human&AI model will be implemented?
– How will the compliance with the security and privacy regulations be enabled?
These are some of the key decisions that have to be made prior to engaging in the conversational AI business. It is not a simple task, especially for large scale enterprises like banks containing various functions, silos, processes, products, customer segments and regulations. However, it offers big potentials. Therefore, the banks that position themselves to meet customer expectations by offering simple, personalized and seamless experiences and recognize the power of conversational AI will design and implement the sustainable business models of the future.