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The Art and Science of Conversational Banking with AI

With high-tech Conversational Banking platforms, the art is designing a great experience centered on words – written and spoken. This represents a shift from traditional design (which focuses on content, graphics, and buttons) to recognizing what a customer is asking, maintaining the context of the conversation, providing relevant responses, and performing actions for the customer.

A catalyst for this trend is today's age of "hyper personalization" – an art (and a science) that is mastered by Big Tech companies such as Amazon, Facebook, and Apple. With Conversational Banking, banks use technology to interact with customers in intelligent, two-way conversations and experiences, personalized to the specific customer. This leads to enhanced customer engagement and improved operational efficiencies – a true win-win scenario.

Conversational Banking tools can effectively communicate with customers in whatever way the customer chooses to describe his or her banking needs. In the past, digital experiences took a user down a steep path to find an answer. This assumed the customer had enough knowledge (and patience) to make the right choices throughout the digital journey to find the answer. Results were not stellar! In contrast, modern conversational platforms are designed to consider the many ways that customers may ask a question or make a request, with no clear starting or ending point. The reality is that customers do not speak in bank jargon – they may use acronyms, slang, and even emojis to communicate, and will weave in and out of topics along the way. In conversational platform design, information architecture must take all of this into account.

Next generation Conversational Banking bots can complete simple tasks and complex workflows.

Lightweight chat software (chatbots / bots), powered by Artificial Intelligence (AI), communicate with bank customers and bank employees through familiar text and voice-based interfaces to enable a 2-way digital experience and conversation.The bot processes natural language commands from speech or text.Using AI and Machine Learning (ML), the bot understands context, keeps information in memory, analyzes emotions, and learns from interactions.Interaction occurs when it is needed – proactively, scheduled, or on demand.

For banking, the best bots offer:

  • Superior Automatic Speech Recognition (ASR): Trained for higher vocabulary ranking; provides context intelligence and enables natural language processing.
  • Speed to Market: Pre-built bots help the bank to begin the Conversational Banking journey; a bot builder framework enables the bank to extend and customize bots, and build new bots to meet their tactical and strategic Conversational Banking objectives.
  • Built for Banking: Enterprise-grade and purpose-built for banking.
  • Omnichannel: Deployment of a single bot configuration across many channels, with centralized management capabilities.
  • Flexible Deployment Options: On premise, private cloud, public cloud, or a hybrid.AI and ML
  • Empathy Engine: In addition to essential customer/transaction servicing, also helps to optimize the customer's financial behavior and enables intelligent goal setting and fulfillment.
  • Differentiation: Application program interface (API) gateway and marketplace provides a common digital API that can be used by any channel to construct truly differentiated user experiences and offerings.

We'll "continue this conversation" in my next blog where we discuss the role of Conversational AI in next generation Personal Financial Management 


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Andrew Beatty

Andrew Beatty

Head of Wealth, Retirement & International


Member since

17 Sep 2018



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This post is from a series of posts in the group:

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