You might have heard the term Conversational AI before, after all, it is currently revolutionising banking as we know it. But what is it?
The term conversational AI (CAI) refers to the underlying set of intelligent technologies that enable software systems to interact with humans using natural language processing (NLP).
This involves the ability of software to understand the intent behind what a human is saying and respond in an intelligent, conversational way. In the last decade, technologies and use cases have evolved so rapidly that we have seen a deluge of terms enter circulation like chatbot, virtual agent, voice assistant and conversational UI to name a few.
For senior executives and customer-focused leaders, certainly they should be looking to make this new channel a fundamental part of their banks’ wider customer engagement strategy.
That’s why EPAM has produced a white paper outlining 7 Lessons Learned from the Field as a practical guide for both business leaders and technologists with customer-facing responsibilities in banking.
The power of natural language and emotional awareness in interaction should not be underestimated. CAI is therefore a critical part of modern customer experience strategy, helping your bank stand out from the crowd, build new relationships and strengthen existing ones.
Inside the white paper, you can find 7 Lessons from the Field. These are:
- Identify the problems you’re trying to solve
- Align the organisation on a conversational AI vision
- Think strategically about your conversational AI vision
- Secure funding and momentum for your conversational strategy
- Staff the right talent: starting with a conversational analyst
- Create a persona for your conversational AI early
- Optimise your virtual agent through agile design and delivery
Alongside these key seven elements, there’s a chance to take a deep dive into understanding conversational AI.
After all, conversational AI technologies aren’t new. However, over the last decade or so, the technologies have evolved so rapidly that we have seen a deluge of terms circulate and find use in the industry—chatbot, virtual agent, voice assistant and conversational UI to name a few. That—combined with the complex nature of these technologies—has made them hard to keep up with, invariably resulting in confusion for businesses and consumers alike.
This deep dive defines the two types of common conversational AI solutions. From the virtual assistant, to the virtual agent. There’s also an example of a conversational AI session flow, to really understand the process involved. However, it’s important to note that once you’ve launched your conversational AI program successfully, keep monitoring it and make improvements as necessary so that you are meeting—and exceeding—customers’ evolving expectation.
Global spend on AI is forecast to double, growing to more than $110 billion in 2024, with banking and retail predicted to spend the most.
40% of 18- to 44-year-old consumers are ready to bank through social platforms and voice assistants according to the EPAM 2020 banking report.
The Bottom Line
With cost pressure relentlessly increasing and every bank’s budget squeezed year over year, it’s clear to see where CAI can make the biggest impact: the bottom line. Increased automation, reduced wait times, personalisation, consistency and more successful service outcomes can all drive significant efficiency and revenue gains. Expect simple automation to deliver around a 30% reduction in customer service queries and up to 80% for more complex and sophisticated experiences that integrate with your back-end systems.
While CAI is not a silver bullet for everything, there are almost certainly quick wins to be gained by identifying customer interactions that will deliver maximum value with the lowest effort. What’s more, outstanding customer service will almost certainly depend on a fine balance of CAI and human interaction. All banks must transform their customer service vision and start preparing now as they have the opportunity to be at the forefront of the next wave of transformation, seamlessly integrating conversational AI to solve the complex challenge of serving and assisting time-challenged customers at every step of their journey.
Click here to read the white paper in full.