How conversational AI can help banks grow

9 August 2021 | 3111 Shares

Do you ever ask Siri if it’s going to rain tomorrow? Or ask Alexa to play your favourite song? For millions of us, having conversational interactions with technology has quickly become second nature.

This presents a real challenge for many financial institutions, whose traditional, interactive voice response (IVR) systems often fall far below the expectations set by the voice-enabled virtual assistants of their customers’ smartphones and smart speakers.

Even as banks race to deliver intelligent, conversational self-service over the telephone, they must also work to keep pace with the digital services of online banks and fintech pioneers. The “forced familiarisation” of the pandemic has only made these efforts even more urgent, as even previously reluctant mobile banking customers have embraced messaging channels and mobile apps.

Simply put, financial institutions now face huge pressure to create personalised, conversational experiences, however a customer gets in touch. And in many cases, the key is conversational AI.

Applied intelligently and strategically, it can underpin natural, contextual interaction with banks, saving customers time and effort. It can help a bank’s agents to focus on the tasks that really need the human mind or touch. And it can support proactive service experiences and continuous optimisation through ongoing data analysis.

What’s more, it can unlock fresh opportunities for growth.

Growing with the help of AI

Both agile new entrants and historic household names are already using AI to differentiate, creating AI-assisted services that open new sources of revenue.

Think about personal finance apps such as Cleo, which allows users to track spending and saving through interactions with a chatbot. Or Digit, which automatically decides how much its users can afford to save based on their income and outgoings and moves an appropriate amount into their savings account every month. Such apps already have customer bases that number in the millions.

Another way AI is helping financial institutions grow is by allowing them to predict their customers’ wants and needs. In much the same way as retailers use AI to decide which books or shoes to promote to returning customers, banks are starting to use AI to crunch huge volumes of customer data and make the right offer at the right time.

For further evidence of the transformative effect of AI, look at the wealth management sector. Here, robo advisors are now so common it would be easy to feel overwhelmed by the number of options available to automate your investments. Indeed, it’s predicted that by 2023 robo advisors will be managing $2.5 trillion worth of assets.

Serving customers with the help of AI

If there’s one fundamental rule of customer service, it’s “make it as easy for the customer as you can”. Conversational AI is great at minimising customer effort.

Increasingly, major financial institutions are empowering their customers to complete everyday tasks—checking their balance or paying a bill, for example—by talking or typing to a virtual assistant (VA). Many are also using VAs to provide always-available, cost-efficient customer support.

Swedbank, one of Sweden’s largest retail banks, initially created its virtual assistant to help its agents find the right answers to customer queries. Soon, however, it put its VA to work on its website—where it now answers more than 80% of customer questions directly and supports personalised services like balance enquiries.

Through further integration, Swedbank has also empowered its VA to complete selected actions for its customers—for example, replacing or unblocking the customer’s card. (25% of all debit card replacements are now handled through the VA.)

Another great example is BNP Paribas Personal Finance Spain, which launched its VA to meet a dual objective. “With our virtual assistant project, we seek to achieve the most important improvements for any customer service model: greater customer satisfaction and increased efficiency,” says Paz Puchol, Director of Operational Digital Transformation, BNP Paribas Personal Finance.

The VA is able to answer more than 90 common customer questions. If it can’t help—or detects signs of frustration or aggression—it can seamlessly transfer the customer to a contact centre agent, along with all the context they need to continue the conversation. Two years after its launch, the VA is satisfactorily resolving 46% of customer queries without any agent involvement.

Fighting fraud with the help of AI

Fraudsters have seized on the disruption of the last 18 months, taking advantage of widespread anxieties and socially engineering isolated contact centre agents to exploit financial relief programmes.

For many financial institutions, the rising tide of fraud has heightened the need to move beyond traditional, knowledge-based authentication—with its easily stolen PINs and passwords—and implement biometric authentication based on inherent individual characteristics.

Voice biometrics technologies, for example, are an increasingly common choice for banks looking to strengthen fraud prevention and differentiate on customer experience.

The leading voice biometrics solutions can authenticate a customer in a few seconds. The customer says a passphrase—or simply starts talking—and the technology analyses hundreds of variables in their voice and matches it against their registered “voiceprint”.

This technology is already delivering impressive outcomes for financial institutions such as NatWest Group. “It’s not just about stopping financial loss—it’s about disrupting criminals,” says Jason Costain, Head of Fraud at NatWest. “For example, one prolific fraudster we identified was connected to suspect logins on 1,500 bank accounts. That’s helped us protect potential fraud victims and identify the ‘mules’ being used by the crime network to perpetrate fraud, leading to two arrests so far.”

Whether a financial institution is looking to strengthen fraud prevention or boost customer satisfaction, conversational AI technologies have a key role to play in enabling low-effort, high-security experiences.

In case you’re reading this article with a view to implementing conversational AI at your own institution, we’ll leave you with some practical advice.

Three tips for your conversational AI strategy

1: Aim for consistency

The experiences you create should remain consistent across your channels, even as you tweak them to take advantage of each channel’s strengths. Or, to put it another way, your customers should always feel like they’re interacting with the same brand, however they choose to engage.

2: Don’t lose the context

What’s worse than not getting the answer you need on your channel of choice? Having to repeat yourself as you try a different approach. So, save your customers this all-too-common pain—choose a conversational AI platform that can carry the context of their conversations across channels and interactions.

3: Optimise, optimise, optimise

With all AI-based initiatives, ongoing optimisation is the key to success. Regularly review your engagement data to assess omnichannel performance. You’ll identify hidden issues like bottlenecks, but you’ll also find opportunities to make your greatest customer journeys even greater.

It’s a short and simple list. But if you follow these principles as you implement conversational AI, you’ll set your institution up to not only meet the growing expectations of customers but to address other business priorities—from improving contact centre efficiency to reducing fraud losses and costs.

Want to talk conversational AI?

Nuance helps financial institutions create outstanding conversational experiences, and its enterprise-grade AI is used by 19 of the 20 largest financial services organisations in the world. Find out more about its customers and solutions.