By Stephen Harcup, Head of AI Banking, EMEA, IPsoft

After years of incremental change, banks need a fundamental rethink of operations in order to thrive in a rapidly digitised and data-driven world.

Across the globe, the retail banking industry is fast embracing a mobile-centric customer experience. Investment in mobile technologies has led to a rapid adoption of digital banking to meet consumers’ constantly evolving demands. Meanwhile, consumers’ experiences in other industries are upping the ante for most banks. Recent research found that banking consumers have a stronger emotional connection to brands like Apple, Amazon, and Google than to their banks. These companies have the ability to blend experiences from the physical and digital worlds and that is what provides a good model for banks.

But in striving for the latest and greatest omnichannel solutions, banks may be tempted to embrace whatever new technology is available. This has led to a glut of banks implementing chatbots, which claim to bolster customer service functions with automation. In reality, these “bots” behave more like dated robots and are highly rigid in how they interact with customers, creating an experience that frustrates callers and prevents banks from truly serving their customers.

This need to bolster customer service offerings with technologies is especially pertinent today, in the aftermath of COVID-19 lockdown measures and the possibility of subsequent lockdowns. It’s now clear that many banks were overwhelmed by an influx of calls at the height of the quarantine, and they are now facing a potential resurgence as many cities and towns deal with local flare ups.

Yet, for whatever reasons call volumes spike, banks need to be able offer the same quality of service over the phone as they would in person. Banks can’t be expected to satisfy customers with rudimentary chatbots. They should instead look to the power of Digital Employees, which can help them meet scalable customer expectations in ways that are not possible with any other technology.

Adapt to customer needs

Conversational artificial intelligence (AI) forms the backbone of Digital Employees, a new technology that differs from chatbots in a number of ways – a primary one being their ability to handle customer going off script. Chatbots cannot determine what customers want if they change their mind mid-sentence, or introduce multiple issues or queries simultaneously. Chatbots tend to become confused and either provide the wrong answer or fail to provide any answer at all. This can be extremely frustrating for consumers, whose issues will only be worsened by the chatbot’s inability to resolve them.

Stephen Harcup

Chatbots are built with a strict, formulaic interaction in mind. They cannot learn to answer questions beyond the way in which they were programmed, nor can they learn to resolve new issues over time. This inevitably leads to roadblocks that reduce net promoter scores (NPS) and decrease the number of interactions that can be resolved on first contact. Moreover, conversational AI agents will make it easier for customers to access their bank as they are “always on” and will never deviate from best practice or have a “bad day”.

Unlike a chatbot, digital employees can rapidly adapt to customer needs. Most importantly, in the form of customer intent. When a customer says, “On Wednesday, transfer £100 to Steve” the Digital Employee will understand the request. If the customer then adds, “Transfer it on Thursday instead” the conversational AI will understand what the user meant by “it”, react accordingly and transfer the money via the requested service without further clarification.

Digital employees can also prioritise the most important aspects of a request. Suppose that a customer says “I cashed in my loyalty points for a gift card and would like to know when it will ship. Also, there is a fraudulent charge on my account, so I’ll need to cancel my credit card,” chatbots would not know to respond. At best, a customer might find out when the gift card will ship. Digital employees are able to cut through the clutter and take immediate action on the fraudulent charge, while also recognising the second intent to know when the gift card will ship.

Help customers without restrictions

Learning is another key facet that differentiates Digital Employees from traditional chatbots. Chatbots, as rigid systems, don’t get smarter with time, nor can they provide assistance in the form of a whisper agent, which helps human employees answer customer questions and resolve problems faster and more efficiently.

The ability to handle the unexpected is key to driving NPS and first call resolution. The key differentiators for Digital Employees reside here. In fact, they can go beyond the automation of simple tasks, such as troubleshooting and password resets. Capable of helping customers unearth account details, process mortgage applications, and introduce new products, digital employees are quickly becoming a personal concierge for every customer.

They go further than an FAQ alternative, using Natural Language Processing (NLP) to better understand what the human is trying to say. Unlike a chatbot, digital employees will not come to a standstill simply because a customer asked more than one question at a time.

Built to provide solutions without stumbling

Chatbots and true AI – specifically conversational AI – should not be confused. They are not the same and will not provide the same results. While chatbots cannot handle the unexpected, Digital Employees can evolve with customer needs.

Powered by conversational AI, digital employees can decipher complex sequences, identify intent and provide solutions without stumbling or reaching dead ends. And, if there is a problem it cannot resolve on its own, the Digital Employee is smart enough to transfer over to a human customer agent, who can take the reins from there.

Ultimately, conversational AI technologies – in the form of Digital Employees – have matured and are ready to implement now. They offer the best opportunity in decades to establish new operational models. By pairing the existing strengths of traditional banking, with cutting-edge AI technology, banks can seize competitive advantage amongst a growing number of non-competitive forces. The speed and scalability of cognitive technology will release a constant stream of growth opportunities for banks that adopt conversational AI now.