How conversational AI is shaping the future of banking

0
340

Share on LinkedIn

Financial institutions are at the forefront of technological innovations, searching for ways to execute faster and serve their customers better. But in striving for the latest and greatest solutions, it may be tempting to embrace whatever technology comes around. This has led to the proliferation of chatbots, which claim to bolster call centers with automation. In reality, these “bots” behave more like dated robots and are highly rigid in how they interact with customers, creating an IVR 2.0 format that frustrates callers and prevents banks from serving their customers.

This is especially challenging today, in the aftermath of stay-at-home orders and the possibility of subsequent lockdowns. Many banks were overwhelmed by an influx of calls at height of the quarantine, and they are now facing a potential resurgence as many cities and states reconsider their decision to reopen.

Even when call volumes are high, banks need to be able offer the same quality of service over the phone as they would in person. Yet banks can’t be expected to hire an overabundance of call center agents to handle fluctuating call volumes or satisfy customers with chatbots. They should instead look to the power of digital employees, which can help them meet customer expectations in ways that are not possible with any other technology.

Adapt to customer needs

Conversational artificial intelligence (AI) is the backbone of digital employees, which differ from chatbots in a number of ways, starting with 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 will 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.

Chatbots were 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 NPS scores and limit the number of contacts that can be resolved on first contact.

Unlike a chatbot, digital employees can adapt to customer needs. Most importantly, digital employees understand what the customer meant. That means if a customer says, “On Tuesday, transfer $200 to Jeff,” the digital employee will understand the request. If the customer then adds, “Transfer it on Wednesday instead via Zelle,” conversational AI will understand what the user meant, react accordingly and transfer the money via the requested service without further clarification.

Digital employees can also prioritize the most important aspects of a request. Suppose that a customer says the following: “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 that 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 recognizing the second intent to know when the gift card will ship.

Help customers without restrictions

Learning is another key facet that differentiate 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.

As highlighted before the ability to handle 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 are more 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.

Chetan Dube
Chetan Dube has served as the President and CEO of IPsoft since its inception in 1998. During his tenure, he has led the company to create a radical shift in the way IT is managed. Prior to joining IPsoft, Chetan served as an Assistant Professor at New York University, where his research was focused on deterministic finite-state computing engines. Chetan is a widely recognized speaker on autonomics, cognitive computing and the future impact of a digital workforce. He serves on the board of numerous IT-related institutions.

ADD YOUR COMMENT

Please use comments to add value to the discussion. Maximum one link to an educational blog post or article. We will NOT PUBLISH brief comments like "good post," comments that mainly promote links, or comments with links to companies, products, or services.

Please enter your comment!
Please enter your name here