Financial institutions such as banks are at the forefront of technological innovations, looking for ways to execute faster and serve their customers better. It may be tempting to embrace whatever technology comes on the way in striving for the latest and greatest solutions. It has led to the proliferation of chatbots that claim to reinforce call centres with automation. In reality, these bots behave like dated robots and are stubborn in how they communicate with customers, building an IVR 2.0 format that frustrates callers and does not allow banks from serving customers.
Due to the pandemic and the possibility of subsequent lockdowns, this seems challenging. Most of the banks were inundated by an influx of calls at the height of the quarantine. Now they are facing a potential resurgence as many states and cities reconsider their decision to reopen.
Even when call volumes are high, banks need to be able to serve the same quality of service over the phone as they would physically. However, banks cannot be expected to hire an overabundance of call centre executives for the smooth functioning of call volumes and satisfy customers with chatbots. They should instead monitor the power of digital employees, which can help them to meet customers' expectations in ways that are impossible with any other technology.
Conversational artificial intelligence backs digital employees, which differ from chatbots in numerous ways, starting with their ability to handle customer going off-script. Chatbots are unable to determine what customers want if they change their mind mid-sentence and come up with multiple issues or queries simultaneously. Being confused chatbots will either provide wrong answers or fail to give any answer at all. This could make consumers extremely frustrated, and their issues will only be worsened by the chatbot's inability to resolve them.
Chatbots are built with a strict, formulaic interaction in mind. They are not able to answer questions beyond their capacity in which they were programmed, nor can they learn to solve new issues over time. It inevitably drives roadblocks that reduce NPS scores and limit the number of contacts which can be sorted out on the first contact.
Digital employees can adapt to customers' needs, unlike a chatbot. Moreover, digital employees understand what the customer exactly referred to. For instance, if a customer says, "On Thursday, transfer $200 to Jack," the digital employee will understand what it means. If the consumer then adds, "Transfer it on Friday instead via Ricky," conversational artificial intelligence (AI) will understand what the customer meant, react accordingly and transfer the money via the requested service without further clarification.
Digital employees can prioritise the most important aspects of a request as well. For example, if a customer says, "I cashed my loyalty points for a gift card and would prefer to know when it will ship. Due to a fraudulent charge on my account, I need to cancel that card." Chatbots would not know how to respond; at best, a user might find out when the gift card ships. Digital employees can cut through the clutter and take immediate action on that fraudulent charge while identifying the dual intent to know when the gift card ships.
Learning is another key factor that distinguishes digital employees from traditional chatbots. Chatbots, as a rigid system, don't improve with time, nor can they assist in the form of a whisper executive that helps human employees answer customer queries and resolve problems faster and efficiently.
As focused before the capability to handle unexpected is the key to driving NPS and first call resolution. The key differentiators for digital employees lay here. They can even go beyond the automation of simple tasks like troubleshooting and password resets. The capacity of helping customers unearth account details, process mortgage applications and introduce new products, digital employees are quickly turning into a personal concierge for every consumer. They can perform more than an FAQ alternative, applying Natural Language Processing to understand better what the human is trying to imply. Unlike a chatbot, digital employees will experience standstill if a customer asks more than one question at a time.
One should not be confused between chatbots, true artificial intelligence and conversational artificial intelligence. These are not the same and do not deliver the same results. Wherein chatbots cannot handle the unexpected; digital employees can evolve with customer requirements.
Backed by conversational AI, digital employees can decipher complex sequence, recognise the intent and then provide solutions without stumbling or arriving at dead ends. If a problem comes up that it cannot resolve on its own, the digital employee is smart enough to hand it over to a human customer representative who can take the reins from there.
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