The call center has always been an important way for banks to connect with customers. But it won’t be long before call centers without artificial intelligence (AI) will be unable to make those human connections.

I’m reminded of a meeting that I and one of my colleagues recently had with a bank CEO. My colleague remarked that he and his wife had been a customer of the bank for 25 years. Yet, in a recent interaction with a customer service representative (CSR) at the bank, the representative was unaware that my colleague’s daughter had recently turned 18 and begun her financial life as an adult. The CSR – and the bank – had missed an opportunity to acquire a new customer by, for example, suggesting that his daughter open a checking account or obtain a credit card.

AI is changing all that. Today, AI-based call centers can be found assisting financial services CSRs throughout the call process. Conversational AI automatically handles many types of incoming calls, such as requests for account or product information. We worked with a large insurance and wealth management company, for example, to deploy a chatbot-based virtual assistant that handles hundreds of common call center inquiries and transactions related to account balances, withdrawals, loans and transfers. The system has reduced the volume of calls handled by live agents by 5%, improved the center’s customer service index score by 5% and reduced operating costs by $6.7 million.

For more complex calls, AI applications can route the customer to the right CSR. Before the CSR even answers the incoming call, the system identifies who the customer is, including details like the customer’s financial profile and the likely reason for the call based on an analysis of recent financial activity, personal preferences, geographical location and recent events – like a daughter turning 18. It then suggests potential products and solutions that can help address the customer’s needs and meet their goals.

Freeing Agents to Focus on the Customer

During a call, AI solutions “listen in” on the conversation and provide the agent with real-time support. They can, for example, automatically retrieve information that the agent or customer needs, dramatically impacting both the agent’s and the customer’s experience. One analysis found that in a typical six-minute customer service call, only one-quarter of that time involved customer interaction, with the rest taken up by manual research tasks. By automatically handling research and administrative tasks, AI-based call centers can enable agents to do work that’s more interesting and valuable. As agents begin delivering a better customer experience, this leads to greater job satisfaction and a more effective employee – one who can focus on connecting with customers.

When a call is complete, CSRs have to create call summaries. Not only is this time-consuming, but the summaries themselves can also vary in quality and content based on how busy the agents are. With AI-based call centers, financial institutions can now automatically create these summaries quickly and consistently, and include all the key phrases used by the customer and the agent on the call.

Getting to the Heart of the Matter

Banks are also using AI-based call centers to provide real-time coaching during calls. In this case, the AI system analyzes the caller’s data and their questions during the call to provide the CSR with recommended products or solutions customized to individual situations and needs. Or, by analyzing diction, word choice, tone and even the pauses between words, it gauges caller sentiment and determines whether they are angry or frustrated. It then recommends incentives the CSR can offer to satisfy the customer, such as waiving fees, and even notify supervisors when they need to step in to help.

When a large financial institution wanted to provide a better customer experience, we helped it use natural language processing and sentiment analysis to classify call types, structure data and develop sentiment measures. Used in conjunction with predictive analytics, this allowed the bank to use call center interactions to anticipate future customer behavior and develop strategies to improve customer outcomes. The system streamlined call center operations and helped boost customer satisfaction scores by up to 20%.

AI helps call centers continuously “learn,” as well. We recently designed an AI contact center solution for a global property and casualty insurer that gives CSRs real-time personality profiling and conversation cues while a call is in progress. It also allows the insurer to monitor about 8,000 calls a month to help drive ongoing improvement – rather than just a handful – while slashing review time by as much as 40%.

Soon, it will become all too obvious – to both customers and agents – when their bank does and doesn’t use AI. Banks that begin investing in AI-based call centers now will be better positioned to forge all-important customer connections in the near future.

Maria Nazareth

Maria Nazareth

Maria Nazareth is Associate Vice President of AI in Cognizant’s Banking & Financial Services Practice. In this role, she enables clients to... Read more