AI in the contact center: Benefits, innovations and training

This interview first appeared as part of the BAI Special Report: The strategic contact center of today and tomorrow. Find more perspectives in the report on optimizing CX technology and creating enterprise-wide strategies from this crucial banking hub.

Lindsay Soergel has been an executive in the banking and financial technology domain for nearly 25 years, with expertise in self-service banking and omnichannel customer experience. She has served as a technology and marketing executive at two large U.S. banks, several well-known global financial technology providers and innovative technology startups serving financial institutions of all sizes.

Soergel’s professional passion is using data and technology to connect people with vital content in memorable, personalized ways, and her teams have been recognized for a variety of digital banking “firsts.”

What AI technologies are currently being used in contact centers?

Considering how generative AI advances dominate the news, it can be easy to forget that artificial intelligence has been around for a long time and that contact centers were among the first areas of the financial institution to adopt AI for consumer-facing applications. Whether we’re thinking about speech recognition, automated call routing, predictive analytics, voice biometrics or natural language processing, many of these AI-based technologies have been in use at scale since the 1990s. So it stands to reason that more recent innovations in AI—such as intent detection, automated quality assurance and generative AI copilots and agent assistants—have all quickly found a home in our financial call centers.

What are the key benefits of using AI in the contact center?

AI is a natural fit for the contact center. The leaders in this area of banking are continuously challenged to find new ways to improve operating efficiency, enhance teammate performance and ensure the security of every interaction, all while delivering a better experience for banking consumers. That can be a really tall order, but AI delivers advantages in each of these areas.

Regarding operating efficiency, chatbots can enable after-hours coverage with no need to add staff. In terms of teammate performance, AI agent assistants can improve first-call resolution and average call-time metrics by 15% or better. And AI-based security and privacy technologies like voice biometrics, data anonymization and end-to-end encryption are now built directly into call center platforms, all of which contribute to a more secure experience. Finally, when it comes to the consumer experience, AI-driven personalization has delivered significant improvements in customer satisfaction scores, which tend to correlate directly with customer loyalty and profitability.

Is AI spurring any process innovations in contact centers?

It is not an overstatement to say that AI is at the heart of a process innovation revolution in contact centers. Since the public launch of ChatGPT in November 2022, we’ve heard a lot about how generative AI makes it possible for agents to access banking procedures, policies and regulations in an instant, enabling them to serve customers faster and with higher quality. These advances are delivering real progress. Yet, I think some of the most exciting progress is happening behind the scenes at the contact center, in the form of fraud prevention and risk mitigation innovations. AI can monitor human interactions and proactively detect anomalies that signal potentially fraudulent behaviors, by both employees and consumers. AI can also look for potential lapses in regulatory compliance or the disclosure of sensitive financial information, and then it can use real-time agent alerts and data masking techniques to mitigate these risks.

How can AI be used to train contact center agents?

Banking industry studies have consistently found that new employees stand to benefit most from the introduction of AI. Agents who have been on the job for a while often know where to look to quickly find information. But newer employees don’t have that advantage, so it helps to consult a banking-savvy large language model for a bit of guidance. AI copilots can also monitor conversations and provide real-time coaching and assistance to the agents, helping them get up to speed faster than was historically possible. And, increasingly, AI is being incorporated directly into agent training modules, an approach which offers the advantages of purpose-built simulations, virtual role-playing and personalized learning programs that adapt directly to each individual being trained.

What can financial institutions do to ensure smooth adoption of AI in the contact center?

Bankers can take care to listen to their teams first, understand what concerns they may have about AI and be sure to address those through training and education. They can introduce AI as a kind of virtual teammate that is there to help agents do their jobs better. AI takes care of the monotonous work, the highly manual and time-consuming processes that have historically prevented agents from doing the best part of the job—serving customers and members. So, leaders should be honest with their teams and let them know that AI is now a key part of the way business gets done, and then be sure to communicate regularly to uncover and correct for any challenges the human team is experiencing with the change.

How have you seen contact center agents adapt to using AI?

Some of the very best, most successful integrations of digital assistants and generative AI copilots have occurred when the bankers really lean into the more human and conversational qualities of AI. Doing this requires some advance planning and collaboration among the contact center folks, the digital channel leaders and the brand and marketing team. It also helps to incorporate some direct customer feedback during the planning process. By treating AI a bit more like a teammate and a bit less like software, many banks and credit unions have designed AI solutions that have distinct “personalities” and that do a great job reflecting the institution’s unique brand identity. This approach allows the agents—and the consumers they serve—to have a bit of fun with AI. These FIs and teams tend to be the ones leading in customer and employee adoption, which has a positive impact on loyalty, share of wallet and profit.