Transforming customer support in banking: Putting cloud and AI to work with agents

By now, most customers have interacted with AI-driven chatbots. These types of chatbots understand what consumers are asking or looking for and provide them with a truly conversational experience.

Many banks already use AI-driven chatbots for front-end customer support. And more banks are rolling them out every day for that purpose.

What many banks don't realize is that they can apply the same underlying, cloud-based technology – known as conversational artificial intelligence (CAI) – behind the scenes to maximize call center effectiveness and efficiency and further enhance the customer experience.

Specifically, banks can use CAI with their call center agents, who are all too often overlooked, to transform their customer support function.

For example, banks can use CAI to:

Hiring the right frontline agents is key to delivering consistently excellent customer support. And CAI can be extremely useful in helping banks to make sound agent hiring decisions, especially when assessing soft skills such as empathy, active listening, and responsiveness.

It can test a candidate's ability to manage a range of customer and call types ­­– both in unguided and guided scenarios, such as role plays, which provide help prompts­­.

Because the technology is cloud based, hiring managers can give potential employees remote access to assessments as needed. And then they can review those assessments from wherever they are, whenever they have time.

Banks can also embed CAI into their new-hire training curricula, giving new agents a safe environment where they can practice and learn with no risk to bank customers or their own performance evaluations.

Many banks have told us that getting trainees on the floor for guided or on-the-job training as soon as possible is the primary aim of classroom or instructor-led training. CAI provides the perfect intermediary step for agents – after they've completed classroom training and before they begin serving actual customers on their own.

With CAI, banks can reduce overall time to train, getting new agents in on the action faster.

Especially in an era of virtualized workforces — where call center managers may not be able to walk the floor to provide agents with timely feedback — CAI can help banks deliver excellent customer support by providing agents with in-the-moment coaching.

For example, CAI can push training modules to agents' desktop portals to help them respond to actual customers with enhanced empathy and emotional intelligence in real time. Call center managers can also schedule agents to participate in training, either as part of their after-call work or at designated training times. Alternatively, they can manually assign trainings to an agent based on customer satisfaction or other scorecard results to drive improvement in specific areas.

And these trainings can focus on contact types, customer types, products, or situational scenarios that require continued practice.

Effective CAI interfaces enable agents to make quicker and more effective decisions by combining system-of-record data – pulled from customer relationship management systems and transaction databases, for example – with insights from customer interactions and journeys. Customer support teams and systems integration experts should prioritize trainings based on the frequency and friction of these journeys.

For even greater impact, banks can marry CAI with downstream robotic process automation. For example, if a customer calls in to dispute a transaction, the CAI might prompt the agent to ask specific, clarifying questions while a bot gathers information and auto-populates data entry fields so the agent doesn't have to.

With the information they need literally at their fingertips, agents can make lightning-fast, effective decisions to better support bank customers.

Based on customer context or response, CAI can also offer agents immediate suggestions for what they should do next. This ability to suggest the 'next best action' is the Holy Grail of AI-based systems. But ultimately, it relies on accurate customer segmentation modeling and prediction engines that sit outside the AI.

For example, based on a customer's profile and the nature of the conversation with the agent, the CAI can prompt the agent to recommend a specific, applicable, and relevant offer that the customer is statistically likely to accept. In this way, CAI can help banks drive sales conversions. It can also prompt agents to make suggestions that effectively close out the customer's inquiry, leading to coveted first-call resolutions.

Increasingly, front-end digital channels are handling lower complexity customer interactions. As a result, customer interactions with human agents are becoming more complex. This means it is critical for banks to hire better agents in the first place, train them to become even more effective, and use advanced technologies to assist them during customer interactions so they can make more informed and efficient decisions.

CAI offers banks many opportunities in the contact center space. It can improve the agent experience and empower agents to improve their performance and reach their full potential. This, in turn, positively impacts the bank's customers and bottom line.

CAI is a cloud-based technology. And cloud is the foundation upon which banks build true digital transformation. Without it, exceptional and innovative customer and agent experiences – backed by advanced digital technologies like CAI – cannot be realized at speed and scale. So, building a strong cloud foundation now will pay off for banks long into the future.

Making agents' lives easier should be a top priority for all banks and, indeed, for any organization focused on customer experience. The more efficiently and effectively agents perform their jobs, the better the customer experience and business outcomes for the bank.