How generative AI can transform banking CX — it starts with more productive post-call work

Generative artificial intelligence (gen AI) has captured the imagination of the business world since the introduction of Open AI’s ChatGPT in late 2022.

As a result, organizational leaders across industries have been investigating how gen AI’s ability to create new text, images, code and other content can help them boost efficiency and gain an advantage on competitors.

Leaders in the financial services sector are no doubt paying close attention to AI’s potential to enhance a range of business disciplines, such as marketing, sales, software engineering and customer support.

Indeed, a report by McKinsey heralded banking as “among the industries that could see the biggest impact as a percentage of their revenues from generative AI.” If fully integrated, gen AI could contribute an additional $200 billion to $340 billion annually across the banking industry, according to McKinsey.

Although we can imagine numerous eventual use cases for gen AI in banking, most leaders are likely to take a cautious approach in adopting the technology as potential benefits and risks continue to be identified. Perhaps the biggest risk associated with gen AI is “hallucination,” which occurs when these systems invent their own “facts,” confusing and misleading users.

With such well-founded concerns over hallucination, most banks will understandably be initially reluctant to allow customers to directly interact with gen AI without guardrails. Nonetheless, banks can use gen AI today to boost the efficiency and effectiveness of their customer experience (CX) teams, while investigating the technology for future use cases that will improve the customer journey.

3 ways generative AI improves banking CX

For banks, help with improving customer service is no small consideration. For example, CX quality has remained flat for banks, while CX scores for multichannel banks fell for the second consecutive year, according to a report from Forrester Research.

Delivering high-quality CX is a significant priority for banking executives because strong customer service is inevitably correlated with higher customer loyalty and greater deposit retention. With so many choices, today’s consumers often refuse to tolerate substandard CX, opting instead for banks or neobanks that deliver convenience and personalized services.

Because gen AI is capable of responding to customer queries with human-like responses, the technology can help banks meet consumers’ increasingly high expectations.

Let’s get into the three ways banks can use gen AI right now to improve CX:

Increase staff productivity: Gen AI can automate routine tasks that require the investment of substantial human resources, such as summarizing customer interactions and recommending next steps. Traditionally, this “after-call work” has been performed by agents immediately upon completing customer calls.

While time-consuming for staff members, these summaries are essential for banks to properly coordinate customer service. By automating data entry and document processing, banks can save time on each customer interaction and redirect human efforts toward more strategic goals, driving greater productivity and operational efficiency.

Improving customer service: By analyzing historical data and real-time interactions, generative AI helps banks facilitate personalized customer service on a larger scale. Given the competitive banking landscape, this advantage helps strengthen customer relationships and loyalty with tailor-made solutions.

Banks can employ generative AI to analyze every customer interaction in real-time, proactively identifying CX friction points that could benefit from increased automation. For example, banks can leverage generative AI to detect fraud by uncovering patterns, anomalies and signs of compromise.

Promoting innovation: To grow, banks must innovate. Gen AI can help banks further product development by rapidly generating and testing numerous variations of ideas and prototypes, accelerating innovation. For example, banks have traditionally trained virtual customer service agents to recognize every phrase a customer might say that indicates a desire to check their account balance.

In contrast, with gen AI, a virtual agent can learn the intent of each of these phrases on its own, removing the need to be trained on every variation. Gen AI can also improve risk management for financial institutions by identifying potential risks and opportunities through complex data analysis.

Requirements for successful implementation of generative AI

Of course, generative AI is no panacea. To succeed in this emerging field, banks need to ensure proper technological infrastructure, collaboration, and optimization. Here are three essential elements that every generative AI initiative must account for:

Risk assessment: Hurried AI implementations lacking adequate risk assessment may lead to costly problems down the road. Therefore, it is essential for banks to identify potential risk associated with gen AI adoption and develop mitigation strategies. One popular option is to ensure oversight via “human-in-the-loop” trainers who can identify and remove information hallucinated by gen AI.

Scalability and infrastructure: To realize the full benefits of gen AI initiatives, these projects must be scalable and rely on infrastructure that can support growing service demands. Bank contact centers that run on legacy systems lack the scalability to support generative AI, requiring banks to migrate legacy centers to the cloud.

Piloting and testing: Small-scale pilot programs and testing validate gen AI solutions before full-scale integration. This approach enables banking leaders to identify challenges, gather feedback, and fine-tune AI models for optimal performance.

Wrapping it up

Generative AI holds the potential to revolutionize how the banking sector manages customer service, offering an approach that can boost productivity and promote innovation.

By harmonizing human efforts with the advantages of this emerging technology, banks can pave the way for genuine transformation.

Rahul Kumar is Vice President and General Manager for financial services at Talkdesk.