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The Business Value Of Improving Complaints Management Using Generative AI

Started ‎11-01-2023 by
Modified ‎11-01-2023 by
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Article By - Sidharth Khona (Business Advisory & Business Value Lead India)


My colleague @FedericoPozziAI recently wrote on the Complaints Management With Generative AI. Providing outstanding customer service is critical for success in today’s highly competitive banking sector. Customer complaints are an important customer touchpoint—and the way that they are handled can make or break the relationship with that customer. They may also arrive by phone, email, letters, or via customer service chatbots on the bank’s website, but must all be handled consistently and rapidly.

Banks are increasingly turning to new solutions to help them to manage complaints more effectively. One option is using a combination of analytics and generative artificial intelligence (AI), which provides considerable Business Value.


Managing Customer Complaints

Customer complaints are a natural part of any business, including banks. However, many businesses find them extremely complex and time-consuming to manage. Currently, most complaints are dealt with by employees, which has huge benefits in terms of making the process more ‘human’. However, people have finite capacity. They are also not always consistent with themselves or each other, even with a script—and using a script, of course, decreases complaints handlers’ ability to respond more personally. During busy periods, complaints handlers may experience fatigue and burnout, or response times may be longer and slower. For global companies, there are also issues about where complaints handlers are based, and how to respond to customer complaints from different time zones. It may also be challenging to analyse the data from complaints as a way to improve the complaints handling process.


The real issue, though, is that being unable to address customer complaints adequately results in lower satisfaction for both customers and employees. It also results in far higher costs of complaints handling, and greater customer churn, which is expensive because it means banks incur the costs of acquiring new customers.


A New Option: Harnessing AI and Analytics

To address these problems, banks are now turning to AI and analytics to support the complaints management process.

The key word here is "support". This is not about replacing complaints handlers with AI or chatbots. Instead, it is about using automation to supplement the process, but without removing the human touch. This effectively speeds up the complaints management process, making it more likely that the customer will receive a satisfactory response to their complaint.



There are two sides to the process: one driven by analytics, and the other by generative AI, or large language models. The analytics side automatically categorises ticket information, such as the product concerned and the issue raised. It incorporates AI-driven offer arbitration in the process, so that it can generate a ‘next best offer’ for the customer and include this in the automated reply. The large language model summarises long email threads or phone calls, and automatically generates a reply to the customer for review by the complaints handler.

This relatively simple addition to the complaints management process has considerable business benefits for customers, employees, the process and the bank (see figure).


Customer satisfaction and loyalty are likely to increase because of faster response times and better resolution. Customers are also less likely to take their business elsewhere. Employees will benefit from being more satisfied and more efficient. Their average handling time could reduce by 20% to 40%, and average response time by 30% to 40%. The volume of complaints handled is likely to increase by 15% to 20%.


The process efficiency is also greatly improved, with complaint resolution time going down by around 20% to 25%, and cost per contact by 8% to 15%. It will be easier to generate data-driven insights into trends and issue resolution patterns, enabling other process improvements. Finally the bank sees benefits such as better regulatory compliance, and fewer compliance violations. When customers are happier, they will leave better online reviews and ratings, improving the bank’s reputation. The bank can also incorporate more customer feedback into product improvements.


A Combined Approach

The key to this improvement is the combination of human complaints manager with analytics and generative AI. Analytics identifies the problem and proposes a suitable solution, generative AI summarises issues and drafts replies, and the complaints manager controls the process and ensures that it remains fully human.


It is not an exaggeration to say that this provides a quantum leap in complaints management efficiency, effectiveness and customer focus. The process is simpler, but provides a much better opportunity to engage effectively with customers and create an outcome that improves trust and relationships. It could well be the start of a new era in complaints management.

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