By now, there is a global consensus that the world will never be the same once we leave behind Covid-19. In the last two years, the pandemic has changed the way people and businesses function. As income patterns and consumer choices evolve, companies are pivoting to new models to cater to these.
For the banking industry, the significant shift is that their customers are more conscious than ever about their savings, investments, insurance, and other finances. They want to safeguard their future by attaining a comprehensive view of their finances. This trend is a significant opportunity for banks, NBFCs, and other financial institutions to build lasting relationships with customers. However, the key to these relationships is a 'cut-above customer experience.
The increased customer interest in financial planning has set off a higher number of inquiries at banking contact centers. Traditionally, these contact centers work on a human resource-heavy model. Contact center agents work with heaps of non-contextual and even dated data to respond to customer calls, emails, and chats. Add low agent capacity to the problem, and customer experience is far lower than optimal. Often, customers do not switch banks due to lower returns on investments but due to suboptimal experiences. To address these challenges, banks need to transform their contact center experience. Here’s how artificial intelligence (AI) powered contact centers can help banks differentiate themselves and attain customer stickiness:
Personalization: This is an essential aspect for every industry that requires customer interaction. Anyone loves to be treated with a bit of personalized touch. Moreover, customers have experienced personalized interactions in other industries and expect the same when they reach out to their banks. Using voice, text, email, and chat-based solutions, AI is helping banking contact centers create personalized experiences for customers. In addition, by leveraging AI, their last preferences/behavioral patterns are to be leveraged while conversing, making customer experiences smooth and streamlined.
Accuracy: Understanding customer queries and complaints from unstructured text or calls is challenging and perhaps better left to humans. However, when the queries and complaints are in large numbers, even humans tend to make mistakes with analysis and provide suboptimal solutions. Moreover, if these errors involve customers' hard-earned money, it reduces the bank’s credibility and does not reflect well on the business. On the other hand, automate AI-based contact centers rely on powerful NLP engines to interpret customer complaints, map the frequency of complaints, and streamline the processes. As a result, the support provided by banking contact centers becomes more accurate and reliable.
Stronger relationships: Using machine learning capabilities, the automated contact center analyses each interaction with customers to create their profiles. These profiles help the contact center agents or automated system be more personalized and effective with each successive conversation. In addition, the improvements in terms of greetings, language, tonality, and minute nuances reduces the monotony of interactions and make the bank more humane (ironically) for customers.
Banks work with highly commoditized and barely distinguished product portfolios. Therefore, the constant quest is to create an edge via service delivery experience. AI-powered contact centers are not only about managing the volume of customer queries and optimizing the operation cost. It enables banks to impact customers through an outstanding experience and lead in a highly competitive space.
The article has been written by Dr Rashi Gupta, Chief Data Scientist and Co-Founder, Rezo.ai