Abstract

This case study focuses upon HSBC’s efforts to solve a looming strategic problem by leveraging new data analytics and generative artificial intelligence (AI). HSBC currently has a dominant position in Hong Kong, counting over 5.5 million of Hong Kong’s 7.3 million residents as its clients. Such dominance masks a long-term problem, however. With a growing number of its younger customers choosing to conduct their banking transactions via digital means, HSBC has been starting to lose a growing number of millennials to new, online-only competitors (i.e., digital banks). While HSBC has been generating the bulk of its profits from older, more established clients, millennials represent its future.

In particular, this case describes the challenges faced by two executives at HSBC Hong Kong, Jiahao Teo, HSBC's Managing Director, Global Head of Data, Analytics & CRM, GPB & Wealth, North Asia WPB and Amy Hui, Head of Personal Banking and Customer Lifecycle Management, WPB HK. Jiahao had been instrumental in developing HSBC’s now significant data collection and analytics machinery. Jiahao and Amy needed to understand the pros and cons of their technology resources and determine the best ways to deploy them to attain the objectives of HSBC’s new CLCM strategy – to retain and attract millennials to ensure that HSBC will continue to dominate Hong Kong’s lucrative market.

Learning Objectives

After studying the case, students are expected to be able to:

1.       Understand the practical aspects of Customer Lifecycle Management and why CLCM was an important strategic initiative for HSBC in Hong Kong.

2.       Elaborate on the importance of customer segmentation, targeting and positioning.

3.       In business analytics and data science courses, gain familiarity with algorithmic segmentation, leveraging clustering algorithms using the synthetic data provided by HSBC to gain bottom-up insights into different customer segments.

4.       Assess the significant potential of Artificial Intelligence (AI) within the banking sector, as well as the inherent risks in utilizing AI.