HSBC, one of the world’s largest banks, is leveraging artificial intelligence (AI) to enhance customer experiences and speed up complex analytics.
The first use case focuses on personalizing the customer experience. HSBC uses AI and machine learning to analyze transactional data and understand the spending and saving patterns of its retail and personal banking customers. This data is then used to provide personalized insights such as wealth portfolio views, gains and losses, and insurance protection levels. The bank has also launched a budget feature on its mobile app that uses AI to track and categorize spending patterns.
The second use case involves the acceleration of complex analytics. HSBC has launched its PayMe application, aimed at reinventing mobile payments. To overcome challenges with legacy systems and data processing, HSBC has adopted Azure Databricks and Delta Lake. These tools provide real-time, anonymized production data to data science teams, centralizing the analytics process. This has resulted in faster data pipelines, improved engagement levels, and the deployment of predictive data models.
These initiatives demonstrate how AI can be used to improve customer service and streamline operations in the banking sector.