Impact Study

Power your banking value chain with AI/ML at scale

In a world of rapidly advancing technology, artificial intelligence (AI) and machine learning (ML) are essential to a bank's growth strategy. 


McKinsey cautions that banks that do not prioritise AI adoption are at risk of being overtaken by competition and abandoned by customers who are looking for highly personalised experiences. The consulting firm cites four key trends that are leading banks to incorporate AI/ML into their core strategy and operations:

  • Demanding customer expectations driven by digital banking improvements
  • Competition from leading banks’ use of AI/ML solutions
  • The disintermediation of traditional financial services by digital ecosystems
  • Encroachment of big tech players into or adjacent to traditional financial markets and business models.

Forward-looking financial institutions are eager to integrate AI/ML into their operations and leverage rapidly evolving AI/ML tools to more quickly and efficiently deliver hyper-personalized products and services to customers, improve operational efficiency, increase revenue, and drive innovation.

International Data Corporation (IDC) forecasts that the banking and retail industries are set to deliver the most significant investments in AI/ML over the period of 2022-2026, and are projected to account for roughly 25% of all AI spending worldwide.

As in any significant transformation journey, banks face a number of considerations and challenges along the way. First, they’re increasingly required to carefully balance the benefits of innovation brought forward by AI/ML solutions, alongside new regulation designed to ensure fair treatment of customers.

Additional challenges in banks’ AI/ML journey include skills gaps and the ability to effectively scale AI/ML capabilities beyond pilots and singular use cases.

According to Organisation for Economic Co-operation and Development (OECD) data, AI applications are increasingly evident across a breadth of financial market activities. However, such use cases are approached in silos leaving an opportunity for firms to embed AI/ML across the end-to-end value chain. 

Download this Finextra Impact Study, produced in association with Amazon Web Services (AWS), to learn more.

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