The 20th anniversary edition of the Capgemini Research Institute’s World Retail Banking Report, published today, reveals 80% of retail bank executives believe that generative AI represents a significant leap in advancing AI technology. However, only 6% of retail banks are ready with a roadmap for enterprise-wide AI-driven transformation at scale.
As a result of macroeconomic uncertainty, many retail banks are being forced to make strategic decisions to navigate challenges to their existing business models. Productivity and efficiency dominated the priority list of the bank leaders surveyed. When it comes to technology, 70% of bank CXOs plan to increase investment in digital transformation by up to 10% in 2024. Yet, the report finds that banks are not ready to embrace and scale intelligent transformation, which involves the strategic application of advanced technologies like AI, machine learning and gen AI to drive innovation and efficiency.
Banks Ill-Prepared for Intelligent Banking
For this report, Capgemini evaluated 250 retail banks across diverse business and technology parameters to understand their infrastructure data maturity and commitment to artificial intelligence. It found most banks are ill-prepared to thrive in an intelligent banking future. Globally, only 4% of retail banks achieved a high score on business commitment and technology capabilities, while 41% scored average, indicating a widespread lack of readiness to embrace and effectively implement intelligent transformation. Regional disparities further underscore this issue. In North America, 27% of banks displayed low readiness, followed by Europe with 31%, and Asia-Pacific (APAC) exhibiting a significant lag, with 48% of banks scoring low. Focusing on intelligent solutions, that are embedded with AI-driven capabilities, will allow banks to navigate ongoing structural challenges, ultimately ensuring sustainable growth. However, success must be measurable: among those surveyed, just 6% of banks have established key performance indicators (KPIs) to measure AI impact and continuous monitoring. More than 60% of banks are still identifying and developing KPIs, while 26% of banks that have already set up some KPIs are not measuring them. According to the report banks risk succumbing to “generative AI silent failure” due to the delayed realization of suboptimal results and outcomes from their experiments with the technology. For instance, just 2% of executives indicate they are regularly tracking the business impact KPIs of their generative AI performance. In addition, 39% of executives express dissatisfaction with the outcomes of their AI use cases further reinforcing this disconnect. To combat this, the study suggests banks set up an AI observatory to track, monitor, and report AI and generative AI real impact, when implemented at scale. “One year after generative AI cemented itself as a core boardroom conversation, we are seeing how banks risk becoming technological laggards if they aren’t rapidly adopting solutions and preparing to take advantage of its capabilities,” said Nilesh Vaidya, Global Industry Head of Retail Banking and Wealth Management at Capgemini. “Generative AI can have a lighthouse effect when used responsibly and wisely across operations. There is also a need for increased efforts on making gen AI explainable and appropriately transparent. The time to act is now to establish practices that build much-needed trust and customer intimacy. Success will come down to developing a roadmap that balances hype with a pragmatic, traceable and measurable approach.”
