Banks that move quickly to scale generative AI across their organizations could increase their revenues by up to 600 bps in three years, according to Accenture research.

Using publicly available employee data, Accenture analysed banking tasks to estimate how generative AI could impact bank employees’ time by function and then modeled the financial implications for banks over three years, using existing financial data from more than 150 large banks globally, including public and private sector banks in India.

The analysis found that banks which effectively adopt and scale generative AI could increase employee productivity by up to 30%, streamlining numerous language-related tasks.

Operating income could increase by around 20%, while return on equity levels could rise by 300 bps. By helping banks operate more efficiently, the technology could lead to 1%-2% in cost savings, with cost- to-income ratios declining by up to 400 bps.

The report further revealed that generative AI could help evolve the 20 largest roles across banks. These roles fall into three categories:

Roles with a high potential for automation: 41% of all banking occupations have a high potential for automation. Roles that primarily involve collecting and processing data could greatly benefit from automation as their routine tasks could be supported by generative AI. This could improve speed and accuracy, reduce costs and relieve employees of the more tedious aspects of their jobs.

Roles with a high potential for augmentation: 34% of bank employees whose work involves a high measure of judgement, including credit analysts and relationship managers, could be empowered by generative AI tools.

Roles that could potentially benefit equally from automation and augmentation: 25% of all bank employees will similarly benefit from both automation and augmentation, including customer service agents who spend time responding to inquiries, explaining services and preparing documentation.

To carry out the research, Accenture used data from the US Bureau of Labor Statistics and the Occupational Information Network to analyse 2.7 million banking employees in the US as well as the 170 roles and 3,500 tasks they perform to assess the impact of generative AI on labour productivity.

Accenture tagged each task and the time employees spend in performing it in one of four categories: high potential for automation, high potential for augmentation, low potential, or no language tasks.