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  "documentTitle": "The age of AI: Banking’s new reality",
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      "text": "We also used a combination of expert judgement and generative AI itself (GPT-4). We started by identifying which of the granular tasks require intensive use of language. Then, we assessed in which way the task requires the use of interpersonal or cognitive skills to be resolved. This enabled us to understand whether generative AI could automate a task or augment the employee's skills.",
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      "text": "We tagged each task and the time employees spend in performing it into one of four categories: High potential for automation, high potential for augmentation, low potential, or no language tasks. We analyzed data for 2.7 million banking employees in the US as well as the 170 roles and 3,500 tasks they perform. This enabled us to assess the potential of generative AI across various job roles.",
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      "text": "Assessing generative AI's impact on productivity, Accenture conducted extensive research on the impact of generative AI across industries. We used data from the US Bureau of Labor Statistics and the Occupational Information Network to analyze descriptions of 900 occupations across industries in the US, the 19,000 tasks they perform, and the time employees spend on each of those. This allowed us to understand the likely impact of generative AI on labor productivity.",
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      "text": "Our assessment of generative AI's impact on banking staff expenses was based on an analysis of over 200 language-related tasks, using data from the Bureau of Labor statistics. We linked these tasks to various banking roles and evaluated the potential for task automation and augmentation in different occupational categories, leading to insights on possible productivity gains across diverse roles in the banking sector.",
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      "text": "Assessing generative AI's impact on banking financials\nTo explore the influence of generative AI in the banking sector, we conducted a comprehensive analysis using financial data from 150 of the largest banks worldwide. This data, sourced from S&P Capital IQ, spanned a 12-month period ending September 2023.",
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      "text": "The estimation of generative AI's effects on revenue generation was informed by insights gleaned from expert consultations and relevant case studies. Our assumptions included expected improvements in various financial metrics related to lending, deposit rates and other banking revenues. Specifically, we considered the impact of generative AI on revenue streams such as wealth and asset management, as well as service charges.",
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