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What are the most promising use cases for generative AI in banking?
But generative AI isn’t suitable for some banking applications.
How should the banking industry prepare for the rise of generative AI?
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About This Report
ChatGPT is the talk of 2023. In the banking industry, generative AI technology has promising use cases in marketing and customer service, and it has the potential to make machine learning applications more accurate and efficient.
What are the most promising use cases for generative AI in banking?
But generative AI isn’t suitable for some banking applications.
How should the banking industry prepare for the rise of generative AI?
Sources
Media Gallery
Executive Summary
ChatGPT, a generative AI-powered conversational chatbot developed by OpenAI, is the talk of 2023. In the banking industry, generative AI will help create marketing images and text, answer customer queries via virtual assistants, and produce data that will make machine learning applications more accurate and efficient.
Where will generative AI have the biggest impact?
Generative AI could revolutionize various verticals within banking. Here's our take on the top four areas where the technology could have the greatest impact.
Retail banking and wealth. The sheer volume of new accounts opened any given day at large financial institutions demands more effective, efficient know-your-customer (KYC) processes. Generative AI can create synthetic data to help train the machine learning algorithms behind KYC. It can also help create more accurate natural language models for virtual assistants.
SMB banking. Beyond enabling more sophisticated virtual assistants, generative AI will help interpret small business loan applications that contain nonnumeric data—business plans, for example.
Commercial banking. Generative AI will speed up back-office tasks in commercial banking, such as answering questions in real time about a customer’s financial performance in complex scenarios. It might also help train forecasting algorithms by augmenting sparse data on business performance under certain economic conditions.
Investment banking and capital markets. Generative AI could help banks stress test balance sheets that contain complex, illiquid financial products. By synthesizing test data on a variety of scenarios, the technology could help make financial stability measures more precise and lower the cost of compliance.
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Table of Contents
Executive Summary
Where will generative AI have the biggest impact?
What are the most promising use cases for generative AI in banking?
But generative AI isn’t suitable for some banking applications.
How should the banking industry prepare for the rise of generative AI?
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