The acceleration of deep learning ignited the big bang of artificial intelligence research. This sparked the ‘iPhone moment’ for AI: ChatGPT, a large language model powered by a supercomputer, that reached 100 million users in just two months. Its remarkable capabilities have captured the world’s imagination. Generative AI is a new computing platform, comparable to the impact of the PC, internet, and mobile cloud. Accelerated computing and AI have fully integrated and arrived.
Generative AI systems have far-reaching uses, such as for financial services. It will certainly be used to create better applications, like chatbots, to improve customer service, but the true power will come from its ability to ingest a wide variety of unstructured data and synthesize answers to natural language queries. GenAI is a smart language-powered interface to complex data, and other analytical and AI capabilities. Everyone can be a researcher, knowledge worker, or coder. Urgency in its implementation is crucial due to the transformative, disruptive power and potential of these technologies.
But what are the specific opportunities and risks of generative AI for financial centers and services? What are the latest implications, trends, strategies and challenges? In this Research Topic, we call on papers for the following topics:
• Which use cases in FSI will be addressed by GenAI and what will the impact be? How will this change financial services, financial markets, and financial centers? How will different segments of FSI, like banking, insurance, and investments adopt it?
• How will sustainable finance, ESG, and climate risk, be addressed using GenAI and foundation models?
• Which other foundation models will we see in FSI besides natural language, for example, foundation models built on payment data or geospatial data?
• How will LLMs and GenAI be implemented, customized and how will adoption, flexibility, agility, and model performance be increased and how will cost, efficiency, and latency be decreased?
• Will we see more models in the cloud or rather in hybrid, on-prem set-ups? Which role will customization play? What will the optimal infrastructure, platforms, stacks, data processing technology and MLOps platforms look like?
• How will Trustworthiness, Security, Safety, Guardrails, Explainability and AI Governance be addressed? What will regulatory sandboxes look like? How will automated GenAI assessments and certification processes be established?
• How will large models be supervised and monitored? How will financial supervisors, regulators and central banks leverage those technologies for themselves and how will they monitor/supervise FSI activities?
• What will Avatars and Digital Assistants look like that are powered by LLMs?
• How will talents and startups develop and how will job profiles change?
Jochen Papenbrock is employed by NVIDIA and Imed Zoutini is employed by Google. All other Topic Editors declare no competing interests with regard to the Research Topic subject.
Keywords:
Large Language Models, ChatGPT, Generative AI, financial service industry, FSI
Important Note:
All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
Generative AI systems have far-reaching uses, such as for financial services. It will certainly be used to create better applications, like chatbots, to improve customer service, but the true power will come from its ability to ingest a wide variety of unstructured data and synthesize answers to natural language queries. GenAI is a smart language-powered interface to complex data, and other analytical and AI capabilities. Everyone can be a researcher, knowledge worker, or coder. Urgency in its implementation is crucial due to the transformative, disruptive power and potential of these technologies.
But what are the specific opportunities and risks of generative AI for financial centers and services? What are the latest implications, trends, strategies and challenges? In this Research Topic, we call on papers for the following topics:
• Which use cases in FSI will be addressed by GenAI and what will the impact be? How will this change financial services, financial markets, and financial centers? How will different segments of FSI, like banking, insurance, and investments adopt it?
• How will sustainable finance, ESG, and climate risk, be addressed using GenAI and foundation models?
• Which other foundation models will we see in FSI besides natural language, for example, foundation models built on payment data or geospatial data?
• How will LLMs and GenAI be implemented, customized and how will adoption, flexibility, agility, and model performance be increased and how will cost, efficiency, and latency be decreased?
• Will we see more models in the cloud or rather in hybrid, on-prem set-ups? Which role will customization play? What will the optimal infrastructure, platforms, stacks, data processing technology and MLOps platforms look like?
• How will Trustworthiness, Security, Safety, Guardrails, Explainability and AI Governance be addressed? What will regulatory sandboxes look like? How will automated GenAI assessments and certification processes be established?
• How will large models be supervised and monitored? How will financial supervisors, regulators and central banks leverage those technologies for themselves and how will they monitor/supervise FSI activities?
• What will Avatars and Digital Assistants look like that are powered by LLMs?
• How will talents and startups develop and how will job profiles change?
Jochen Papenbrock is employed by NVIDIA and Imed Zoutini is employed by Google. All other Topic Editors declare no competing interests with regard to the Research Topic subject.
Keywords:
Large Language Models, ChatGPT, Generative AI, financial service industry, FSI
Important Note:
All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.