Agent AI for Finance
This open access book provides an overview of the current state of financial argument mining and financial text generation, and presents the authors’ thoughts on the blueprint for NLP in finance in the agent AI era. Financial documents contain numerous causal inferences and subjective opinions. In a...
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| Format: | Online |
| Language: | English |
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Springer Nature
2025
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| Online Access: | ONIX_20250813T121456_9783031946875_40 |
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| _version_ | 1863745390790049792 |
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| author | Chen, Chung-Chi Takamura, Hiroya |
| author_browse | Chen, Chung-Chi Takamura, Hiroya |
| author_facet | Chen, Chung-Chi Takamura, Hiroya |
| author_sort | Chen, Chung-Chi |
| collection | Directory of Open Access Books |
| description | This open access book provides an overview of the current state of financial argument mining and financial text generation, and presents the authors’ thoughts on the blueprint for NLP in finance in the agent AI era. Financial documents contain numerous causal inferences and subjective opinions. In a previous book, “From Opinion Mining to Financial Argument Mining” (Springer, 2021), the first author discussed understanding financial documents in a fine-grained manner, particularly those containing opinions. The book highlighted several future directions, such as financial argument mining, multimodal opinion understanding, and analysis generation, and anticipated a lengthy journey for these topics. However, since 2022, ChatGPT and large language models (LLMs) have shown promising advancements, motivating the authors to write this second book on the topic of financial Natural Language Processing (NLP). Agent-based AI systems have been widely discussed since the advent of LLMs. This book aims to equip researchers and practitioners with the latest methodologies, concepts, and frameworks for developing, deploying, and evaluating AI agents with capabilities in multimodal understanding, decision-making, and interaction. It places a special emphasis on human-centered decision-making and multi-agent cooperation in financial applications. The book surveys the current landscape and discuss future research and development directions. Targeting a wide audience, from students to seasoned researchers in AI and finance, this book offers an overview of recent trends in Agent AI for finance. It provides a foundation for students to understand the field and design their research direction, while inviting experienced researchers to engage in discussions on open research questions informed by pilot experimental results. Although this book focuses on financial applications, the discussed concepts and methods can also be applied to other real-world applications by integrating domain-specific characteristics. The authors look forward to seeing new findings and more novel extensions based on the proposed ideas. |
| format | Online |
| id | doab-20.500.12854ir-165872 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | Springer Nature |
| publisherStr | Springer Nature |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1658722025-08-14T05:03:22Z Agent AI for Finance Chen, Chung-Chi Takamura, Hiroya Financial Argument Mining Agent AI Opinion Mining Agent-Based Modeling Retrieval-Augmented Generation Multi-Agent Interaction Data Augmentation Generative AI Opinion Ranking Argument Mining Argument Quality Text Mining FinTech Numeracy thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning thema EDItEUR::K Economics, Finance, Business and Management::KJ Business and Management::KJQ Business mathematics and systems thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQL Natural language and machine translation This open access book provides an overview of the current state of financial argument mining and financial text generation, and presents the authors’ thoughts on the blueprint for NLP in finance in the agent AI era. Financial documents contain numerous causal inferences and subjective opinions. In a previous book, “From Opinion Mining to Financial Argument Mining” (Springer, 2021), the first author discussed understanding financial documents in a fine-grained manner, particularly those containing opinions. The book highlighted several future directions, such as financial argument mining, multimodal opinion understanding, and analysis generation, and anticipated a lengthy journey for these topics. However, since 2022, ChatGPT and large language models (LLMs) have shown promising advancements, motivating the authors to write this second book on the topic of financial Natural Language Processing (NLP). Agent-based AI systems have been widely discussed since the advent of LLMs. This book aims to equip researchers and practitioners with the latest methodologies, concepts, and frameworks for developing, deploying, and evaluating AI agents with capabilities in multimodal understanding, decision-making, and interaction. It places a special emphasis on human-centered decision-making and multi-agent cooperation in financial applications. The book surveys the current landscape and discuss future research and development directions. Targeting a wide audience, from students to seasoned researchers in AI and finance, this book offers an overview of recent trends in Agent AI for finance. It provides a foundation for students to understand the field and design their research direction, while inviting experienced researchers to engage in discussions on open research questions informed by pilot experimental results. Although this book focuses on financial applications, the discussed concepts and methods can also be applied to other real-world applications by integrating domain-specific characteristics. The authors look forward to seeing new findings and more novel extensions based on the proposed ideas. 2025-08-14T05:03:21Z 2025-08-14T05:03:21Z 2025-08-13T10:19:40Z 2025 book ONIX_20250813T121456_9783031946875_40 https://library.oapen.org/handle/20.500.12657/105463 9783031946875 9783031946868 https://directory.doabooks.org/handle/20.500.12854/165872 eng SpringerBriefs in Intelligent Systems open access image/jpeg n/a https://library.oapen.org/bitstream/20.500.12657/105463/1/9783031946875.pdf Springer Nature Springer Nature Switzerland 10.1007/978-3-031-94687-5 10.1007/978-3-031-94687-5 9fa3421d-f917-4153-b9ab-fc337c396b5a 49262363-8e6c-49e4-8509-b7ae4bc42702 035eb3d3-58be-4d02-ab04-98c38679fd23 9783031946875 9783031946868 Springer Nature Switzerland 83 Cham [...] National Institute of Advanced Industrial Science and Technology AIST 10.13039/100009757 open access |
| spellingShingle | Financial Argument Mining Agent AI Opinion Mining Agent-Based Modeling Retrieval-Augmented Generation Multi-Agent Interaction Data Augmentation Generative AI Opinion Ranking Argument Mining Argument Quality Text Mining FinTech Numeracy thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning thema EDItEUR::K Economics, Finance, Business and Management::KJ Business and Management::KJQ Business mathematics and systems thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQL Natural language and machine translation Chen, Chung-Chi Takamura, Hiroya Agent AI for Finance |
| title | Agent AI for Finance |
| title_full | Agent AI for Finance |
| title_fullStr | Agent AI for Finance |
| title_full_unstemmed | Agent AI for Finance |
| title_short | Agent AI for Finance |
| title_sort | agent ai for finance |
| topic | Financial Argument Mining Agent AI Opinion Mining Agent-Based Modeling Retrieval-Augmented Generation Multi-Agent Interaction Data Augmentation Generative AI Opinion Ranking Argument Mining Argument Quality Text Mining FinTech Numeracy thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning thema EDItEUR::K Economics, Finance, Business and Management::KJ Business and Management::KJQ Business mathematics and systems thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQL Natural language and machine translation |
| topic_facet | Financial Argument Mining Agent AI Opinion Mining Agent-Based Modeling Retrieval-Augmented Generation Multi-Agent Interaction Data Augmentation Generative AI Opinion Ranking Argument Mining Argument Quality Text Mining FinTech Numeracy thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning thema EDItEUR::K Economics, Finance, Business and Management::KJ Business and Management::KJQ Business mathematics and systems thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQL Natural language and machine translation |
| url | ONIX_20250813T121456_9783031946875_40 |
| work_keys_str_mv | AT chenchungchi agentaiforfinance AT takamurahiroya agentaiforfinance |