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IEEE Std 3410-2025

contributor authorIEEE - The Institute of Electrical and Electronics Engineers, Inc.
date accessioned2025-09-30T23:07:55Z
date available2025-09-30T23:07:55Z
date copyright18 July 2025
date issued2025
identifier other11083718.pdf
identifier urihttp://yse.yabesh.ir/std;jsein=autho162/handle/yse/348475
description abstractThis guide aims to establish a standardized reference framework and technical protocols for implementing large-scale artificial intelligence (AI) models in financial risk management. It serves as an essential guidance for financial institutions seeking to build, iterate, utilize their large-scale AI models for managing financial risks. The guide offers best practice on integrating various data knowledge, including feature space, sample, and model knowledge, into large-scale financial risk management models. It also provides strategic guidance on designing pre-training process, fine-tuning process, and evaluation methodologies to augment the feature and risk comprehensive capabilities of the large-scale models. Furthermore, it elucidates on the swift adaptation of the large models to various financial lending risk scenarios and the iterative process of the large-scale models.
languageEnglish
publisherIEEE - The Institute of Electrical and Electronics Engineers, Inc.
titleIEEE Guide for Large-Scale Financial Risk Management Modelsen
titleIEEE Std 3410-2025num
typestandard
page26
treeIEEE - The Institute of Electrical and Electronics Engineers, Inc.:;2025
contenttypefulltext
subject keywordsfinancial risk management
subject keywordslarge-scale financial risk management models
subject keywordsfine-tuning
subject keywordspre-training
subject keywordsswift adaptation
subject keywordsiteration.
identifier DOI10.1109/IEEESTD.2025.11083718


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