IEEE Guide for Large-Scale Financial Risk Management Models
IEEE Std 3410-2025
contributor author | IEEE - The Institute of Electrical and Electronics Engineers, Inc. | |
date accessioned | 2025-09-30T23:07:55Z | |
date available | 2025-09-30T23:07:55Z | |
date copyright | 18 July 2025 | |
date issued | 2025 | |
identifier other | 11083718.pdf | |
identifier uri | http://yse.yabesh.ir/std;jsein=autho162/handle/yse/348475 | |
description abstract | This 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. | |
language | English | |
publisher | IEEE - The Institute of Electrical and Electronics Engineers, Inc. | |
title | IEEE Guide for Large-Scale Financial Risk Management Models | en |
title | IEEE Std 3410-2025 | num |
type | standard | |
page | 26 | |
tree | IEEE - The Institute of Electrical and Electronics Engineers, Inc.:;2025 | |
contenttype | fulltext | |
subject keywords | financial risk management | |
subject keywords | large-scale financial risk management models | |
subject keywords | fine-tuning | |
subject keywords | pre-training | |
subject keywords | swift adaptation | |
subject keywords | iteration. | |
identifier DOI | 10.1109/IEEESTD.2025.11083718 |