银行风险管理中的机器学习-简要概述

Hafsa Shakeel, Hana Sharif, Faisal Rehman, Bilal Rasool, Azher Mahmood, Hadia Maqsood, Hina Kirn, C. Ali, Muhammad Bilal
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引用次数: 0

摘要

基于计算机的智能在商业应用中的应用正在增长。以前已经执行了许多安排,还有更多的安排正在被发现。全球金融危机凸显了银行风险管理的重要性,人们一直强调如何感知、评估和承担风险。在很大程度上,该行业专注于改善金融投注和当前的困难。本文展示了人工智能(AI)在银行风险、杂货店风险、支票卡风险和现金风险管理中的应用。无论如何,这似乎与正在进行的以高管赌博和人工智能为中心的商业部门层面的讨论没有多大关系。在银行风险的不同领域,高管们可能会从调查如何在任何时候将人工智能应用于个别问题中看到显著的优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Machine Learning in Banking Risk Management - A Brief Overview
The use of computer-based intelligence in business applications is growing. There have been numerous arrangements previously executed, and numerous more are being discovered. The global financial crisis has heightened the significance of risk management in banks, and there has been a persistent emphasis on how risks are perceived, evaluated, and taken. For the most part, the industry has concentrated on the improvement in financial bets and current difficulties. This paper has shown that the use of artificial intelligence (AI) in the administration of banking risk, grocery store risk, check card risk, and cash risk has been found. In any case, it doesn't appear to have much to do with the ongoing business sector-level discussions centered on both executive gambling and artificial intelligence. In different regions of bank risk, executives might see a significant advantage from an investigation of how, at any point, AI can be applied to individual issues.
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