通过大数据和人工智能驱动的客户洞察和风险分析提升金融服务

Tianyi Yang, Qi Xin, Xiaoan Zhan, Shikai Zhuang, Huixiang Li
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引用次数: 0

摘要

文章讨论了大数据和人工智能(AI)技术在金融领域的整合,重点关注定价模型的监督学习,以提高客户识别和定位能力。文章详细介绍了客户特征系统的构建,包括借记卡和信用卡交易、贷款申请和在线行为等属性。通过利用人工智能,金融机构旨在准确描述客户特征、促进消费和改善价格管理,最终帮助做出风险管理和贷款审批决策。文章还介绍了金融风险监控和信用风险建模中的机器学习方面的相关工作,重点介绍了这些领域的进步和挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ENHANCING FINANCIAL SERVICES THROUGH BIG DATA AND AI-DRIVEN CUSTOMER INSIGHTS AND RISK ANALYSIS
The article discusses the integration of big data and artificial intelligence (AI) technologies in the financial sector, focusing on supervised learning for pricing models to enhance customer identification and targeting. It details the construction of customer feature systems, including attributes like debit and credit card transactions, loan applications, and online behavior. By leveraging AI, financial institutions aim to accurately profile customers, boost consumption, and improve price management, ultimately aiding risk management and loan approval decisions. The article also covers related work in financial risk monitoring and machine learning in credit risk modeling, highlighting advancements and challenges in these areas.
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