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Research on Financial Network Loan Risk Control Model based on Prior Rule and Machine Learning Algorithm

Published: 12 April 2019 Publication History

Abstract

With the development of big data and artificial intelligence, it is more and more common to apply machine learning algorithms to financial risk control. However, the current research work still lack the integration of prior rule knowledge and big data algorithms. This paper proposes a novel risk control model, which firstly uses the financial industry's prior rules to conduct risk control identification, and rapid screens data of rise that is easy to judge. Then, we use machine learning algorithms such as SVM to train and learn financial big data. The combination of the two makes full use of prior risk control support for fast and effective data judgment and machine learning for efficient and real-time monitoring of financial dynamic changes.

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  1. Research on Financial Network Loan Risk Control Model based on Prior Rule and Machine Learning Algorithm

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    ICMAI '19: Proceedings of the 2019 4th International Conference on Mathematics and Artificial Intelligence
    April 2019
    232 pages
    ISBN:9781450362580
    DOI:10.1145/3325730
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

    In-Cooperation

    • Southwest Jiaotong University
    • Xihua University: Xihua University

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 12 April 2019

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    Author Tags

    1. Financial Technology
    2. Machine Learning
    3. Risk Control
    4. Rule Model

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