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证券类资产管理公司监管科技的演进路径研究 被引量:1

The Evolution Path of Securities Asset Management Companies’ RegTech
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摘要 监管科技在资产管理公司的交易监控与合规风控方面的作用重大,能够提高资产管理业务效率、保证数据精准。监管科技与其他技术一样需要持续升级,目前我国资产管理公司基于成本和其他管理等因素而选择不升级监管科技,导致合规问题频发。本文考虑资产管理公司之间的竞争性,通过构建证券类资产管理公司之间的对称演化博弈模型,分析资产管理公司监管科技优化升级的动态演进路径以及影响因素,并利用MATLAB进行仿真模拟。研究发现,证券类资产管理公司的数据收集能力、风险识别水平、公司治理能力、预算约束、技术升级成本和被处罚力度,是影响公司进行监管科技优化升级策略选择的重要因素。建议证券类资产管理公司加快监管科技的优化升级,进一步提升数据收集能力、风险识别水平及公司治理能力,合理分配预算和提高监管科技运用能力,以提高业务效率和降低合规风险。 RegTech plays a significant role in transaction monitoring and compliance risk control of asset management companies, which can improve the efficiency of asset management business and ensure the accuracy of data. RegTech needs continuous upgrading as same as other technologies. At present, Chinese asset management companies choose not to upgrade RegTech based on the cost and other management factors, resulting frequent compliance problems. Considering the competition among asset management companies, this paper analyzes the dynamic evolution path and influencing factors of the optimization and upgrading of RegTech of asset management companies by constructing a symmetric evolutionary game model between two securities asset management companies,and uses MATLAB to conduct simulation. It is found that data collection ability, risk identification level, corporate governance ability, budget constraints, technology upgrading cost and punishment intensity are the important factors that affect securities asset management companies’ choices of RegTech optimization and upgrading strategy. In order to improve business efficiency and reduce compliance risks, it is suggested that they speed up the optimization and upgrading of RegTech, further improve data collection ability, risk identification level and corporate governance ability,allocate budget reasonably and improve the application ability of RegTech.
作者 戴德宝 周丹 DAI Debao;ZHOU Dan
出处 《金融监管研究》 CSSCI 北大核心 2021年第12期92-111,共20页 Financial Regulation Research
基金 国家自然科学基金重点项目“互联网+大数据环境下运营管理理论与方法”(项目编号:72032001) 教育部人文社会科学研究规划基金项目“网络学习动态过程发散与收敛状态实证研究”(项目编号:17YJA880014)的资助。
关键词 资产管理公司 监管科技 优化升级 演化博弈 Asset Management Company RegTech Optimization and Upgrading Evolutionary Game
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