人工智能深度介入消费金融：动因、风险及防控

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Abstract Despite its rapid development in recent years, consumer finance is confronted with some problems such as high marketing and customer acquisition cost, difficulty in the acquisition of consumption scenarios, and poor risk management. With the in-depth development of artificial intelligence technology, AI technology displays obvious advantages in consumer finance, and is increasingly widely used in intelligent identification, marketing, risk control, customer service, collection and so on. However, the application of artificial intelligence in consumer finance has encountered many risks. Machine learning algorithms result in “black box” and “discrimination” in consumer finance applications. The inevitable “homogenization” of big data results in high data risk. Artificial intelligence may infringe on the privacy and rights of financial consumers. There is a serious shortage of professionals who are proficient in both artificial intelligence and consumer finance. Artificial intelligence presents great challenges to the law and supervision of consumer finance. In this case, in the development of AI-enabled consumer finance, we need to accord priority to researches on the basic disciplines of AI to prevent black box and discrimination at the source. We need to build a data sharing platform based on credit information system to cement the data base of artificial intelligence. We need to put more efforts into the protection of financial consumers' rights and interests, and guard against the technical risks of artificial intelligence applications. We need to attach importance to the comprehensive development of “governments, users, enterprises, universities, and research institutes”, and cultivate inter-disciplinary talents proficient in both artificial intelligence and consumer finance. We need to strengthen supervision over AI-enabled consumer finance, and simultaneously promote “AI governance” and “legal governance”.

Key words： Internet-based consumer finance financial technology artificial intelligence intelligent financial risk financial regulation risk prevention

Received: 16 March 2021

PACS:	DF438
	F832

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CHENG Xue-jun. Artificial Intelligence Deeply Involved in Consumer Finance: Causes, Risks and Prevention[J]. , 2021, 38(3): 67-76.

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https://xb.szu.edu.cn/EN/ OR https://xb.szu.edu.cn/EN/Y2021/V38/I3/67

[1] 黄志凌. 消费金融发展探索[J].中国金融,2016,(11):24-26.
[2] 鄂春林. 互联网消费金融:发展趋势、挑战与对策[J].南方金融,2018,(3):85-92.
[3] 王晓芳. 互联网消费金融的健康发展之路[J].人民论坛,2019,(9):84-85.
[4] 程雪军. 我国互联网消费金融发展:问题、挑战与监管[J].财会月刊,2019,(15):162-170.
[5] 李佳珂. 人工智能对金融创新的积极影响[J].人民论坛,2018,(25):78-79.
[6] 谷政,石岿然.金融科技助力防控金融风险研究[J].审计与经济研究,2020,(1):16-17+11.
[7] 田红艳. 提升金融服务助力消费增长[J].中国金融,2020,(14):24-26.
[8] 陆璐. “FinTech”赋能:科技金融法律规制的范式转移[J].政法论丛,2020,(1):137-148.
[9] 马国旺,李焙尧.人工智能应用、劳动报酬份额与失业率动态关系的实证分析[J].深圳大学学报(人文社会科学版),2021,(2):61-70.
[10] 胡滨,郑联盛,王寿菊.网络借贷的风险及应对之策:基于信用利差的分析[J].社会科学辑刊,2016,(5):92-98.
[11] 尼克. 人工智能简史[M].北京:中国工信出版集团,人民邮电出版社,2018.185.
[12] 尹振涛,程雪军.我国场景消费金融的风险防控研究[J].经济纵横,2019,(3):55-62.
[13] 陶迎春. 技术中的知识问题——技术黑箱[J].科协论坛,2008,(7):54-55.
[14] 张淑玲.破解黑箱:智媒时代的算法权力规制与透明实现机制[J].中国出版,2018,(7):49-53.
[15] Diakopoulos N.Algorithmic Accountability: Journalistic Investigation of Computational Power Structures[J].Digital Journalism,2014,3(3):398-415.
[16] 刘伟. 关于机器人若干重要现实问题的思考[J].人民论坛·学术前沿,2016,(15):35-43.
[17] Bozdag,E.Bias in Algorithmic Filtering and Personalization[J].Ethics&Information Technology,2013.3(15):209-227.
[18] 匡文波. 智能算法推荐技术的逻辑理路、伦理问题及规制方略[J].深圳大学学报(人文社会科学版),2021,(1):144-151.
[19] 卢克·多梅尔.人工智能:改变世界,重建未来[M].赛迪研究院专家组译.北京:中信出版集团,2017.238-241.
[20] Marcia Stepanek.Weblining[J].Bloomberg Businessweek,2000,April 3:26-29.
[21] 仇筠茜,陈昌凤.黑箱:人工智能技术与新闻生产格局嬗变[J].新闻界,2018,(1):28-34.
[22] 姚凯.缺口超500万中国如何补齐人工智能人才短板[N].第一财经日报,2019-07-10(A11).
[23] 谢平,邹传伟,刘海二.互联网金融监管的必要性与核心原则[J].国际金融研究,2014,(8):3-9.
[24] 北大法律信息网.人工智能+法律实务的思考[M].北京:北京大学出版社,2018.125.
[25] 周晓垣.人工智能:开启颠覆性智能时代[M].北京:台海出版社,2018.178-179.
[26] 于孝建,彭永喻.人工智能在金融风险管理领域的应用及挑战[J].南方金融,2017,(9):70-74.
[27] 张晓燕等. 金融科技行业发展与监管[M].北京:经济科学出版社,2018.39-55.
[28] 卜素. 人工智能中的“算法歧视”问题及其审查标准[J].山西大学学报(哲学社会科学版),2019,(4):124-129.
[29] (美)约翰·贝斯特.数字化金融:人工智能、区块链、云计算、大数据与数字文化[M]. 王勇,黄红华等译.北京:中国工信出版集团,人民邮电出版社,2019.193-203.
[30] 腾讯研究院,中国信通院互联网法律研究中心,腾讯AI Lab,腾讯开放平台.人工智能:国家人工智能战略行动抓手[M].北京:中国人民大学出版社,2017.334-335.