|
|
|
| Financial Security Intelligence Analysis Based on Blockchain Driven Trustable Big Data and AI |
| Ding Xiaowei and Su Xinning |
| School of Information Management, Nanjing University, Nanjing 210023 |
|
|
|
|
Abstract Financial security is a vital component of national security. The 2008 financial tsunami endangered the whole world and is a valuable research sample of financial security to this day. There are many causes for the financial crisis. This study reflects on the 2008 financial crisis from an intelligence analysis perspective. From a data and information point of view, incomplete, imperfect, inaccurate, fragmented, untrustworthy, and inadequate data are the causes of the crisis; whereas data and information silos hinder the intelligent analysis of financial risk and hamper the detection of early warning signs, all of which contributed to the crisis. From a modeling and methodology perspective, input data quality affects model and output quality (GIGO—garbage in, garbage out). The lack of efficient integration between human and machine intelligence is also one of the important causes for the lack of early risk warning signs and the inability to resist crises. Ten years later, we now have blockchain, big data, and artificial intelligence. Will we do better in another financial crisis? This study calls for the construction of a new foundational financial information infrastructure. On this basis, the concepts of trustworthy blockchain-based big data, artificial intelligence, and financial (big data) intelligence analysis are put forward. Equipped with a new foundational financial information infrastructure architecture and a new intelligence analysis based on trustworthy big data and artificial intelligence, human beings are expected to improve their prevention and control of financial risk, early detection of possible financial crises, and maintenance of financial security.
|
|
Received: 26 June 2019
|
|
|
|
1 新华社. 习近平: 金融活经济活, 金融稳经济稳[EB/OL]. (2017-04-26) [2019-04-25]. http://www.xinhuanet.com/fortune/2017-04/26/c_1120879349.htm.
2 人民网. 习近平在中国共产党第十九次全国代表大会上的报告[EB/OL]. (2017-10-28) [2019-04-25]. http://cpc.people.com.cn/n1/2017/1028/c64094-29613660.html.
3 新华社. 习近平: 深化金融改革, 促进经济和金融良性循环健康发展[EB/OL]. (2017-07-15) [2019-04-25]. http://www.xinhuanet.com/fortune/2017-07/15/c_1121324747.htm.
4 任福兵. 美国次贷危机中金融情报缺失分析[J]. 现代情报, 2008, 28(12): 201-204.
5 彭靖里, Jeanne·杨, 陆家康. 国际金融情报的兴起与发展及其给我们的启示[J]. 竞争情报, 2009, 5(2): 8-14.
6 陈福顺. 金融危机十周年回眸——基于行为金融学视角分析[J]. 时代金融, 2019(7): 51-52.
7 余思佳. 2008年金融危机的原因及其后果分析[J]. 科技广场, 2016(11): 154-157.
8 吴晨生, 李辉, 付宏, 等. 情报服务迈向3.0时代[J]. 情报理论与实践, 2015, 38(9): 1-7.
9 高金虎. 论国家安全情报工作——兼论国家安全情报学的研究对象[J]. 情报杂志, 2019, 38(1): 1-7.
10 傅畅, 宋佳庆. 一种基于文本聚类的web军事情报挖掘系统设计与实现[J]. 中国电子科学研究院学报, 2015, 10(5): 541-545.
11 陈传夫, 马浩琴. 图书情报学现实研究中科学方法应用的调查分析——以2010年的期刊论文为样本[J]. 图书馆论坛, 2011, 31(6): 32-37, 67.
12 马费成. 在改变中探索和创新[J]. 情报科学, 2018, 36(1): 3-4.
13 李志男, 孟潇, 杨海丽, 等. 基于信息融合模型的科技情报质量控制研究[J]. 情报杂志, 2019, 38(1): 54-60.
14 沈固朝. 情报预测和预警研究要关注信号分析[J]. 图书情报工作, 2009, 53(20): 10.
15 包昌火. 对我国情报学研究中三个重要问题的反思[J]. 图书情报知识, 2012(2): 4-6.
16 李广建, 江信昱. 不同领域的情报分析及其在大数据环境下的发展[J]. 图书与情报, 2014(5): 7-12, 19.
17 苏新宁. 大数据时代情报学学科崛起之思考[J]. 情报学报, 2018, 37(5): 451-459.
18 经济学家(Economist)[EB/OL]. [2019-04-25]. https://www.econ omist.com/finance-and-economics/2009/12/03/silo-but-deadly.
19 如何破局大数据的“孤岛困境”?[EB/OL]. (2017-11-24) [2019-04-25]. https://www.sohu.com/a/206335246_617676.
20 工信部发布《中国区块链技术和应用发展白皮书》[EB/OL]. (2018-02-27) [2019-04-07]. https://www.sohu.com/a/224324631_711789.
21 中国信通院. 中国信通院发布《区块链白皮书(2018年)》, 可信区块链媒体特设组同期成立[EB/OL]. (2018-09-05 [2019-04-25]. http://www.catr.cn/xwdt/ynxw/201809/t20180905_184619.htm.
22 工信部信软司: 从四方面推进区块链相关工作[EB/OL]. [2019-12-16]. http://blockchain.people.com.cn/n1/2019/0410/c417685-31022620.html.
23 中国信通院: 2018区块链白皮书[EB/OL]. (2018-09-05) [2019-04-25]. https://www.chainnode.com/doc/2599.
24 NakamotoS. Bitcoin: A peer-to peer electronic cash system[EB/OL]. [2019-04-25]. https://bitcoin.org/bitcoin.pdf.
25 人民日报海外版: 让黑天鹅飞不起 灰犀牛冲不动[EB/OL]. [2019-12-15]. https://baijiahao.baidu.com/s?id=1623396649406 274447&wfr=spider&for=pc.
26 罗伯特·克拉克.情报分析: 以目标为中心的方法[M]. 马忠元, 译. 北京: 金城出版社, 2013.
27 唐明伟, 苏新宁, 肖连杰. 面向大数据的情报分析框架[J]. 情报学报, 2018, 37(5): 467-476.
28 李广建, 江信昱. 论计算型情报分析[J]. 中国图书馆学报, 2018, 44(2): 4-16.
29 沈固朝. 信号分析: 竞争情报研究的又一重要课题[J]. 图书情报工作, 2009, 53(20): 11-14, 59. |
|
|
|
