图 书 馆
数据科学于应用金融Data Science for Financial Applications |
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| 课程网址: | http://videolectures.net/kdd2018_hand_data_science/ |
| 主讲教师: | David Hand |
| 开课单位: | 伦敦帝国理工学院 |
| 开课时间: | 2018-09-24 |
| 课程语种: | 英语 |
| 中文简介: |  数据科学的财务应用完美地说明了从主观决策向数据和证据驱动的决策转变的力量。在大约五十年的时间里，整个工业领域发生了彻底的革命。此类应用涉及三个广泛的领域：精算和保险，消费者银行业务和投资银行业务。精算和保险工作是最早采用数据科学思想的人之一，其历史可追溯到很久以前，甚至在计算机发明之前。但是这些领域落后于数据科学技术的最新发展，这意味着应用现代数据分析思想有很大的潜力。消费者银行业务已被描述为数据革命的第一个也是主要的成功案例。可追溯到1960年代，当第一张信用卡发行时，用于分析消费者金融交易的海量数据集的技术推动了数据挖掘和数据科学思想的发展。但是新的模型类型和新的数据源正在为重大发展带来大量机会。在投资银行业务中，经典经济学的“有效市场假设”说，不可能预测金融市场。但这是错误的，尽管几乎是正确的。这意味着有机会使用高级数据分析方法来挖掘传统理论与实际情况之间的微小差距。其他数据科学问题，例如数据质量，道德和安全性，以及对理解模型局限性的需求，在金融应用程序中变得尤为突出。 |
| 课程简介: | Financial applications of data science provide a perfect illustration of the power of the shift from subjective decision-making to data- and evidence-driven decision-making. In the space of some fifty years, an entire sector of industry has been totally revolutionised. Such applications come in three broad areas: actuarial and insurance, consumer banking, and investment banking. Actuarial and insurance work was one of the earliest adopters of data science ideas, dating from long before the term had been coined, and even before the computer had been invented. But these areas have fallen behind the latest advances in data science technology - which means there is considerable potential for applying modern data analytic ideas. Consumer banking has been described as one the first and major success stories of the data revolution. Dating from the 1960s, when the first credit cards were launched, techniques for analysing the massive data sets of consumer financial transactions have driven much of the development of data mining and data science ideas. But new model types, and new sources of data, are leading to a rich opportunity for significant developments. In investment banking the “efficient market hypothesis” of classic economics says that it is impossible to predict the financial markets. But this is false - though very nearly true. That means that there is an opportunity to use advanced data analytic methods to exploit the tiny gap between conventional theory and what actually happens. Other data science issues, such as data quality, ethics, and security, along with the need to understand the limitations of models, become particularly pointed in the context of financial applications. |
| 关 键 词: | 数据科学; 消费者银行业务; 金融交易 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2020-12-09：cjy |
| 最后编审: | 2020-12-09：cjy |
| 阅读次数: | 43 |