As of 2021, China’s population exceeds 1.4 billion people according to United Nations data, which excludes Hong Kong, Macao, and Taiwan. This number makes up approximately one-fifth of the global population, and with the rapid rise in technology in recent years, it can be concluded that they are also one of the largest producers of data. Historically, there were 4 factors of production known to create economic wealth – land, capital, labour and entrepreneurship, but with an increasing global reliance on technology, data (knowledge) is now considered by many to be the fifth factor. Unlike the initial four factors of production, the pricing models for data are opaque with no ownership models truly in place, and ill definitions surrounding sensitivity and the categorization of data. According to many global experts and firms watching the developments with avid interest, China’s crackdown on Big Tech is seen to safeguard one of the world’s most valuable economic resources and is considered to be the new oil. This paper will provide insight into China’s changing data landscape regarding regulations, always linking back to the connection between alternative data availability, collection, and distribution. The content included in this paper has been collected through both publicly available sources as well as through interviews with data experts and proprietary client-only content available through Eagle Alpha’s Data Strategy solution.

Like most forms of ESG analysis, governance analysis has traditionally relied almost exclusively on self-reported information, or metrics derived from self-report information. This reliance on self-reported information is likely even greater when it comes to the topic of governance given that there is a lot of governance data already available. For the most part, companies are obligated to publish a lot of information that is relevant to governance analysis, such as board composition, executive compensation, shareholder rights, and audit and oversight information. Section 1 discusses datasets for analysing Corporate Governance, and the subtopics of the board, pay, ownership and control, and accounting. Section 2 provides a deep dive on the topic of corporate behavior, encompassing the subtopics of business ethics, anti-competitive practices, corruption and instability, financial system instability, and tax transparency. Finally, in Section 3 we explore other alternative data approaches to governance analysis, most notably environmental risks scoring and AI & NLP techniques for governance analysis.

This paper is a compilation of alternative data insights relevant to engineers and data scientists from Eagle Alpha’s vast library of content on the Data Strategy solution. The Data Strategy solution helps our clients to build and innovate their alternative data strategies and discover new opportunities from alternative data. Through our data Strategy advisory services, live workshops, and proprietary content our clients drive alternative data adoption at their firms, increase the ROI on their alternative data initiative, and they mitigate the risks associated with alternative data.OverviewIn this paper we highlight content that ranges from strategic advice from industry veterans to practical insights from engineers and data scientists with experience working with alternative data. The insights reflect Eagle Alpha’s own perspectives, as well as those of highly respected third parties.