Trust Building and Credit Reporting with Big Data in the Digital Age

Wensheng Peng () and Feng Zhu ()
Additional contact information
Wensheng Peng: China International Capital Corporation Limited
Feng Zhu: Luohan Academy

A chapter in The Palgrave Handbook of Technological Finance, 2021, pp 809-836 from Springer

Abstract: Abstract Trust is the foundation of modern commerce and finance, much more so in the digital age where complete strangers seek to make deals on digital platforms. While trust building, including credit reporting, has a long tradition, the rise of digital economy, big data analytics and new business models centering around data have brought exciting opportunities and new challenges. This chapter reviews a number of existing credit reporting models in the major economies, focusing on China’s trust building experiences and on credit reporting in the digital age. To facilitate online trade and financial transactions, new efforts have been made to develop trust building mechanisms based on information sharing that goes beyond the traditional realm of credit scoring. The new approach attaches great importance to integrating technology with business ecosystems and serving the real economy; a broadening range of data sources; and the use of alternative data and AI methods to assess and manage risks to support key business decisions. Digital technologies have played a central role, and in China, tech companies have pioneered a growing number of promising trust building practices that have supported the rise of digital platforms and the sharing economy.

Keywords: Algorithmic fairness; Baihang credit; Big data analytics; Credit scoring; Credit reporting; Digital footprints; Privacy; Sesame credit; Trust building (search for similar items in EconPapers)
Date: 2021
References: Add references at CitEc
Citations: View citations in EconPapers (1)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-65117-6_29

Ordering information: This item can be ordered from
http://www.springer.com/9783030651176

DOI: 10.1007/978-3-030-65117-6_29

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().