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1 – 2 of 2Ming Qi, Jiawei Zhang, Jing Xiao, Pei Wang, Danyang Shi and Amuji Bridget Nnenna
In this paper the interconnectedness among financial institutions and the level of systemic risks of four types of Chinese financial institutions are investigated.
Abstract
Purpose
In this paper the interconnectedness among financial institutions and the level of systemic risks of four types of Chinese financial institutions are investigated.
Design/methodology/approach
By the means of RAS algorithm, the interconnection among financial institutions are illustrated. Different methods, including Linear Granger, Systemic impact index (SII), vulnerability index (VI), CoVaR, and MES are used to measure the systemic risk exposures across different institutions.
Findings
The results illustrate that big banks are more interconnected and hold the biggest scales of inter-bank transactions in the financial network. The institutions which have larger size tend to have more connection with others. Insurance and security companies contribute more to the systemic risk where as other institutions, such as trusts, financial companies, etc. may bring about severe loss and endanger the financial system as a whole.
Practical implications
Since other institutions with low levels of regulation may bring about higher extreme loss and suffer the whole system, it deserves more attention by regulators considering the contagion of potential risks in the financial system.
Originality/value
This study builds a valuable contribution by examine the systemic risks from the perspectives of both interconnection and tail risk measures. Furthermore; Four types financial institutions are investigated in this paper.
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Keywords
Amber L. Cushing and Giulia Osti
This study aims to explore the implementation of artificial intelligence (AI) in archival practice by presenting the thoughts and opinions of working archival practitioners. It…
Abstract
Purpose
This study aims to explore the implementation of artificial intelligence (AI) in archival practice by presenting the thoughts and opinions of working archival practitioners. It contributes to the extant literature with a fresh perspective, expanding the discussion on AI adoption by investigating how it influences the perceptions of digital archival expertise.
Design/methodology/approach
In this study a two-phase data collection consisting of four online focus groups was held to gather the opinions of international archives and digital preservation professionals (n = 16), that participated on a volunteer basis. The qualitative analysis of the transcripts was performed using template analysis, a style of thematic analysis.
Findings
Four main themes were identified: fitting AI into day to day practice; the responsible use of (AI) technology; managing expectations (about AI adoption) and bias associated with the use of AI. The analysis suggests that AI adoption combined with hindsight about digitisation as a disruptive technology might provide archival practitioners with a framework for re-defining, advocating and outlining digital archival expertise.
Research limitations/implications
The volunteer basis of this study meant that the sample was not representative or generalisable.
Originality/value
Although the results of this research are not generalisable, they shed light on the challenges prospected by the implementation of AI in the archives and for the digital curation professionals dealing with this change. The evolution of the characterisation of digital archival expertise is a topic reserved for future research.
Details