Legal review of right to data portability in non-financial personal credit information

2021 ◽  
Vol 34 (3) ◽  
pp. 331-360
Author(s):  
Jae-Mahn Park
2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sachin Banker ◽  
Derek Dunfield ◽  
Alex Huang ◽  
Drazen Prelec

AbstractCredit cards have often been blamed for consumer overspending and for the growth in household debt. Indeed, laboratory studies of purchase behavior have shown that credit cards can facilitate spending in ways that are difficult to justify on purely financial grounds. However, the psychological mechanisms behind this spending facilitation effect remain conjectural. A leading hypothesis is that credit cards reduce the pain of payment and so ‘release the brakes’ that hold expenditures in check. Alternatively, credit cards could provide a ‘step on the gas,’ increasing motivation to spend. Here we present the first evidence of differences in brain activation in the presence of real credit and cash purchase opportunities. In an fMRI shopping task, participants purchased items tailored to their interests, either by using a personal credit card or their own cash. Credit card purchases were associated with strong activation in the striatum, which coincided with onset of the credit card cue and was not related to product price. In contrast, reward network activation weakly predicted cash purchases, and only among relatively cheaper items. The presence of reward network activation differences highlights the potential neural impact of novel payment instruments in stimulating spending—these fundamental reward mechanisms could be exploited by new payment methods as we transition to a purely cashless society.


Author(s):  
Toshiaki Takigawa

ABSTRACT This article examines antitrust issues concerning digital platforms equipped with big data. Recent initiatives by the Japanese competition agency are highlighted, comparing them with those by the USA and EU competition authorities. First examined is whether competition among platforms would result in a select few super platforms with market power, concluding that AI with machine learning has augmented the power of super platforms with strong AI-capability, leading to increased importance of merger control over acquisitions by platforms. Next scrutinized is the argument for utility-regulation to be imposed on super platforms, concluding that wide support is limited to data portability, leaving competition law as the key tool for addressing super platforms, its core tool being the provision against exclusionary conduct, enforcement of which, initially, concerns whether to order super platforms to render their data accessible to their rivals. Passive refusal-to-share data needs to be scrutinized under the essential facility doctrine. Beyond passive refusal, platforms’ exclusionary conduct requires competition agencies to weigh the conduct’s exclusionary effects against its efficiency effects. Finally addressed is exploitative abuse, explaining its relation to consumer protection, concluding that competition law enforcement on exploitative abuse should be minimized, since it accompanies risk of over-enforcement.


2021 ◽  
Vol 45 (3) ◽  
pp. 190-197
Author(s):  
Marlene Barth
Keyword(s):  

Author(s):  
Xiang Zou ◽  
Jinting Zhao ◽  
Yun Tong

This paper focuses on the construction of college students' credit evaluation system and credit risk management under the background of big data. Firstly, based on the 5C approach, this paper evaluates the personal credit of college students from 5 dimensions and 24 indicators, which finally contribute to the establishment of the credit evaluation system for college students. Then, the partial least squares method is used to build the structural equation model to evaluate the effectiveness of the credit evaluation system for college students. According to the in-depth analysis of PSL-SEM, the factors that affect the credit risk of college students are effectively evaluated, and it has contributed to the establishment and improvement of the credit system of college students. Keywords: Personal Credit, Credit Evaluation, Credit Risk, 5C Approach, PLS-SEM.


2018 ◽  
Vol 34 (2) ◽  
pp. 193-203 ◽  
Author(s):  
Paul De Hert ◽  
Vagelis Papakonstantinou ◽  
Gianclaudio Malgieri ◽  
Laurent Beslay ◽  
Ignacio Sanchez

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