scholarly journals Personal Credit and Financial Vulnerability

2021 ◽  
Author(s):  
Adam Gill ◽  
Jacob Turton ◽  
Paul Harrald ◽  
Eleanor Demuth
Keyword(s):  
Cognitive Biases ◽  
Data Sources ◽  
Micro Data ◽  
Financial Vulnerability ◽  
Theoretical Frameworks ◽  
Gambling Industry ◽  
Personal Credit ◽  
Tailored Interventions ◽  
Transient Nature ◽  
Vulnerable Consumers

Rather than a narrow focus on risk of default, this paper advocates for lenders to take a broader data-led approach to tackling the challenges posed by financial vulnerability due to its latent and transient nature. Earlier identification and intervention when customers are experiencing financial hardship may help prevent default. Firstly, we consider how macro and micro data sources, in combination with emerging theoretical frameworks that conceptualise financial vulnerability, could be used by lenders for earlier identification of vulnerable customers. Secondly, we look at tailored interventions that could help financially vulnerable consumers once they have been identified, with passive and active methods inspired by protective efforts currently underway within the gambling industry. Lastly, when consumers do enter the arrears process, we highlight how lenders have a responsibility to help mitigate cognitive biases and promote behaviours that will help consumers escape perpetual debt.

Errors in Surgical Neuropathology and the Influence of Cognitive Biases: The Psychology of Intelligence Analysis

2006 ◽  
Vol 130 (5) ◽  
pp. 613-616 ◽  
Author(s):  
Roger E. McLendon
Keyword(s):  
Decision Making ◽  
Cognitive Psychology ◽  
Medical Decision Making ◽  
Cognitive Biases ◽  
Correct Diagnosis ◽  
Data Sources ◽  
Medical Decision ◽  
Intelligence Analysis ◽  
First Impression ◽  
Decision Making Processes

Abstract Context.—A significant difficulty that pathologists encounter in arriving at a correct diagnosis is related to the way information from various sources is processed and assimilated in context. Objective.—These issues are addressed by the science of cognitive psychology. Although cognitive biases are the focus of a number of studies on medical decision making, few if any focus on the visual sciences. Data Sources.—A recent publication authored by Richards Heuer, Jr, The Psychology of Intelligence Analysis, directly addresses many of the cognitive biases faced by neuropathologists and anatomic pathologists in general. These biases include visual anticipation, first impression, and established mindsets and subconsciously influence our critical decision-making processes. Conclusions.—The book points out that while biases are an inherent property of cognition, the influence of such biases can be recognized and the effects blunted.

The Electronic Hive Mind and Cybersecurity

2019 ◽  
pp. 206-262 ◽  
Author(s):  
Shalin Hai-Jew
Keyword(s):  
Decision Making ◽  
Cognitive Biases ◽  
Mass Scale ◽  
Data Sources ◽  
Micro Scale ◽  
Weakest Link ◽  
System 2 ◽  
Research Questions ◽  
System 1 ◽  
Scale Data

If people are the “weakest link” in cybersecurity because of their psychological make-up and hardwiring—their socialized desire to trust and cooperate with others, their cognitive biases and misperceptions, their preferences for convenience, their general going with System 1 inattention instead of System 2 attention and thinking—this begs the question of whether the same micro-scale cognitive limits found in individual users are also present on a mass scale. After all, there have been discovered problematic unthinking leanings in group decision making: obedience to authority, bystander effects, groupthink, and the Abilene paradox, among others. Using a range of often mass-scale data sources and data analytics tools, research questions were asked around three areas: (1) the level of sophistication of the cybersecurity electronic hive mind towards cybersecurity issues, (2) the gap between the non-expert members and the expert members in the hive mind, and (3) whether the extant hive mind was more reflective of mob unthinkingness or deliberation and wisdom.

scholarly journals Cognitive Biases in Human Causal Learning

2007 ◽  
Vol 10 (2) ◽  
pp. 242-250 ◽  
Author(s):  
Antonio Maldonado ◽  
Andrés Catena ◽  
José César Perales ◽  
Antonio Cándido
Keyword(s):  
Cognitive Biases ◽  
Relative Weight ◽  
Causal Learning ◽  
Causal Relationships ◽  
Theoretical Frameworks ◽  
Prior Beliefs ◽  
Human Causal Learning ◽  
New Findings ◽  
Causal Judgments ◽  
New Evidence

The main aim of this work was to look for cognitive biases in human inference of causal relationships in order to emphasize the psychological processes that modulate causal learning. From the effect of the judgment frequency, this work presents subsequent research on cue competition (overshadowing, blocking, and super-conditioning effects) showing that the strength of prior beliefs and new evidence based upon covariation computation contributes additively to predict causal judgments, whereas the balance between the reliability of both, beliefs and covariation knowledge, modulates their relative weight. New findings also showed “inattentional blindness” for negative or preventative causal relationships but not for positive or generative ones, due to failure in codifying and retrieving the necessary information for its computation. Overall results unveil the need of three hierarchical levels of a whole architecture for human causal learning: the lower one, responsible for codifying the events during the task; the second one, computing the retrieved information; finally, the higher level, integrating this evidence with previous causal knowledge. In summary, whereas current theoretical frameworks on causal inference and decision-making usually focused either on causal beliefs or covariation information, the present work shows how both are required to be able to explain the complexity and flexibility involved in human causal learning.

Evidence for an Age-Related Positivity Effect in Metacognitive Judgments

2020 ◽  
Author(s):  
Edie C Sanders ◽  
Jane M Berry
Keyword(s):  
Age Differences ◽  
Cognitive Biases ◽  
Memory Task ◽  
Late Life ◽  
Affective States ◽  
Theoretical Frameworks ◽  
Positivity Effect ◽  
Age Related ◽  
Metacognitive Judgments ◽  
Memory Monitoring

Abstract Objectives If older adults (OAs) are focused on emotionally meaningful goals in late life, they should demonstrate memory biases for positive stimuli over neutral and negative stimuli and, arguably, these cognitive biases should be reflected in their metacognitive judgments of learning (JOLs). To address this question, we examined age differences in metacognitive monitoring of emotionally valenced stimuli. Method Younger adults (YAs) and OAs (N = 85) studied positive, neutral, and negative words and made immediate JOLs, followed by a 2-alternative forced choice (2AFC) recognition memory task. Results Analyses of JOLs revealed evidence for a positivity effect in metacognitive judgments for OAs and an emotional salience effect in YAs. YAs recognized more words than OAs, but valence did not affect number of words recognized and did not moderate age differences in memory (p = .055). Memory monitoring as measured by resolution accuracy was equivalent in YAs and OAs. Positive affect was higher and negative affect was lower in OAs relative to YAs, lending additional evidence to the emergence of a positive orientation in older adulthood. Discussion These results provide intriguing and novel support for the positivity effect in the domain of metacognitive aging, adding to what is known in memory, attention, and emotion domains. Our findings fall squarely within socioemotional and metacognitive theoretical frameworks from which they were derived. We discuss research directions that might identify mechanisms by which affective states and stimuli interact to produce metacognitive outcomes in late life.

An enhanced personal credit identification coin-day destruction model based on blockchain technology fuzzy sets for region of China pearl river delta

2021 ◽  
pp. 1-7
Author(s):  
Jiansai Zhang ◽  
Lu Guo ◽  
Tingjie Lyu
Keyword(s):  
Fuzzy Sets ◽  
Pearl River Delta ◽  
River Delta ◽  
Data Sources ◽  
Pearl River ◽  
Personal Credit ◽  
Model Based ◽  
Blockchain Technology ◽  
Coastal Cities ◽  
Global Financial System

Nowadays, the Expansion and evolution of the global financial system oblige lenders to develop stricter requirements for assessing creditworthiness of borrowers. This paper analyses the problems prevalent in the existing credit models of coastal cities in China Pearl River Delta, including data centralization, difficulties in detecting forged data and delay in data transmission; we constructed a CDDC model based fuzzy sets that employs all the issues. The related results showed that the technology fuzzy sets decentralizes and expands data sources, acquires and processes data automatically and self-perfects its ability to rank borrowers into cohorts of creditworthiness. Moreover, the CDDC model out-performs the traditional model in assessing creditworthiness and reducing delinquencies and defaults. That means our fuzzy sets model employs decentralized data sources, destroys historical data regularly and facilitates training and improvement. It ranks creditworthy borrowers in a better fashion than the statistics-based traditional credit model.

scholarly journals Geographical Aspects in the Framework of Interdisciplinary Research on Migration

Geografie ◽  
1999 ◽  
Vol 104 (2) ◽  
pp. 73-88
Author(s):  
Dušan Drbohlav
Keyword(s):  
Interdisciplinary Research ◽  
Data Sources ◽  
Process Migration ◽  
Spatial Mobility ◽  
Migration Process ◽  
Theoretical Frameworks ◽  
Mobility Data ◽  
Basic Concepts

This contribution deals with the basic concepts of migration. It focuses on how geographical aspects may be understood within an interdisciplinary research of migration. The following points are discussed: conditionality of the migration process, migration definition within a broader concept of a spatial mobility, data sources and their "organization", principal dimensions of study of migration processes and related important theoretical frameworks and approaches.

How Well is US Intrafirm Trade Measured?

2015 ◽  
Vol 105 (5) ◽  
pp. 524-529 ◽  
Author(s):  
Kim J. Ruhl
Keyword(s):  
Economic Analysis ◽  
Census Bureau ◽  
Data Sources ◽  
Independent Data ◽  
Micro Data ◽  
Trade Data ◽  
Intrafirm Trade ◽  
The Us ◽  
Us Census

Using two independent data sources—the intrafirm trade data from the US Bureau of Economic Analysis and the related party trade data from the US Census Bureau—I construct and compare measures of US intrafirm exports and imports. I find that, in general, the two datasets provide similar measures of US intrafirm trade, particularly for exports. Understanding the differences that do exist in measurement will likely require study of the confidential micro data at both the Bureau of Economic Analysis and the Census Bureau.

scholarly journals From Person-Days Lost to Labour Militancy

2007 ◽  
Vol 62 (1) ◽  
pp. 31-65 ◽  
Author(s):  
Linda Briskin
Keyword(s):  
Human Resources ◽  
Statistical Data ◽  
Point Of View ◽  
Data Sources ◽  
The Political ◽  
Micro Data ◽  
Data Presentation ◽  
Employer Perspective ◽  
The Government ◽  
Work Stoppages

Using the micro-data from Human Resources and Social Development Canada (HRSDC) on the 23,944 stoppages in Canada between 1960 and 2004, this article introduces a labour militancy perspective on work stoppages, that is, from the point of view of workers. It explores patterns of militancy with a focus on strike duration, strike size and strikes for first contracts, and supports re-interpretations which help make visible the significance of such stoppages for workers, unions and communities. A labour militancy frame presents an alternative to the employer perspective on time lost, the government concern to measure the economic impact of stoppages, and the scholarly emphasis on strike determinants. As part of re-examining the HRSDC work stoppage data from a labour militancy perspective, the paper considers the source of these data. It juxtaposes the statistical data with interviews with the provincial correspondents who collect the information for HRSDC. Examining the data in this light underscores the political nature of data collection (what is seen to be germane and not), data presentation (what is made visible and what is not), and data sources (whose voices are heard).

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