Is Ignorance Bliss? Consumer Accuracy in Judgments about Credit Ratings
TLDR
In this article, the authors examined the accuracy of consumers' self-assessments of their credit ratings and found that approximately 32 percent of consumers overestimate their credit rating, while only 4 percent underestimate their rating.Abstract:
There is considerable evidence to suggest that consumers are often misinformed about basic financial and economic principles. The purpose of this study was to examine the accuracy of consumers’ self-assessments of their credit ratings. Findings suggest that approximately 32 percent of consumers overestimate their credit ratings, while only 4 percent underestimate their credit ratings. Those who overestimate their credit quality are less knowledgeable about financial matters in general and are more likely to have acquired their financial knowledge from difficult past experiences. In addition, consumers who overestimate their credit ratings are less likely to budget, save, or invest regularly. There is considerable evidence to suggest that in general, consumers are unaware or misinformed about basic financial and economic principles— information they need in order to make important decisions such as buying a home and planning for retirement (Chen and Volpe 1998; Hogarth and Hilgert 2002; Lee and Hogarth 1999; Mandell 2006). This issue has gained more attention recently as a result of concerns about borrowers in the subprime market obtaining mortgages that they cannot afford. There is little known about the specific nature of this lack of awareness and misinformation. Credit scores are designed to measure credit risk at a particular point in time and are based on models that use information in consumer credit reportsmaintainedat thecredit reportingagencies topredictfuturepayment behavior(Fair Isaacs16). Lendersusecredit scores tohelp them makelending decisions, although each lender may differ in terms of the level of risk it finds acceptable, and this may even vary for different types of loans. Higher scores indicatelowercredit risks orhigher credit quality, althoughnosingle cutoff score is used by all lenders. Previous research on biases in judgment and decision making has shown that individuals tend to display overconfidence about their knowledge andread more
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References
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TL;DR: This book both explains the theory behind logistic regression and looks at all the practical details involved in its implementation using SAS, and explains the differences and similarities among the many generalizations of thelogistic regression model.
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Overconfidence and Excess Entry: An Experimental Approach
Colin F. Camerer,Dan Lovallo +1 more
TL;DR: This paper explored whether optimistic biases could plausibly and predictably influence economic behavior in one particular setting (e.g., entry into competitive games or markets) and found that most new businesses fail within a few years.
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The weighing of evidence and the determinants of confidence
Dale Griffin,Amos Tversky +1 more
TL;DR: The authors show that people focus on the strength or extremeness of the available evidence with insufficient regard for its weight or credence (e.g., the credibility of the writer or the size of the sample).
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Household Financial Management: The Connection between Knowledge and Behavior
TL;DR: In this paper, the authors focus on four financial management activities (cash-flow management, credit management, saving, and investment) and analyze the connections between knowledge and behavior, finding that those who knew more were more likely to engage in recommended financial practices.
Journal ArticleDOI
Knowing with Certainty: The Appropriateness of Extreme Confidence.
TL;DR: This article found that people are consistently overconfident in their confidence judgments and were willing to stake money on their validity when asked to answer general knowledge questions (e.g., absinthe is [a] a liqueur or a precious stone).