Journal ArticleDOI
A review of credit scoring research in the age of Big Data
Ceylan Onay,Elif Öztürk +1 more
TLDR
The authors find that credit scoring is going through a quantitative transformation, where data-centric underwriting approaches, usage of non-traditional data sources in credit scoring and their regulatory aspects are the up-coming avenues for further research.Abstract:
Purpose
This paper aims to survey the credit scoring literature in the past 41 years (1976-2017) and presents a research agenda that addresses the challenges and opportunities Big Data bring to credit scoring.
Design/methodology/approach
Content analysis methodology is used to analyze 258 peer-reviewed academic papers from 147 journals from two comprehensive academic research databases to identify their research themes and detect trends and changes in the credit scoring literature according to content characteristics.
Findings
The authors find that credit scoring is going through a quantitative transformation, where data-centric underwriting approaches, usage of non-traditional data sources in credit scoring and their regulatory aspects are the up-coming avenues for further research.
Practical implications
The paper’s findings highlight the perils and benefits of using Big Data in credit scoring algorithms for corporates, governments and non-profit actors who develop and use new technologies in credit scoring.
Originality/value
This paper presents greater insight on how Big Data challenges traditional credit scoring models and addresses the need to develop new credit models that identify new and secure data sources and convert them to useful insights that are in compliance with regulations.read more
Citations
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Journal ArticleDOI
Applications of Artificial Intelligence in commercial banks – A research agenda for behavioral finance
TL;DR: By using AI, commercial banks can reduce losses in lending, increase security in processing payments, automate compliance-related work, and improve customer targeting, according to a structured literature review.
Posted Content
The Basel Accord and The Value of Bank Differentiation
Ulrich Hege,Eberhard Feess +1 more
TL;DR: In this article, the authors investigate optimal capital requirements in a model in which banks decide on their investment in credit scoring systems, and the main result is that regulators should encourage sophisticated banks to keep their asset portfolios safe, while assets with high systematic risk should be concentrated in smaller banks.
Journal ArticleDOI
Design and application of a personal credit information sharing platform based on consortium blockchain
TL;DR: The in-depth integration of blockchain technology and personal credit reporting helps to realize the safe sharing ofcredit data and reduce the cost of credit data collection, thereby helping the technological and efficiency transformation of the personalcredit reporting industry and promoting the overall development of the social credit system.
Book ChapterDOI
Chapter 6 Big Data and FAIR Data for Data Science
TL;DR: In this paper, a review of modern phenomena in the field of data storage and processing as Big Data and FAIR data is devoted to the review of such modern phenomena, including the Internet of FAIR Data & Services (IFDS).
Journal ArticleDOI
Credit Risk Model Based on Central Bank Credit Registry Data
TL;DR: This research compares five machine-learning models to classify credit risk data, i.e., logistic regression, decision tree, random forest, support vector machines (SVM) and neural network, and proposes a model based on credit registry data from the central bank with detailed methodology that can predict the credit risk based oncredit history of the population in the country.
References
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Journal ArticleDOI
The measurement of observer agreement for categorical data
J. R. Landis,Gary G. Koch +1 more
TL;DR: A general statistical methodology for the analysis of multivariate categorical data arising from observer reliability studies is presented and tests for interobserver bias are presented in terms of first-order marginal homogeneity and measures of interob server agreement are developed as generalized kappa-type statistics.
Journal ArticleDOI
Basic Content Analysis
TL;DR: In this article, Content Classification and Interpretation Techniques of Content Analysis issues in Content Analysis are discussed and an overview of the content classification and interpretation techniques of content analysis issues are discussed.
Book
Basic Content Analysis
TL;DR: In this article, Content Classification and Interpretation Techniques of Content Analysis issues in Content Analysis are discussed and an overview of the content classification and interpretation techniques of content analysis issues are discussed.
Book
The Black Box Society: The Secret Algorithms That Control Money and Information
TL;DR: The Black Box Society argues that we all need to be able to do so and to set limits on how big data affects our lives as mentioned in this paper. But who connects the dots about what firms are doing with this information?
BookDOI
Measuring Financial Inclusion : The Global Findex Database
Asli Demirguc-Kunt,Leora Klapper +1 more
TL;DR: The first analysis of the Global Financial Inclusion (Global Findex) database is presented in this article, which measures how adults in 148 economies save, borrow, make payments, and manage risk.