Results 41 to 50 of about 10,825 (309)
Loan Default Prediction: A Complete Revision of LendingClub
Revista Mexicana de Economía y Finanzas Nueva Época REMEF, 2023 Predicción del default: Una revisión completa de LendingClub El objetivo del estudio es determinar un modelo de predicción de default crediticio usando la base de datos de LendingClub. La metodología consiste en estimar las variables que influyen en el
José Antonio Núñez Mora +4 more
doaj +1 more source
Housing as Asset‐Based Welfare in Australia: An Investigation Through a Consumption Lens
Australian Journal of Social Issues, EarlyView.ABSTRACT Housing asset‐based welfare has long been a key component of Australia's social policy. This resonates with a parallel literature identifying a trade‐off between homeownership and the size of nations' welfare states, wherein owner‐occupiers in smaller welfare states tend to come to rely on housing wealth to meet many of their welfare needs ...
Gavin A. Wood +3 more
wiley +1 more source
Monoallelic POLR3A Variants Cause Early‐Onset Peripheral Neuropathy
Annals of Neurology, EarlyView.Objective Biallelic variants in genes encoding the RNA polymerase III complex (Pol III) cause a spectrum of neurological disorders primarily affecting the central nervous system. Monoallelic variants have been reported in the POLR3B subunit only, associated with neurodevelopmental disorder, epilepsy, and peripheral neuropathy.
Luiza L. P. Ramos +46 more
wiley +1 more source
COCOA FARMERS CREDIT DEFAULT AND ITS IMPLICATIONS FOR RURAL AGRICULTURAL FINANCING IN GHANA [PDF]
Scientific Papers Series : Management, Economic Engineering in Agriculture and Rural Development, 2022 The role played by rural and community banks (RCBs) in financial intermediation in the cocoa sector is commendable, however, their full potential is not realized due to the high level of credit default by farmers.
Sonny Gad ATTIPOE +3 more
doaj
Multi-view GCN for Loan Default Risk Prediction
Neural Computing and Applications, 2023 Abstract Loan default risk prediction is a major application of machine learning for financial institutions to evaluate the client's default probability. Existing deep learning models rarely consider the connection among application records for loan default detection.
Zihao Li 0005 +4 more
openaire +1 more source
Journal of the Association for Information Science and Technology, Volume 76, Issue 4, Page 649-664, April 2025.Abstract Many theories of human information behavior (HIB) assume that information objects are in text document format. This paper argues four important HIB theories are insufficient for describing users' search strategies for data because of assumptions about the attributes of objects that users seek.
Anthony J. Million +3 more
wiley +1 more source
Default Rates in the Loan Market for SMEs:Evidence from Slovakia [PDF]
The current crisis raises the question whether loans to SMEs in emerging markets areinherently more risky. We use a unique unbalanced panel of nearly 700 loans made toSMEs in Slovakia between 2000 and 2005. Several probit and panel probit models showthat
Jarko Fidrmuc, Christa Hainz
core +2 more sources
Business Strategy and the Environment, EarlyView.ABSTRACT This study assesses the degree of alignment with and eligibility to the EU Taxonomy of non‐financial firms and investigates its relationship with their Cost of Debt (CoD). The empirical analysis is based on a sample of 306 non‐financial firms listed on the Stoxx Europe 600 Index across 15 European countries. Taxonomy‐related data were manually
Fabio Rizzato +3 more
wiley +1 more source
Riset Akuntansi dan Keuangan Indonesia, 2019 Erratum untuk artikel ini dapat dilihat: https://doi.org/10.23917/reaksi.v4i3.9409. Versi PDF terbaru artikel ini dapat diunduh pada laman tersebut.
Zulfikar Zulfikar +3 more
doaj +1 more source