Credit concession through credit scoringAnalysis and application proposal

  1. Oriol Amat 1
  2. Raffaele Manini 1
  3. Marcos Antón Renat 2
  1. 1 Universitat Pompeu Fabra
    info

    Universitat Pompeu Fabra

    Barcelona, España

    ROR https://ror.org/04n0g0b29

  2. 2 Universidad de Murcia
    info

    Universidad de Murcia

    Murcia, España

    ROR https://ror.org/03p3aeb86

Revista:
Intangible Capital

ISSN: 1697-9818

Año de publicación: 2017

Título del ejemplar: IV Jornada ACCID i APC

Volumen: 13

Número: 1

Páginas: 51-70

Tipo: Artículo

DOI: 10.3926/IC.903 DIALNET GOOGLE SCHOLAR lock_openAcceso abierto editor

Otras publicaciones en: Intangible Capital

Objetivos de desarrollo sostenible

Resumen

Purpose: The study herein develops and tests a credit scoring model which can help financial institutions in assessing credit requests. Design/methodology/approach: The empirical study has the objective of answering two questions: (1) Which ratios better discriminate the companies based on their being solvent or insolvent? and (2) What is the relative importance of these ratios? To do this, several statistical techniques with a multifactorial focus have been used (Multivariate Analysis of Variance, Linear Discriminant Analysis, Logit and Probit Models). Several samples of companies have been used in order to obtain and to test the model. Findings: Through the application of several statistical techniques, the credit scoring model has been proved to be effective in discriminating between good and bad creditors. Research limitations: This study focuses on manufacturing, commercial and services companies of all sizes in Spain; Therefore, the conclusions may differ for other geographical locations. Practical implications: Because credit is one of the main drivers of growth, a solid credit scoring model can help financial institutions assessing to whom to grant credit and to whom not to grant credit. Social implications: Because of the growing importance of credit for our society and the fear of granting it due to the latest financial turmoil, a solid credit scoring model can strengthen the trust toward the financial institutions assessment’s. Originality/value: There is already a stream of literature related to credit scoring. However, this paper focuses on Spanish firms and proves the results of our model based on real data. The application of the model to detect the probability of default in loans is original.

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Fuente de los datos: Dialnet