VALIDATION PROCESS FOR SCORING AND RATING MODELS USING NEURAL NETWORKS
Published: 12 Sep 2018
Abstract: This research paper investigates the validation and calibration of models for determination of credit scoring and rating with statistical methods. This is done through a comparison of the results of the model to an alternative model, based on a neural network, and a calculation of different statistical parameters. A prototype of a software system for analysis and evaluations is represented that calculates distance, standard deviation, correlation, cumulative accuracy profile (CAP), as well as accumulation and analysis of historical statistics for default losses.
Keywords: credit rating, scoring, validation, analysis, calibration, neural networks
Cite this article: Anatoliy Antonov, Ventsislav Nikolov. VALIDATION PROCESS FOR SCORING AND RATING MODELS USING NEURAL NETWORKS. Journal of International Scientific Publications: Economy & Business 12, 95-104 (2018). https://www.scientific-publications.net/en/article/1001722/
Download full text
Back to the contents of the volume
© 2021 The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0/
, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. This permission does not cover any third party copyrighted material which may appear in the work requested.