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Economy & Business, Volume 12, 2018

Anatoliy Antonov, Ventsislav Nikolov
Pages: 95-104
Published: 12 Sep 2018
Views: 1,336
Downloads: 193
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).
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