Designing of a Risk Assessment Model for Issuing Credit Card Using Parallel Social Spider Algorithm

Shukla, Urvashi Prakash and Nanda, Satyasai Jagannath (2019) Designing of a Risk Assessment Model for Issuing Credit Card Using Parallel Social Spider Algorithm. Applied Artificial Intelligence, 33 (3). pp. 191-207. ISSN 0883-9514

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Abstract

The financial creditability of the customer needs to be verified by the lender/bank before issuing a credit card. This involves assessment of factors like the economic, social or social-economic background of the person. Thus, the features incorporated into the analysis are mixed data type ex. Income (numerical) and Property Owned (Categorical). In this manuscript, a credit card lending model is designed using a recently proposed parallel social spider algorithm by Shukla and Nanda in 2016. Suitable modifications have been introduced in the coding scheme and mating procedure to efficiently solve the credit assessment problem. Experiments are carried out on various standard credit card data available like German, Australian and Japanese credit card datasets. The superior performance of proposed algorithm is reported as compared to that achieved by K-means, parallel real genetic algorithm and parallel particle swarm optimization (PPSO). The Silhouette Index obtained by various algorithms specifically for Germen dataset are 0.56% by K-means, 0.86% by parallel Real Coded Genetic algorithm, 0.71% by PPSO and 0.84% by proposed method.

Item Type: Article
Subjects: Research Scholar Guardian > Computer Science
Depositing User: Unnamed user with email support@scholarguardian.com
Date Deposited: 19 Jun 2023 10:51
Last Modified: 08 Dec 2023 04:12
URI: http://science.sdpublishers.org/id/eprint/1189

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