Artificial Bee Colony for Logic Mining in Credit Scoring

• DOI: 10.11113/mjfas.v18n6.2661
• Publication Date: 2022-12-29T15:28:31Z
• Authors: Siti Zulaikha Moh...; Nur Syazwani Sa’ari; Mohd Shareduwan M...; Muhammad Fadhil M...; Nur Ezlin Zamri; Siti Aishah Azhar; Yueling Guo; Mohd. Asyraf Mansor
• Keywords: Overfitting; Credit score; Swarm intelligence

During the SARS-CoV-2 (Covid-19) pandemic, credit applications skyrocketed unimaginably. Thus, creditors or financial entities were burdened with information overload to ensure they provided proper right person. The existing methods employed by prone overfitting and did not provide any regarding behavior of creditor. However, outcome consider attribute creditor that led default outcome. In this paper, a swarm intelligence-based algorithm named Artificial Bee Colony has been implemented optimize learning phase Hopfield Neural Network 2 Satisfiability-based Reverse Analysis Methods. proposed hybrid model will be used extract logical in data more than 80% accuracy compared method. effectiveness was evaluated showed superior results other models.