2024/04/26 by Mohammad Sajjad Shahbazifar, Shahbazifar, Mohammad Sajjad, Reza Kazemi Matin +5
Computer Science · Decision Sciences · Social Sciences · #Banking Groups #Data Envelopment Analysis #Delphi Technique in Research #Efficiency Analysis Using DEA #Group Efficiency #Imbalanced Data Classification Techniques #Machine Learning #Neural Network #Ranking
paper · doi:10.82521/ijo.2023.1154113
openalex publication_date 2024/04/26 · openalex created_date 2025/12/27 · openalex updated_date 2026/07/07
This paper explores the intersection of Group Ranking in Data Envelopment Analysis (DEA) and the potent capabilities of Machine Learning (ML) within the insurance sector, aiming to redefine group efficiency assessment. While DEA has been a cornerstone for evaluating Decision-Making Units (DMUs), the traditional models fall short in the nuanced insurance sector. To address these limitations, ML is integrated into DEA, enabling more effective DMU ranking. The study includes an empirical application within the banking industry, emphasizing the methodology's relevance and potential to transform the insurance landscape.