Survey the effect of fintech companies’ profitability enhancement on winning customers’ loyalty using an artificial intelligence-based optimization algorithm

Document Type : Research Paper


1 Department of Information Technology Management, Qeshm Branch, Islamic Azad University, Qeshm, Iran

2 Department of Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran

3 Department of Industrial Engineering, Faculty of Engineering, Khatam University, Tehran, Iran

4 Department of Accounting, Tehran Science and Research Branch, Islamic Azad University, Tehran, Iran


The financial technologies currently known as Fintech refer as a significant innovation to the firms that combine financial services with innovative technologies. More precisely, Fintech means innovative financial solutions enabling novel and creative technologies and methods. Based on the reports by credible international institutions, global investments in Fintech in 2019 have undergone an increase of 120% in contrast to 2018. Therefore, the technological innovation development strategy and the related mechanism and process should gradually create new competitive advantages. Fintech innovations are strategic decisions a given company makes to enhance profitability and win customers’ loyalty. The present study investigates the effect of Fintech companies’ profitability enhancement on winning the customers’ loyalty through a random forest algorithm. The study uses a descriptive-applied research method. The study population included the customers of Asan Pardakht Company, reaching ten thousand individuals with 700000 transactions in number. These individuals (customers) were separated based on clustering operation and classified for being subjected to various tests.
Moreover, the cross-industry standard process (CRISP) Method was used, and its various stages were implemented, such as business perception, data perception, data preparation, modeling, evaluation, and expansion. After the explication of the data and, also, purging them in various stages, and following the data preparation, the data clustering operation resulted in six data clusters that were subsequently subjected to various examinations; the largest cluster (cluster no.4) was finally identified. Afterward, the various artificial intelligence-based optimization algorithms were implemented in the modeling stage. This is usually done with the determination of the accuracy and error rates. The results indicated that implementing the artificial intelligence-based optimization algorithm could enhance the companies’ profitability, which affects the companies’ winning of the customers’ loyalty and satisfaction with the managers of these companies being eventually envisioned as more efficient.


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Volume 14, Issue 1
January 2023
Pages 2409-2423
  • Receive Date: 28 February 2022
  • Revise Date: 12 April 2022
  • Accept Date: 19 June 2022