PERAM: An Efficient Readiness Assessment Model for the Banking Industry to Implement IoT – A Systematic Review and Fuzzy SWARA Methods

Abstract

Since the emergence of the IoT and its significant benefits, various economic, social, and political groups have been deploying and implementing IoT in different sectors. The large amounts of data generated from connected devices and products can be analysed, transforming the goals and attitudes of businesses and industries, including the banking industry. However, implementing IoT on a large scale in an industry as complex as banking is challenging. While the advantages and role of IoT in banking are clear and increasing with various studies, inadequate implementation of IoT can lead to potential risks and failures. This research aims to assess the banking industry's readiness for implementing IoT, specifically focusing on their IoT implementation readiness. The study identified the factors and aspects affecting the research topic using a systematic review method and classified its enablers into dimensions, components, indicators, and sub-indicators. After validating the initial model with experts, the final model revealed that 7 dimensions, 8 components, and 63 indicators influence the readiness of the banking industry to implement IoT.  To rank the main aspects of the study, the Fuzzy SWARA method was used, and the results showed the following ranking: the dimensions of hard infrastructures, soft infrastructures, supply chain infrastructures, organizational factors, environmental factors, education and users, and security and privacy ranked first to seventh, respectively. The identified dimensions, components, and indicators provide a robust model for assessing the readiness of the banking industry for IoT implementation. The findings highlight the complexity involved in implementing IoT on a large scale within the banking sector.