Digital transformation challenges in sustainable financial service systems using novel interval-valued Pythagorean fuzzy double normalization-based multiple aggregation approach

Recently, financial service systems have had essential impacts on public policies, the economic performance of firms, and all forms of industry and commerce. These systems play an important role in determining whether a society (which includes a wide range of members, from governmental institutions to individual consumers) has been successfully considered an environmentally sustainable path. The literature shows that the people who work in the financial sector are mostly unaware of the pressure and rationale behind sustainable development and its bearing on their work; however, those who work in the relevant research and policy areas generally ignore the vitality of the role of the financial sector in such a development. The study of interval-valued Pythagorean fuzzy sets (IVPFSs) indicates an urge for a decision approach to implementing the available information for rational decisions properly. Inspired by the advantage of IVPFSs, an extended decision methodology called the IVPF rank-sum weighting method (RSWM)-double normalization-based multi-aggregation (DNMA) is discussed. In this line, the IVPF-RSWM is applied to find the subjective weights of digital transformation challenges of sustainable financial service systems (SFSS), and the DNMA framework is developed to obtain the preferences of SFSSs in the banking sector. A case study to assess the main digital transformation challenges in SFSSs of the banking sector is undertaken. Further, comparison and sensitivity investigations are taken to illustrate the advantage of the presented approach.