The financial services sector experiences significant effects from digitalization. A crucial factor is that financial offerings heavily rely on information. Notably, fintech chatbots enhance the exchange of information by being integrated into messaging platforms, websites, and mobile apps. This integration enables users to engage with these chatbots using written or spoken conversations.

While the literature has explored different enablers that facilitate the adoption of fintech chatbots, the interplay between these enablers is currently intricate and multifaceted. Due to the rising complexity, academics and practitioners have become increasingly interested in understanding the proper hierarchy of fintech chatbots’ enablers. The SPAR-4-SLR protocol of systematic literature review is used to identify the contextual enablers of fintech chatbots, which are further finalized by integrating experts’ recommendations. In response, this study applies interpretive structural modeling (ISM) and creates a five-level hierarchical structure.

Sonal Ahuja
Doctoral Research Scholar, Jindal Global Business School, O.P. Jindal Global University, Sonipat, India.

Vaibhav Sharma
Doctoral Research Scholar, Jindal Global Business School, O.P. Jindal Global University, Sonipat, India.

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