Ensuring Success With Analytics in Banks and Financial Services Firms

Abstract

Purpose: Big data analytics is a recently available state of the art technology with prospective company influence. Nevertheless, the roadmap for the successful implementation of its as well as the road to exploiting its essential value remains unclear. This particular analysis seeks to make a much deeper understanding of the enablers facilitating BDA implementation in the banking.

Design/Methodology/Approach: We use an integrated approach that incorporates Delphi review, interpretive structural modeling, and fuzzy MICMAC strategy to determine the interactions between enablers, which determine the achievements of BDA implementation. Our strategy uses experts' understanding and gains a novel insight into the underlying causal relations regarding enablers, linguistic analysis of the mutual impacts among variables, and including 2 innovative methods for visualizing the outcomes.

Findings: Our findings highlight the primary key role of enabling elements, which includes skilled and technical workforce, financial assistance, infrastructure readiness, and choosing proper major data solutions. These factors have significant driving impacts on various other enablers in a hierarchical design. The results give reliable, easy and robust insights into the characteristics of BDA implementation in banking and monetary service as an entire program, while demonstrating possible influences of all interconnected important elements.

Originality/Value: This analysis explores the primary key enablers for effective BDA implementation in the banking and monetary service sector. More to the point, it reveals the interrelationships of elements by calculating operating and dependence degrees. This specific exploration provides managers with an obvious strategic path toward good BDA implementation.