ADOPTION, ANALYTICS, AND OUTCOMES: A QUANTITATIVE ASSESSMENT OF DATA-DRIVEN DECISION MAKING IN VIDARBHA’S FINANCIAL FIRMS

Abstract

Data-driven decision making (DDDM) has become one of the primary drivers of competitiveness and the success of operations in the financial industry due to its frantic turn into digitalization. The paper is a qualitative analysis of the implementation, introduction and the outcome of DDDM activity in the Vidarbha region of the state of Maharashtra comprising of commercial banks, cooperative banks as well as the non-banking financial companies (NBFCs). The research will scrutinize the rate of analytics adoption, technological maturity, existence of the data infrastructure, and perceived efficacy of the analytics-enhanced choices, following a questionnaire that will be handed out to the workers both on the managerial and the operational level (N = 300). This was one of the most common statistical tools, descriptive analysis, factor analysis, correlation and regression modelling, to investigate the connections between the most significant variables that may or may not be limited to the analytics capability, decision quality, operational efficiency, customer insights, and risk management processes. The findings indicate that the scale of DDDM implementation is moderate-to-high among the private and nationalized banks and low in the case of the cooperative and small banks due to the shortage of resources, competence gaps, and the legacy systems. It has also been found out that the correlation between analytics adoption and accuracy of decision making and efficiency of services and financial performance is very strong and positive. However, the challenges of low technical competence, difficulties in integrating data as well as the presence of irregular systems of governance are also some of the aspects that hamper the full capacity of DDDM in the region. The paper also offers practical recommendations that can be used to enhance the degree of analytics maturity, including the specialized training of the staff, the scaled data architecture investment, and the strengthened data management policy. Overall, the work provides empirical evidence to the existing body of research of the analytics adoption in new regional financial ecologies and uncovers the possibilities to implement the data-driven change in the Vidarbha financial sector more rapidly.