Abstract

Indian card industry has gone through several interesting changes in the recent past. We wanted to explore this fascinating world both from card issuing and merchant acquiring perspective within our chosen study period of around 6 years - from Q2, 2011 to Q4, 2016. However rather than hunting the data to prove any pre-defined notion we wanted to listen to the data to capture the story it wants to tell us. We took a canvas of raw primary data from a no. of sources ranging from Reserve Bank of India to World Bank, from Ministry of Finance to Ministry of Statistics & Implementation (of Govt. of India) and a no. of other sources like Yahoo Finance, Index Mundi data portal. As a choice of tool we have used R (an open source software) and Excel for our study. In order to uncover the underlying story behind the data we have used an array of techniques ranging from descriptive trend chart, heat map, multidimensional bubble plot, outlier chart to advanced data analytics techniques like clustering using machine learning algorithm. We also uncovered the correlations of card industry parameters with other economic and social indicators and went ahead in building optimum casual predictive model as well as time series forecasting model.

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