Albany – NY, Oct. 20, 2015 (GLOBE NEWSWIRE) — Automatic Teller Machines (ATMs) remain one of the main channels for the provision of retail banking services. ATMs continue to be one of the main touch-points for the customers of financial institutions. ATMs have changed their historical role of a mere cash dispenser and are expanding their potential to offer a wider range of services. The ATM industry’s offering has evolved significantly since its inception in the early 1960s, becoming a key enabler of branch innovation, and now evolving in parallel to internet banking and newly developing mobile banking channel.
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The ATM market continues to grow globally, largely thanks to a huge demand for cash withdrawal services in the coming years from emerging markets, in terms of the quantity of ATMs proportional to the population, in the volume and value of transactions captured through various channel.
The key trends observed in the market include rising electronic transactions, innovative technological advancing ATMs and entrepreneurs investing in Bitcoin ATMs among others. But there are certain challenges too faced by industry which include global increase of non-cash transactions, increasing high costs of operating retail ATM business and issues related to deployment of Bitcoin ATMs. The major growth drivers include increasing demand for cash withdrawals, integration of ADTs into ATMs, ATM growth in developing nations as well as increasing global GDP.
The report provides a comprehensive study of ATM market globally. The industry is concentrated with a few large players such as NCR Corp., Diebold, Inc. and Wincor Nixdorf. All these companies have been profiled in the present report highlighting their key financials and business strategies for growth.
By combining SPSS Inc.’s data integration and analysis capabilities with our relevant findings, we have predicted the future growth of the industry. We employed various significant variables that have an impact on this industry and created regression models with SPSS Base to determine the future direction of the industry. Before deploying the regression model, the relationship between several independent or predictor variables and the dependent variable was analyzed using standard SPSS output, including charts, tables and tests.
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