Big Data Analytics in the German Banking Sector Using the Example of Retail Banking

Fom - University Of Applied Sciences, Berlin, Germany ,Kevin Hock

doi:10.47191/afmj/v7i2.01

Fom - University Of Applied Sciences, Berlin, Germany , Kevin Hock

Open Access

https://doi.org/10.47191/afmj/v7i2.01

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Abstract

Due to digitalization, the banking sector has been undergoing massive change in Germany for years. The causes are the rapid technological progress, regulation and supervision, the low-interest phase and demographic change. The future world of work will be characterised by digitalization and automation. These changes will have an impact on how bank customers demand, evaluate and ultimately purchase financial services. This paper examines the impact of digitalization on the entire German banking market and shifts the focus to big data analytics as a possible means of improving existing business areas with innovative approaches. The retail banking business is used as an example to show how Big Data Analytics is already being used by banks and what opportunities there are for further development. This quantitative research summarises the analysis of German banking groups using real key figures. The aim is to identify approaches to how banks can respond to the challenges of the market environment beyond cost-cutting measures. The relevance of the research's findings can be useful for academics looking at big data analytics and digital transformation in general in Germany's banking centre and looking for real examples from practice.

Highlights

According to a study conducted by the International Data Corporation (IDC) in 2020 as part of IDC's Spending Guides, the banking industry is the industry with the highest market share in terms of the Big Data analytics market in a global comparison
“Big Data Analytics in the German Banking Sector Using the Example of Retail Banking”
Trelewicz attributes the high relevance of big data analytics in the banking industry to the presence of the typical big data characteristics - the "3Vs" - in the financial environment: volume, velocity and variety of data

Summary

INTRODUCTION

According to a study conducted by the International Data Corporation (IDC) in 2020 as part of IDC's Spending Guides, the banking industry is the industry with the highest market share in terms of the Big Data analytics market in a global comparison. Trelewicz attributes the high relevance of big data analytics in the banking industry to the presence of the typical big data characteristics - the "3Vs" - in the financial environment: volume, velocity and variety of data She sees the constantly changing regulatory requirements and reporting standards as drivers for the continuous development of new data sources. According to Moormann, the integration of big data analytics into business processes, coupled with general technological progress, is leading to the biggest structural upheaval the German banking industry has ever experienced. The authors identified the use and expansion of big data analytics as a possible answer to the challenges presented in the banking market (Giebe & Schulz, 2021c)

LITERATURE REVIEW

Findings

CONCLUSIONS