Abstract

The performance of the banking sector depends on the ability of a range of banking products to meet customer needs in a timely and complete manner. Due to the specific features of the banking sector, technological capabilities to accumulate a massive pool of customer information about banking services, the German banking sector has more capacity than other industries to launch and sell banking services that will be in high demand among users. The author points out that innovative methods and solutions were developed on the basis of mathematical and statistical models. It is stated that a progressive tool for providing customer-oriented services and products, in the banking sector, is currently defined as “Big Data & Analytics”.

The main purpose of the study is to identify the peculiarities of the use in the banking practice of the analytical tool “Big Data & Analytics” and the functional ability of this tool to ensure stable customer loyalty in the course of using banking services.

The study empirically confirmed (based on a survey conducted in the fall of 2019) and theoretically proved that there is a strong relationship between the use of the Big Data & Analytics tool and the provision of key principles of customer loyalty in the following areas of the banking sector: advice to clients by banking employees systems must be objective and comprehensive, be individualized and be provided in a timely and comprehensive manner. Emphasis is placed on the need for further research on the effectiveness of internal and external business coaching, which is particularly relevant in the context of a total digital transformation of all spheres of society and entrepreneurship.

Keywords: big data and analytics, corporate social responsibility, customer loyalty tool, business ethics.

JEL Classification: G21, Q56.

Cite as: Giebe, C., Hammerström, L., Zwerenz, D. (2019). Big Data & Analytics as a sustainable Customer Loyalty Instrument in Banking and Finance. Financial Markets, Institutions and Risks, 3(4), 74-88. http://doi.org/10.21272/fmir.3(4).74-88.2019.

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