The state of implementing big data in banking business processes: An Indonesian perspective

Abstract

Notwithstanding the perceived global potentiality, how big data enhances decision-making quality prompts an intriguing inquiry, especially in an increasingly competitive banking environment in developing economies. Building on an industry data-driven framework, this study strives to understand the state of implementing big data in the Indonesian banking sector. A deductively organized descriptive method employing in-depth interviews was conducted with subject matter experts representing Indonesian banking-related areas. The result and the following analysis show the modest status of big data implementation across three major banks and two complementary companies, as indicated by many elements of the framework phases that were found during the early adoption stage. This denotes a steady buy-in across banking business processes as particularly reflected in the framework’s four phases – continuing push to meet the variety aspect (intelligence), structured data architecture domination (design), limited choice of performance indicator for big data value (choice), and customer–corporate vision decoupling (implementation). While Indonesian banks have evidently initiated the big data implementation, further improvement remains imperative for the decision-making process. Accordingly, big data should be tightly coupled with a strong data-driven vision that drives decision-making across intra-firm actors. Handling data omnipresence shall be viewed as the embodiment of a data-driven vision.