Impact of Big Data Analytics on Banking Sector: Learning for Indian Banks

Abstract

The big data revolution happening in and around 21st century has found a resonance with banking firms, considering the valuable data they’ve been storing since many decades. This data has now unlocked secrets of money movements, helped prevent major disasters and thefts and understand consumer behaviour. Banks reap the most benefits from big data as they now can extract good information quickly and easily from their data and convert it into meaningful benefits for themselves and their customers. Banks internationally are beginning to harness the power of data in order to derive utility across various spheres of their functioning, ranging from sentiment analysis, product cross selling, regulatory compliances management, reputational risk management, financial crime management and much more. Indian banks are catching up with their international counterparts; however a lot of scope remains. This paper aims to capture how big data analytics is being successfully used in banking sector, with respect to following aspects: Spending pattern of customers Channel usages Customer Segmentation and Profiling Product Cross Selling based on the profiling to increase hit rate Sentiment and feedback analysis Security and fraud management The data used is secondary data from a bank while the analysis is of primary nature. This study reveals some of the best practices being adopted by banks globally, and can be replicated by Indian banks to enhance their financial service offerings to customers.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 161 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.