Abstract
As the need for real-time data availability and reporting capabilities grew
over the following several decades, increasingly sophisticated database standards and
applications were created. These developments have recently started to accelerate due
to the rising use of advanced analytics and data visualisation in recent years. The
process of extracting hidden insights from vast amounts of organised and unstructured
data known as data science now makes use of highly developed technology such as
data mining, machine learning, and advanced analytics. Big data is no exception to the
banking industry's history of being an early user of new technologies. Big Data is a
term used to describe an expanding body of data that is both structured and
unstructured and is present in a variety of formats. Volume, velocity, variety, value,
and truthfulness are this technology's key characteristics.
Keywords: Credit risk analysis, Descriptive analytics, Liquidity risk, Market trading analytics, Operational risk, Predictive analytics, Regulatory specifications, Risk modelling, Risk management.
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