The be recorded systematically. Structuring and recording

The notion
“Big Data” is no more cramped to the realm
of technology. Big data expanding in diverse segments of the business world using some advanced
statistical and mathematical models such as data mining, artificial
intelligence, predictive analysis to gain new acumen ensuing superior and
quicker business decisions. In this context, we can pose a question to
ourselves “do banks and financial institutions have the potential to produce a huge volume of data?” The answer is, “Of
course, Yes”.   

Banks
record millions of business transaction every day and these entries are real-time in nature. The nature and volume of
data generated by banks are not just
large also real time. Nonetheless, capturing and recording such a huge chunk of
data is a challenging job for bankers. Big data analytics help banks by
providing a platform where these transactions can be recorded systematically.  Structuring and recording the data are
useless until and unless there is a plan to make use of such a large data.
Therefore, identifying the connection between the data captured and possible
results is a puzzling task in today’s complex business world. The connections
may be anything such as security and fraud detection, risk management, analysis
of customer spending & investment pattern, compliance, financial reporting,
market segmentation and product customisation, etc.

Decades
ago, a typical bank customer would walk into a bank and be greeted by an executive
who knew his name, his personal backgrounds and how best to serve his personal
banking needs. This is quite an old model where banks have acquired and
retained the customer’s trust and served them for a long time. However, the situations
changed. People often be engaged on
multiple assignments and locations and travels to different geographical locations.
If one day he stays in New Delhi, the immediate next day he may have to visit
Paris on his business assignments. In such conditions, it is challenging for a
bank executive to track his personal preferences and whereabouts to meet his
needs. Big data give insight into many complex areas of business including
their lifestyle, need and preferences so that it is easy for banks to personalise services to the needs of each
individual.

For
a long time, the banks miserably failed to utilise
the information generated by their own business. The big data has become a game
changer transforming conducts and process to identify business opportunities
and potential threats. Generally, banks and financial institutions find big
data from the sources such as log data,
transactions, emails, social media, external feeds, sponsorship, audio, video
and some other sources. Introduction of big data in banking has destroyed many
ground rules of business and transforming the landscape of the financial
services industry. With a huge volume of data gushing from countless
transactions, the financial institutions like banks are trying to find out
innovative business ideas and risk management solutions. Each set of the data
gathered over a period tells a unique story and shows the goalpost for a
definite future period so that a business firm can capitalize on this information to attain a competitive edge in the market. Big data
analytics can improve the extrapolative power
of risk models used by banks and financial institutions. Big data can also be
used in credit management to detect fraud signals and same can be analysed in real time using artificial
intelligence.

On a
serious note, banking and finance industry cannot see the significance of data
analytics in isolation. Along with identifying business opportunities, they
also concerned about identifying the possible security threats, the occurrence of fraud and possible remedies. Furthermore,
inability to connect big data across departmental and organisational silos has been a greater challenge for years.  Still, some banks of India, have not begun
their big data activities which are beneficial for some of the largest private
sector banks. Big data science not only brings new insights, but it also enables banks and financial institutions to
stay a step ahead of the game with advanced technologies and analytical tools.