Big Data Analytics in the Banking Industry

Running Head: BIG DATA ANALYTICS 1
BIG DATA ANALYTICS
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BIG DATA ANALYTICS 2
The banking industry has faced a great impact when it comes to big data analytics
applications in the firm's endeavors. This concept is widely used in the current banking sector to
reach ever-increasing masses. Most banks view this concept has the main tool for innovations in
planning for new ventures in the industry. It is applied when distributing resources for the aimed
consumers. When weighing dangers involved in new investment. Final conclusions are reached
upon the application of this tool. Industries use big information analysis when looking for new
ways of reaching the market.
Evolution of data analytics in the banking industry.
The role banking sector has been affected by the application of big data analysis in
several numbers of ways (Puiu et al., 2016). For instance, the determination of consumers
transaction behavior. Banks have a one on one link with their customer's accounts and they can
use this information in order to calculate an increment in the very customer's basic salary. This
stands a yardstick to banks when assessing dangers involved in lending to customers as well as
the sale of insurance coverage to their customers.
Grouping of potential customers according to their spending habits. Since they have
information concerning different spending habits of different customers, they can generate a
table of customers from the most potential ones to the least potential ones in terms of loan
repayment. This also helps banks to draw their expenditure draw well as well as planning their
yearly budgets effectively.
Easy identification of scammers and frauds. Banks using analysis of big information from
their potential customers can easily detect any form of fraud. For instance, if a given customer
prefers to use a credit card to draw a given amount of money from their accounts either monthly

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or weekly and all of sudden he /she attempts to make a huge amount of withdrawal using the
credit card, this attempts can be prevented since some reasons have to be given in order to
ascertain the identity of the person.
The information customer after dealing with certain banks contributes significantly to the
bank's productivity and success. This feedback information relates to how the customers view the
bank charges, rate and repayment period. The kind of punishments given to customers for late
repayments of loans. The banks use this information to apply other methods to improve their
efficiency and effectiveness.
Ways in which big data has disrupted the industry.
The emergence of new technology in the banking sector as a result of big data has really
disrupted the normal operations of different banking institutions. For instance, the use of mobile
banking, this has really reduced congestion in banks since people do not have to present
themselves physically as it was the case before (Xiang et al., 2015). The use of cheques is now
minimized by the use of bank to bank account transfers. Most customers find it easy to apply this
method instead of writing checks which usually takes a long time to mature.
In the stand, payments have been facilitated by the use of block chains and the use of
friend's payments via massages instead of rushing to the banks to use long procedures in order to
make simple payments to clients and customers. People do not need to visit the bank premises in
order to make some credit borrowing, all they need is to visit the specific website in order to
make their request and immediately get their wants granted depending on their creditworthiness.
How do you see the analytics changing the industry in the future?