Predictive Analytics in Financial Service

Running head: Predictive analytics in financial service
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According to (Bharadwaj, 2019) nowadays, the business has implemented automation
in its operations. This event has resulted in the collection of a lot of data. It is therefore evident

Predictive analytic in financial service 1.
that analytic data techniques are growing exponentially in business sectors. Predictive analytics
and predictive modeling are one of the most-known analytic tools used.
(FIRMANI, 2019) Defines predictive analytics as to the use of machine learning and
statistical analyzing techniques to predict the occurrence of a particular event in future form set
of historical data. He continues to add that business nowadays leverage predictive modeling to
discover complex data correlations to identify unknown patterns and well as forecasting.
Predictive analytics and modeling have gained its routes in different industries and
business sectors. For this matter, we wish to present a use case of the technique in financial
services. Predictive analytics helps in solving problems and helps in unleashing new
opportunities. In commercial sectors, for instance, banks, predictive analytics have been
embraced to detect fraud as well as reducing it. It has its roots in the measurement of credit risk.
It is, however, worth noting that data form financial services like banks tend to form a certain
Patten. For instance, the data can show a lot of significant transaction during the night, and this
might suggest that there might be some of the rules, for example, is evaded during the night. It is
therefore reasonable to uses pattern tracking as the best data mining technique in this form of
industry. In banking, for instance, data mining helps in: (1) forecasting the most probable loan
defaulters,(2) detection online banking and fraudulent and (4) identifying the potentially
profitable customers and their preferred needs. (Sharda, 2011) . An excellent example of a
finance case application of the predictive analytics and predictive model is Rapid miner
(Ristoski, 2015). The company was founded in 2007 ever since then; it has been building
software to do data analysis. Some of the predictive analytic that Rapidminer offers includes;
demand forecasting, fraud detection, and preventing churn among others. Recently PayPal is
working with the company. (Verma, 2014) Claims that predictive analytics software by