In the digital era, it’s important to know how much you make, where you spend it and what you purchase. Some people don’t divulge this to their nearest trustees. But the precious data held by banks is an enormous opportunity. Especially in cases where loans and trade are subject to constant lower interest rates and more stringent rules. Surprisingly, most of this information is presently within the banking scheme, produced by day-to-day transactions. No intrusive client surveys or costly market study programs collect this precious data.
Further, most generate data comes from the bank’s information systems. This includes manually entered data or automated such as credit card processing and ATM transactions. Additionally these arrive from internal and external audit requirements, meeting government or central bank regulations.
Why Data Mining?
In many company organizations, including the banking industry, data mining is becoming a strategically significant area. This is a method for evaluating and synthesizing data from a range of perspectives. Data mining helps the banks to search for hidden patterns in a group and to find unknown information relation.
The increase in data extraction occurs with a changed regulatory context. New rules on EU technology businesses implemented last year enable access of client information on authorization. EU’s privacy laws are now stricter. Companies need permission for using private data gleaned from users.
Where is this Applicable?
The retail store is an example of the earliest implementations of data mining. The stores management analyses often purchased products together by mining the quantities of points of sale (POS). This understanding resulted in modifications in the shop layout that physically have brought the associated products closer The findings resulted in better inventory management and stock storage.