Predictive Analysis for Risk Reduction in Data Mining

Abstract

In this age of artificial Intelligence and machine learning, Business Intelligence is also gaining more significance as the organizations worldwide want to build intelligence into their business processes so they can better understand the customer behavior or patterns and provide insights for business leaders to make the right decisions in the market place to keep them competitive and efficient by reducing the risk optimizing operations or Fighting fraud to the extent possible. Business Intelligence in its crude form always existed before the IT in terms of experience and business expertise with the employees handling certain business process over decades but this process does not guarantee all the factors have been accounted for and no way to prove their analysis out before any decisions to be made by the organization. The Business Intelligence is data driven and has a scientific process behind it to analyze the data and provide models to test the What-If scenarios so Businesses can make less risk prone decisions. That said we cannot make it 100% reliable but it is way far better than making a guess out of one person's perspective. This paper aims to explore Data Mining and Predictive Analysis in the context of business applications and the techniques involved which eventually build the intelligence needed in the Business Intelligence.