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Data Mining Techniques




Data mining is an interdisciplinary field of astronomy, business, and computer science, economic and other to discover new patterns from large datasets. Data mining technology can help the insurance firms for taking crucial business decisions.

The insurance sector is primarily dependent on customer’s base. The most scenario of any insurance firm, effective management of customer data is essential one. With the help of data mining techniques, the customer data handled effectively.

Data mining is to help the market specialists for decision making process. Companies in the insurance industry collected huge amounts of data about their customers. Due to their protective regulations, extracting information from the database caused a lot of time. In that situation, Data mining very helpful to the firm for access the data easily

Data mining refers to extracting or “mining” knowledge from large amount of data. Data mining as a synonym for another popularly used term, knowledge discovery from data or “KDD” The goal of this technique is to find pattern that was previously unknown data.

A. Data Mining Techniques

Data mining techniques have applied to various insurance domains to improve decision making. Data mining use predictive modeling, market segmentation, market basket analysis to answer business questions with greater accuracy. Various data mining techniques used for the insurance industry development are Classification, Clustering, Regression and Association rules, summarization  used for knowledge discovery from database.


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