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Improving Data Quality

We asked four leading insurance industry analysts the following question: What are the important steps insurers need to take to improve the quality of their data in preparation for the installation of analytical tools?

By Robert Regis Hyle | Updated on August 31, 2013

We asked four leading insurance industry analysts the following question: What are the important steps insurers need to take to improve the quality of their data in preparation for the installation of analytical tools?

Craig BeattieSenior analyst, insurance, Celent

Improving the quality of data after it has been captured has always been a challenge. The first step is to improve the quality at point of capture. This can mean making it easy for customers to enter the right data, the use of appropriate validation rules, and incentivizing staff to capture the data accurately.

There are possibilities for improving existing data as well. A simple example is to take address data and use a tool to geo-code the address. This can highlight missing data and bad addresses, which could be dealt with through exception processing. The use of tools that look for valid names of individuals is another good example as a side benefit to the rise of the use of credit scoring in some countries.

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