Last Updated on
The insurance industry is one of the many taking full advantage of data through aggressive data management programs. Like most other industries, these programs reduce costs and give companies strategic advantage. The insurance industry is particularly sensitive to the use of accurate data. The fundamentals of the industry are based upon statistics, underwriting and the reduction of risk. Fully understanding the risk of each insured allows an Insurer to understand the level of coverage they can provide. Within these risk assessments are the actuary tables, which predict, within a highly narrow margin, the predictability of life span and probability of death. These tables have always been a part of the process, but now, accurate data sets can sharpen the accuracy predicting certain circumstances.
Our case study focuses on the Zurich Insurance Group, which is a leading multi-line insurance provider offering a wide variety of commercial business insurance products and risk management solutions for medium and large businesses, as well as multi-national corporations. The company has locations in North America, Europe, Latin America, Asia-Pacific, and the Middle East. Due to the stringent standards of the insurance industry, the constant need to police and monitor data requires clean, usable information.
Andy Green, Statistics Manager with Zurich NA, was responsible for resolving conflicting data within its core mainframe database. In the insurance industry, having payee names aggregate and match are critical for the functioning of various payment processes.
Their current system does not have a hard edit function where payee names can pre-populate, so those managing and entering information in the database can just key in any type of information. If any query was run against the main data warehouse, a long list of duplicate information would pop up. The result of this would cause problems with vendor names not aggregating appropriately.
With the best in class data cleansing and fuzzy matching capabilities, combined with customized training by Data Ladder specialists, Zurich NA was finally able create several confidential reports required by the industry, something they were not able to do before.
With the ability to constantly monitor data and locate certain records quickly, they could use DataMatch to look at information and make sure that payments were processed correctly and without human error. Andy Green, Statistics Manager stated:
“As part of the insurance industry we have to provide internal reports. We could not do these reports before. Now, DataMatch has become a main staple in my suite of tools that I work with!”
Requests for Data Match software are becoming more frequent within the organization. With the support and backing of the company’s Chief Financial Officer, DataMatch has become quite the resource for data cleansing and fuzzy matching needs.
Finding the right partner is the key to success when managing data. This case study clearly demonstrates the ability of Data Ladder to provide exceptional service and product to an industry with complex needs. Go to DataLadder.com to see more case studies, then download a free trial of our flagship software.