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Data Solutions Overview


RMSI leverages its domain knowledge and data expertise to develop high quality, cost effective solutions specific to its clients' needs. Our offerings include data enhancement, manual flood determination and data engineering services. RMSI’s expertise lies in process migration and development.

 

We have been providing data enhancement services to the global insurance and reinsurance sector. We help our clients in cleansing and standardizing their actual insurance contracts data to be used in catastrophe models for assessing the potential risks due to natural and man-made disasters.

 

RMSI also has extensive experience in providing manual flood determination services such as determining whether properties fall in a flood zone, identifying the exact location of properties, and correlating the locations on to the flood insurance rate map accurately.

 

Data engineering services at RMSI, are designed to facilitate the categorization, storing, and management of clients’ data. We are able to convert large volumes of both paper-based and electronic files into electronic data for use in web-based or in-house applications.

 

Some RMSI projects include:
Development of a building and construction industry database containing over 700 building product categories, and requiring data indexing, cataloging and metadata creation

Creation of a digital database to hold large volumes of current and archived publication material, and requiring on-time delivery of consistent quality in terms of automatic XML conversion

Data capture and data entry of paper-based data into electronic information, which is easily portable and accessible via the web, and enables faster and more accurate searches to improve accuracy standards from 99.9% to 99.95%

Data capture and data entry of real estate information from quarterly broker reports, converting the data from PDF to MS Access format, and categorizing data into various pre-defined fields

Delivering improved efficiency in data cleaning operations by establishing specific workflows, which vary according to the quality of the source data, and automating processes wherever possible




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