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Data Quality Toolkit The RMS® Data Quality Toolkit,
a robust client-server application, enables insurers and reinsurers to assess
exposure data quality, measure its impact, and target data improvements
where they matter most for catastrophe risk models. Data can be viewed
at a macro level, e.g. by cedant or portfolio, or honed in to the
location level. The Data Quality Toolkit delivers objective and
independent insight into data quality, providing transparent,
actionable, and easy to communicate metrics to inform portfolio
management and underwriting decisions.
Unlike the use of conventional metrics, the
scoring metrics produced by the Data Quality Toolkit utilize RMS’ innovative Data
Quality Analytics that build upon the foundations of our catastrophe
models to weight the quality of data by the importance of vulnerability,
hazard, and net exposure. Scores account for the
severity and gradient of the hazard, the relative importance of
modeling attributes (e.g. occupancy, construction class, year built, and
number of stories) for that region and peril, and the implications of
financial structures, including attachment points.
Accuracy is assessed using formalized validation
heuristics to identify suspicious combinations of building, financial
and policy attributes; comparison with the RMS ExposureSource database;
and metrics to indicate how aggressively or conservatively the portfolio
has been coded compared to industry averages.
The ExposureSource database is a comprehensive
database of location-specific, U.S. commercial and residential property
exposure data. Developed specifically to provide exposure data optimized
for use with catastrophe modeling for the insurance industry, the
ExposureSource database provides a robust source of exposure data for
improved risk analysis and management.
Key Features The Data Quality
Toolkit is a Microsoft Windows application running in a client-server
environment designed to provide users with maximum flexibility for
measuring, reporting, and improving exposure data quality at the
portfolio level.
Assess Portfolios across Multiple Data Sets
The Data Quality Toolkit assesses the quality of exposure data contained
within the RMS Exposure Data Module (EDM). Portfolios can be grouped for
analysis across one or more EDM databases to score and report data
quality by user-defined groupings such as by cedant, broker, or business
unit.
Validate and Enhance Data
The enhancement feature enables the improvement of exposure data by
replacing incorrect or missing attributes with those from the
ExposureSource database. After enhancement, the Data Quality Toolkit
reassesses the enhanced data to measure the impact of the improvements.
Optionally, a newly enhanced EDM can be generated for analysis in the
RiskLink® software platform.
Create User-Defined Validation Heuristics
The toolkit provides over 100 validation heuristics against which the
data is compared in order to identify inconsistent or illogical
combinations of geocoding, building, valuation, and financial
attributes. In addition, users can access a rule builder that enables the
creation of additional validation heuristics. These customized
heuristics can be incorporated into unique validation heuristics
profiles alone or with RMS defined rules, allowing evaluation of
datasets against a variety of profiles to adjudge data quality.
Flexible Job Profiles
The Data Quality Toolkit provides an
intuitive interface for defining analysis runs. Analyze data quality via
multiple runs using subsets of analytics or different validation
heuristics or enhancement profiles. The results from each run are stored
in the results database to allow comparisons.
Compare Data by Cedants, Business Units, or Over Time
Compare results from multiple
results databases to evaluate relative data quality over time or across
groupings of exposure data such as cedants or business units.
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