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ExposureRefine Service
The RMS ExposureRefine service assesses data quality,
improves it where possible, and develops prioritized recommendations for
improvements over time. The assessment of current data quality focuses
on the evaluation of geocoding resolution, attribute completeness, and
attribute accuracy, and also includes in-depth sensitivity analyses to
understand how the quality of existing data influences modeled results.
This process is illustrated in the graphic below:
Completeness and Accuracy
The
ExposureRefine service employs RMS Data Quality Analytics to provide a
consistent benchmark for data quality in regard to geocoding resolution
and the completeness of primary attributes. In addition, two proprietary
RMS tools provide a powerful way to assess current data accuracy:
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The ExposureSource database, RMS’ proprietary
database of United States commercial and residential properties.
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Validation heuristics that assess data for accuracy
by flagging suspicious data based upon comparison to regional exposure
distributions as well as location level engineering-based rules.
Together,
these tools help to identify inaccuracies and bulk coding in the data.
This typically includes processing errors that may be causing a false
level of accuracy and, where data is “known,” systematic errors and
optimistic coding. Finally, a series of sensitivity analyses are carried
out to help quantify how inaccurate model results could be given current
data quality.
Recommendations for Improvement
After
problem areas are identified using Data Quality Analytics, the
ExposureSource database, and custom sensitivity analyses, a prioritized
set of recommendations for improving data quality are delivered based on
the specific engagement findings.
RMS Service Suite
The RMS Service Suite consists of distinct, but integrated services
provided by RMS that can be subscribed to as stand-alone offerings, or in
conjunction with additional services. Working with RMS analysts,
companies gain efficiency, speed, and quality assurance without the
expense of recruiting, training, and employee overhead.
RMS Data Cleansing Service addresses the “consistency” aspect of
data quality by offering a rigorous process for data formatting,
cleansing, and geocoding enhancement, resulting in high-quality data
that can be imported directly into RMS catastrophe models, or other
systems. The service increases analyst productivity by up to 50%, helps
reduce costs, and reduces risk uncertainty by cleansing property
schedules using RMS best practices.
RMS Data Analytics Service fits into the underwriting workflow to
assess exposure data quality and its impact on modeled loss costs. Data
Analytics empower insurers to assess the data quality of a risk at the
time of underwriting, measure its impact and target data improvements,
facilitating more informed pricing decisions. The Data Analytics service
utilizes RMS Data Quality Analytics and the Data Quality Toolkit to
synthesize data quality insights into an actionable report. Reports can
be customized to complement internal ”underwriting packs” or model
result summaries, providing enhanced insight into the risk being
underwritten.
RMS RiskAnalytics offers cost-effective analytical intelligence
from highly skilled analysts that support catastrophe modeling
activities as a seamless extension of an in-house team. The
RiskAnalytics operation is dedicated to the full spectrum of core
catastrophe modeling functions, and the team provides a range of RMS
support and expertise for identifying, quantifying, reporting, and
managing catastrophe risk.
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