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RMS To Release Data Quality Toolkit, Enabling
Companies To Target Data Improvements
California – May 19, 2009 - Risk Management Solutions (RMS) today
unveiled its new Data Quality Toolkit, which will empower insurers and
reinsurers to assess, manage, and improve the quality of their exposure
data. The Toolkit integrates advanced RMS analytics, data from a unique
exposure database, and result reports, allowing companies to
comprehensively assess both the completeness and accuracy of their
exposure data from a model-informed perspective.
As the issue comes under growing scrutiny by third parties, companies
are increasingly required to demonstrate robust data quality practices.
The RMS® Data Quality Toolkit enables companies to target data
improvements in the areas that will have the greatest impact on
catastrophe model loss results. It also enhances their ability to select
between previously undifferentiated risk and to offer competitive
pricing structures on the risks selected.
The Data Quality Toolkit – a Microsoft Windows® application - draws on
the proprietary RMS ExposureSourceTM Database, which contains primary
modeling attribute information for more than 9 million commercial and 65
million residential locations throughout the U.S. This allows companies
to compare their existing information with the RMS database, and enhance
missing or incorrect attributes including occupancy, construction class,
year built, number of stories, and floor area.
“The release of a tool that can objectively assess data quality and help
to fix the highest priority locations is a significant advancement,”
commented John DeMartini, executive vice president of Towers Perrin. “We
envision using this tool to accelerate our ability to help clients
improve the quality of their data in time to impact 1/1 renewals.”
As well as being able to compare their data against the ExposureSourceTM
Database, companies can use the Toolkit to assess the accuracy of their
data by:
• Using validation heuristics, which highlight suspect geocoding,
unusual combinations of primary modeling attributes, and questionable
coding of financial structures, and
• Comparing it against an industry benchmark portfolio to suggest
aggressive or conservative data coding of primary attributes and
secondary modifiers.
Reports produced from the Data Quality Toolkit allow users to examine
the drivers of data quality at an aggregate level - such as portfolio,
account, state, or county – or down to location level, enabling them to
implement specific strategies to address data issues.
Roger Arnemann, vice president of Data Solutions at RMS, explained: “The
Data Quality Toolkit offers an objective perspective on data quality,
giving companies unique insight into factors such as exposed limit,
underlying hazard, vulnerability for different perils, and sensitivity
effects on modeled losses.” He added: “New metrics will help insurers
and reinsurers quantify the potential range of modeled loss changes due
to incomplete or insufficiently detailed data.”
Rating agency requirements
Rating agencies examine data quality when assessing the reliability of a
company’s probable maximum loss (PML) and its balance sheet strength,
and A.M Best has recently introduced additional questions about data
quality in their Supplemental Rating Questionnaire (SRQ). Thomas Mount,
assistant vice president of the Property & Casualty Ratings Division at
A.M. Best, explained: “If our analysts have concerns about a company’s
data quality and these are not explained or addressed properly, we could
potentially add up to 30 percent onto the probable maximum loss that is
reported.” The Data Quality Toolkit includes a report that directly
addresses these questions, potentially saving companies days in
compiling the information.
Mr. Arnemann concluded: “Systematic use of data quality analytics
informs the insurance lifecycle from primary underwriting and pricing
through to reinsurance, retrocession, and capital allocation.
Well-informed risk selection, whether for policies or treaties, leads to
better pricing and fewer surprises in the event a catastrophe strikes.”
The Data Quality Toolkit will be available from June 30, 2009. More
information is available at:
www.rms.com/Publications/Data_Quality_Toolkit.pdf
About RMS
Risk Management Solutions is the world’s leading provider of products
and services for catastrophe risk management. More than 400 leading
insurers, reinsurers, trading companies, and other financial
institutions rely on RMS models to quantify, manage, and transfer risk.
Founded at Stanford University in 1988, RMS serves clients today from
offices in the U.S., Bermuda, the U.K., France, Switzerland, India,
China, and Japan. For more information, visit our website at
www.rms.com.
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