BACKOFFICE
Strategies and technologies to boost
behind-the scenes efficiencies
BACK OFFICE SOLUTIONS
InSPro In TroDucES BI,
AnALy TIcS SoLu TIon
InsPro Technologies, an Eddystone, Pa.-based provider of comprehensive and
flexible life and health insurance processing solutions, announced the introduction
and immediate availability of InsPro Analytics, a data analysis and business intelligence application pre-integrated with the
InsPro Enterprise solution suite for life and
health policy management.
InsPro Analytics is available through a
traditional software license, as a hosted
solution, or via software-as-a-service
(SaaS), and is designed to import third-party data in order to build a robust data
set as well as provide breadth, depth and
detail with the resulting analysis.
The combination of InsPro Enterprise, a
flexible, end-to-end policy management
and administration suite, with the newly
introduced InsPro Analytics, enables insurers to learn from the past and react quickly to best impact the future, the company
says.
Additional InsPro Analytics’ highlights
include:
• Detailed business analysis for sales,
customer service, actuarial and claims de-
partments
• A single, streamlined user interface
with decision trees and drag-and-drop
mapping
• Easily customizable views and dash-
boards
• Demographic data mapping, numeric
reports, and graphic and pie displays
• Extensive on-demand reporting with
current data for the most up-to-date view
of the business
• Data imports from external sources
for more robust data set.
STonErIvEr rELEASES v7.0 oF
rEInSurAncE SoLu TIon
StoneRiver, Oakland, Calif., released ver-
sion 7.0 of URS, its reinsurance software,
which includes a Java-based user interface
with business logic running on a J2EE ap-
plication server. The N-tiered architecture
and new technology improvements prom-
ise to enhance operations and scalability as
well as streamline the reinsurance solution’s
multiple operating environments,
StoneRiver says. A new browser-based in-
terface enables desktop administration of
processing cycles in the system’s all-Win-
dows environment.
AIr uPDATES TruExPoSurE
DATA SoLu TIonS
AIR Worldwide, Boston, added data quality scoring capabilities to TruExposure, a
comprehensive suite of solutions to help
property insurers and reinsurers validate,
benchmark and improve exposure data
used for catastrophe analyses.
TruExposure data-quality scores not
only quantify the potential impact of missing primary risk characteristics on catastrophe loss estimates, but they also indicate
where data improvements will have the
greatest benefit, AIR says.
AIR adds that many insurance/reinsur-ance companies benefit from TruExposure.
The new data-scoring capability in TruExposure was designed to leverage AIR’s industry exposure database and advanced
catastrophe models to provide two scores
essential to understanding and improving
the quality of data used for catastrophe
risk assessment.
For more about synthetic data, search “Making Insurers
Smarter” at www.insurancenetworking.com.
EMC and NetApp offer de-duplication
within their product lines, but take different approaches. There also are third-party vendors that will de-duplicate
data for carriers as a service.
THE DATA ITSELF
By its very nature, insurance data is not
static. Mahoney contends that any
meaningful use of synthetic data is go-
ing to be heavily reliant upon internal
carrier data as a starting point, noting
that an estimated 2.5% of the consumer
demographics information stored in
corporate databases changes each
month. That means a complete turnover
of information is possible every four
years. “Before we move into synthetic
data points, let’s make sure we have our
arms around our internal aspects,” he
says. “If your internal data is flawed, you
are building on sand.”
An indication on the breadth of con-
cern surrounding data quality was evi-
dent in a study released by New York-
based Novarica in November 2010. The
study queried 75 insurance CIOs who
are members of Novarica’s Insurance
Technology Research Council about the
challenges they face leveraging business
intelligence. The results indicated that
the primary issues all surround data
quality, with 50% of respondents citing
significant challenges with data incon-
sistency (data is in different forms) and
more than 60% indicating significant
challenges concerning source system
data quality (the information is inaccu-
rate or invalid).
The remedy to many data quality
woes may be a stringent data validation
and scoring process that mandates a set
of rules to check on data completeness.
Data benchmarking is another tool
for insurers devising a synthetic data
strategy, says George Davis, VP at Bos-
ton-based AIR Worldwide. Benchmark-
ing can highlight subtleties or discrep-
ancies in data when analyzing a
company’s data in comparison to in-
dustry distributions. Davis recalls an ex-
perience when he was reviewing
benchmarking data with an insurer cli-
ent; they realized that many of the
homes covered in a certain book of
business were, in fact, mobile homes.
The insurer was thus forced to concede
that it had either failed to follow its un-
derwriting strategy or had serious
shortcomings in the quality of its loca-
tion data.
