SWOC DAMA 2008 Showcase at American Modern Insurance

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SWOC DAMA 2008 Showcase at


American Modern Insurance

February 21, 2008

Showcase Agenda


Background/Business Case

20 minutes Sandy Wagner



Data Warehouse


AIIM

20 minutes Latha Subramanian



Data Model


AIIM

20 minutes Duke Ganote



Information Management


AIIM

20 minutes Dan Daly



Q& A


Duke/Sandy/Latha/Dan

20 minutes

American Modern Insurance

Company Background




Founded in 1938 as a consumer finance company



Provider of highly focused, specialty insurance products



Positioned to grow into a multi
-
billion dollar organization



Entrepreneurial spirit & deep commitment of employees



Approximately 1200 employees country
-
wide, with 1000
employees in eastern Cincinnati area (Amelia)


American Modern Insurance

Company Background



The organization believes that the strategic
deployment of technology can help it achieve, and
sustain, a competitive advantage.




As stated in its Operating Principles, “Our
investment in information technology is part of a
carefully planned strategy to ensure that American
Modern's company
-
wide infrastructure is among
the most advanced in the specialty insurance
industry.”

American Modern Insurance

Initiative Background

In 2000, American Modern embarked upon
long
-
range initiative, coined “modernLINK,”



Business and IT collaboration



Business case and funding


Three prongs:



Web
-
enable insurance transaction processing



Replace aging legacy processing systems



Develop a Knowledge Management architecture

American Modern Insurance

Business Case


The anticipated returns of this business case were:


20% annual increases in directly
-
attributed new
business


37% of Policy and Partner Administration moved from
existing internal units directly to point of service


25% improvement in current Product Review and
Management cycle time


21% improvement in Product Filings cycle time


2% reduction in total loss ratio directly attributed to
modernLINK initiative

American Modern Insurance

Business Case


These returns would yield a significant recurring annual
benefit through additional premium, increased profit, and
decreased expenses



Almost 50% of these benefits would be attained through
better knowledge/data management, richer data
segmentation, and improved data and risk selection



John Hayden, President and CEO, American Modern
states:


We must have accurate data about the risks we insure today if
we are to ever be successful in establishing The Right Rate for
Every Risk we choose to insure in the future.

American Modern Insurance

Knowledge Management Roadmap


Enterprise Data Model


Operational Data Store


Enterprise Data Warehouse


Themed analytic data marts


Enterprise reporting portal


Metadata management


Data Stewardship

American Modern Insurance

Knowledge Management Results


Business users can:


Make informed decisions


Respond quickly to new business initiatives


Create new opportunities


Business users are:


Moving from data collectors to data consumers


Asking “why” instead of “what”


American Modern Insurance

Knowledge Management Results


Retention


Joe David.

In the last four years, we have leveraged the
corporate reporting tools to develop a series of targeted strategies
that have allowed us to improve retention by nearly eight points,
which equates to annualized premium of nearly $60 million




Claims. Integration of 3
rd

party Claim data
-

Heather Bolyard.
This
one
-
month sample of data for one material has identified a potential
indemnity reduction of $70,000.




Reserving


Gene Stetler.
The new Loss Reserving data store from
the Enterprise Data Warehouse has enabled process efficiencies,
thus allowing us to predict our reserving needs with accuracy.



Product


Kevin Randall.
The implementation of American Modern's
data warehouse has been a significant part of the successful launch
of the company's right rate for every risk initiative

American Modern Insurance

2007 Awards and Recognition

In 2007, American Modern received two awards
from Computerworld:



Laureate

-

The laureate status for the Enterprise Data
Warehouse presented at the Carnegie Mellon
Auditorium in Washington D.C


June 2007



BI Award

-

Best Practices in Business Intelligence in
the category “Creating an Agile BI Infrastructure”
presented in Las Vegas, NV


September 2007

Showcase Agenda


Background/Business Case

20 minutes Sandy Wagner



Data Warehouse


AIIM

20 minutes Latha Subramanian



Data Model


AIIM

20 minutes Duke Ganote



Information Management


AIIM

20 minutes Dan Daly



Q& A


Duke/Sandy/Latha/Dan

20 minutes

Enterprise Data Warehouse


Create an implementation roadmap


Content scope


January 1998 thru present


All products loaded over 5 years



Implement “value” after each iteration


Loss Cost, Retention, Loss Triangles



Establish Data Stewardship
-

2004

Enterprise Data Warehouse

The data warehouse will support:

Loss

Cost Analysis

Retention

Analysis

modernLINK


Reporting

Profitability

Analysis

Data

Warehouse

Underwriting

Analysis

Product

Pricing

Analysis

Financial

Analysis

Data Warehouse Value

MH


Loss Cost

SB

Loss Cost

MC

Loss Cost

Retention

UVRC

Pricing / GLM

Loss

Triangles

modernLINK

MH PIF

mLINK


vs. Legacy

Retro


Studies

Mapping

Renewal

Reporting

FID

MSB

CAT Analysis

Cancellation

Reporting

Address

Data

Agency

Profile

Analysis

Claims

Liability

Partner

Experience

Reporting

Data Warehouse Statistics

1997 policies used to seed warehouse:
~700,000


Total policies Jan 1998 thru Jun 2007


Total units Jan 1998 thru Jun 2007


Average Number of Coverages per policy: 5


Average number of policies in
-
force per
month: 800,000


Average number of claims per month: 8,000


Data Warehouse Benefits


Single version of the truth



Data integrated at the lowest level



High
-
end hardware platform



Codes translated to “English” terms



Resolve source system problems



Data quality review and correction



Integration of external information



Data Mart Themes


modernLINK quote


Exposure


Retention


Experience


Loss Cost


Claims


Underwriting

Technology Enablers….


IBM RS6000 AIX processors



EMC data storage



Oracle DBMS



COGNOS for reporting utilizing query,
report, mapping and analytical tools



Websphere Portal



LDAP for single sign
-
on



Showcase Agenda


Background/Business Case

20 minutes Sandy Wagner



Data Warehouse


AIIM

20 minutes Latha Subramanian



Data Model


AIIM

20 minutes Duke Ganote



Information Management


AIIM

20 minutes Dan Daly



Q& A


Duke/Sandy/Latha/Dan

20 minutes

Data Model


Provides a common, integrated way for
the corporation to view and to
communicate about its business



Allows the business to drive the system



Creates standard
definitions/documentation



Provides structure to new development
projects

Enterprise Data Model

People

Places

Things

Insureds

Operators

Lienholders

Claimants


Geography

Address

Quotes/Policies

Claims

Coverages

Accidents/Violations

Homes/Vehicles

UW rules

Makes/Models

Jump Start Enterprise Data Model

Acord Standards

Generic Model based on Insurance Industry Practices

AMIG Enterprise Data Model

AMIG Specific Requirements

Integrated View:

Common Data Definitions

Across business

Manufactured Home

Site Built

Motorcycle

Motor Home

Travel Trailer

Classic Auto

FID

Commercial

Data Model Benefits


Foundation for:



modernLINK rate & quote applications


Data warehouse/data mart/analytic
design


mLP3 Operational Data Store (ODS)
design


New projects simply add to the model


Insurance score


Claims liability


Development of data standards and a
common “language”

Inmon, Initially


Data warehouse built using Inmon
approach:


Source

(non
-

relational)

Data

Warehouse

(normalized)

DataMart

(star)

End of

month

End of

month

“Corporate Information Factory Components”,
W. H. Inmon

http://www.inmoncif.com/view/26

Conformance


Conformed Dimensions:


Data

Warehouse

(normalized)

Loss Cost

DataMart

(star)

Conformed

Dimensions

Pricing

DataMart

(star)

Retention

Mart

(star)

“The 38 Subsystems of ETL”,
Ralph Kimball

http://www.intelligententerprise.com/showArticle.jhtml?articleID=54200319

Challenges


Multiple sources


Latency


Stewardship

Multiple Sources

OPPORTUNITIES
:



Daily claims/catastrophe feeds



3rd party Claim data (claims cost
standards)



Huon (an new Insurance ERP)



Munich RE (pending merger with
reinsurer)

Multiple Sources

RESPONSES
:


Pull data
: generally from relational
DBMS, e.g. DB2, Informix, SQL
Server



Push data
: generally from non
-
relational DBMS: DMS II (Unisys)




Latency Changes

OPPORTUNITY
: Daily information



Catastrophe reporting; e.g. Hurricane
Katrina 2005, “Fab Four” of 2004



Financial Institutions requesting daily
account information on insureds.




Latency Changes

Source

(OLTP)

CATastrophe

DataMart

(star)


Staging

Area


daily

daily

Daily

Conformed

Dimensions


RESPONSE
: Kimball architecture

“Kimball Design Tip #34: You Don’t Need an EDW”,
Ralph Kimball

http://www.kimballgroup.com/html/designtipsPDF/DesignTips2002/KimballDT34YouDontNeed.pdf

Latency Changes

Kimball Architecture

“The staging area is exactly like the kitchen in a
restaurant. The kitchen is a busy, even
dangerous, place filled with sharp knives and hot
liquids. The cooks are busy, focused on the task
of preparing the food. It just isn't appropriate to
allow diners into a professional kitchen or allow
the cooks to be distracted with the very separate
issues of the fine dining experience. ”

Two Powerful Ideas: foundations for modern data warehousing,
Ralph Kimball

Sept 17, 2002: http://www.intelligententerprise.com/020917/515warehouse1_1.jhtml

Data Stewardship

OPPORTUNITY
:


Daily instead of monthly reference data
needed. However, for example, no
daily

system of record

automated for:



Claims Adjusters



Catastrophe name/details




Data Stewardship

RESPONSE
:



Data stewards maintain master data /
system of record.



Over night ETL uses master data for
building dimension.



Referential integrity always enforced with
fact table, so data stewards cannot “delete”
required for integrity.

Showcase Agenda


Background/Business Case

20 minutes Sandy Wagner



Data Warehouse


AIIM

20 minutes Latha Subramanian



Data Model


AIIM

20 minutes Duke Ganote



Information Management


AIIM

20 minutes Dan Daly



Q& A


Duke/Sandy/Latha/Dan

20 minutes

Information Management Benefits


Single BI Architecture


Provides a consistent view of our Corporate Data


Allows for common product training & support


Volume license pricing provides flexibility and
cost savings



Converting Data Collectors to Information
Consumers


Corporate Portal Integration


Delivering specific information to specific
business users


Providing pre
-
emptive alerts to users based on
specific (data) events


Single BI Architecture


(Consistent View, Common Training & Support & Volume Pricing)


Using Cognos 8.2 for our Enterprise
Reporting Portal


Report Studio, Analysis Studio, Query Studio,
Event Studio, Metric Studio



All Cognos Content Provided in Themes


modernLINK quote


Exposure


Retention


Experience


Loss Cost


Claims


Underwriting

Single BI Architecture


(Consistent View, Common Training & Support & Volume Pricing)

Converting Data Collectors
to Information Consumers


Corporate Portal Integration

Converting Data Collectors
to Information Consumers


Delivering specific content to specific users


‘Bursting’ Experience & Exposure information
directly to our Business Partners (Agents)

Converting Data Collectors
to Information Consumers


Providing pre
-
emptive alerts to users
based on specific (data) events



So What’s Next?


Spend more time
executing strategy
& less time
gathering data



Manage to
Corporate
Scorecards /
Performance
Metrics



Showcase Agenda


Background/Business Case

20 minutes Sandy Wagner



Data Warehouse


AIIM

20 minutes Latha Subramanian



Data Model


AIIM

20 minutes Duke Ganote



Information Management


AIIM

20 minutes Dan Daly



Q& A


Duke/Sandy/Latha/Dan

20 minutes

Q & A session

Wrap Up



Enterprise Data Warehouse now in its 7
th

year



Business units embrace the DW



Holistic view of information in one place



Next phase: deliver similar functionality to our external
business partners



Our case study has been placed in National Archives



The copy of the case study can be found on the following
web page:
http://www.cwhonors.org/viewCaseStudy.asp?Nominatio
nID=54

SWOC DAMA 2008 Showcase at


American Modern Insurance

February 21, 2008