Published on 13-Apr-2010
"We want to be the carrier of choice to our agency partners because we have better relationships and more effective technology. Business intelligence is the foundation for a strong core competency in predictive analytics." - Senior Executive Vice President, Chief Administrative Officer Richard F. Connell
Customer:
Selective Insurance
Industry:
Insurance
Deployment country:
United States
Solution:
Business Intelligence, Smarter Planet
Smarter Planet:
Smarter Insurance
Overview
This case study will explore how the company has realized the benefit of an enterprise data warehouse that uses the IBM Insurance Information Warehouse as well as harnessed IBM Cognos Business Analytics.
Business need:
"The insurance industry is data rich but information poor," says Executive Vice President, Chief Underwriting and Field Operations Officer John Marchioni. "We realized early on that the potential of putting that data in a real-time environment would help drive long-term shareholder value."
Solution:
Selective uses IBM Cognos Business Anlaytics to harness aggregate critical information from across diverse transaction systems – particularly underwriting, claims, billing, agency production and safety management; Manage risk selection and find the right balance between risk and price; Gain deeper insight into share of wallet, customer mix, quality of business, exposures, new business acquisition and lines of business; Identify low performing areas and create action plans to improve performance.
Results:
The company saw its Specialties program grow by 40 percent through the early months of 2009, thanks to information that helped bring competitive products to market.
Benefits:
Through IBM Cognos Business Analytics, Selective’s corporate and regional executives and managers are able to aggregate critical information from various transactions to gain a more comprehensive understanding of Selective’s performance compared to goals and objectives. Reports can be run and sorted across a host of dimensions such as by state and region, strategic business unit, policy type, and line of business.
Case Study
Introduction
Selective Insurance Company of America (“Selective”) is one of seven property and casualty insurance companies held by Selective Insurance Group, Inc. which is rated “A+” (Superior) by A.M. Best. Through independent agents, the insurance companies offer primary and alternative market insurance for commercial and personal risks, and flood insurance underwritten by the National Flood Insurance Program. Selective delivers high-tech, high-touch insurance and risk management solutions to consumers through approximately 960 independent agents in 22 states across the eastern and mid-western United States. Nearly 2,000 employees develop and maintain competitive advantages that
make Selective one of the best regional insurance organizations in the marketplace.
A key to Selective’s success is its superior field model, broad underwriting appetite and deep relationship with its agents. To support these efforts, the company has invested heavily in analytics technology to manage the customer life cycle and safeguard revenues and returns. “We want to be the carrier of choice to our agency partners because we have better relationships and more effective technology,” says Senior Executive Vice President, Chief Administrative Officer Richard F. Connell. “Business intelligence is the foundation for a strong core competency in predictive analytics.”
This case study will explore how the company has realized the benefit of an enterprise data warehouse that uses the IBM Insurance Information Warehouse as well as harnessed IBM Cognos Business Analytics to:
- • Aggregate critical information from across diverse transaction systems – particularly underwriting, claims, billing, agency production and safety management
• Make faster, informed decisions that drive completion of corporate objectives
• Manage risk selection and find the right balance between risk and price
• Gain deeper insight into share of wallet, customer mix, quality of business, exposures, new business acquisition and lines of business.
• Identify low performing areas and create action plans to improve performance
Facing the Challenges
Like all insurance companies, Selective has a tremendous amount of data pouring in from different transaction systems – policy and claims, finance and other areas within the company.
“The insurance industry is data rich but information poor,” says Executive Vice President, Chief Underwriting and Field Operations Officer John Marchioni. “We realized early on that the potential of putting that data in a real-time environment would help drive long-term shareholder value.”
The challenge is always to find the best answer to fundamental business questions. How to get the most granular pricing information? Understanding the renewal book and how to manage it when prices are moving higher? What are the competitive sustainable advantages in the marketplace? What is the competition doing? The challenge is to transform this data into answers to these critical questions.
“In this tough market, we knew our knowledge management strategy could really help us find the right balance between growth and profitability,” continued Marchioni. “It could help us align strategy and tactics to capture and create value in the marketplace. It would also help us unite and manage information to make better, long-term profitable decisions in our book of business.”
Making the Data Available
With these challenges in mind, the company decided to invest more heavily in business intelligence. There was no need to look far for help since Selective already had a strong business intelligence solution; IBM Cognos was being used for reporting and analytics.
“We began using Cognos several years ago for monitoring claims information” says Mike MacMullin, Vice President, Information Strategy. “We had been using IBM Cognos
primarily for tabular reporting. We opted to upgrade to the latest version to accommodate more users, more data, more capabilities and more departments.”
Selective’s users had become more sophisticated in their handling of business analytics and their appetite grew for additional information. The time was right to make business
analytics insight available to more people, in more forms and for daily consumption.
As a starting point, the company employed the IBM Industry Models for the Insurance Information Warehouse. The models helped Selective standardize its environment and
implement its information sharing initiatives faster and more reliably. One of the keys to success from the outset of this phase of the project was having a clear vision of data cleansing and modeling requirements.
In parallel, Selective began building the reporting side of each area being developed in the warehouse. This allowed them to immediately begin offering users of the information analytics such as scorecards, dashboards and other reports as soon as each section of the warehouse was complete. These tools, delivered to the desktop, can provide an easily understood visual of information key to decision making for underwriting, claims and many other areas.
The most powerful underwriting screen in Selective’s Commercial Lines underwriting system is the Decision Support Screen (DSS). The DSS identifies key data elements from the data warehouse and presents an underwriter with critical information needed to underwrite and price an account. It shows billing history, experience with Selective, loss ratio, safety management reports and a link to the claims inquiry system, giving the specific claims information behind the numbers. It also provides agency information and one and three-year growth and profitability numbers. Most important, the predictive model score is provided as well as links to relevant information behind the score.
“Predictive modeling is not unique to Selective,” says Marchioni. “But what is unique is the combination of our highly experienced underwriters and the data rich environment in which they make astute decisions. Our models help ensure that their decisions are precise and comprehensive.”
Benefits Realized
Through IBM Cognos Business Analytics, Selective’s corporate and regional executives and managers are able to aggregate critical information from various transactions to
gain a more comprehensive understanding of Selective’s performance compared to goals and objectives. Reports can be run and sorted across a host of dimensions such as by state and region, strategic business unit, policy type, and line of business. With more information and analysis, decisions can be made faster and with greater confidence.
These analytic capabilities allow business users from across the organization to more effectively pinpoint trouble spots within their book of business. They can also implement more timely, corrective underwriting and safety measures.
For instance, the company saw its Specialties program grow by 40 percent through the early months of 2009, thanks to information that helped bring competitive products to market.
“Now that we have the ability to run business analytics at the state, line of business or perhaps the agency level,” says Senior Vice President of Field UW and Information Strategy Brenda Hall. “Our business users can run their own reports to support the development of strategies to improve performance, customer satisfaction, retention and growth.”
Another example of the analytic tool supporting shrewd business decisions was in the case of a certain hotel segment that was underperforming. Using business analytics, management discovered that the newer business travel hotels carried a higher claims load due to more relaxed building codes and safety management procedures. The organization responded by implementing new underwriting guidelines and requirements – mandating that new business travel hotels employ seasoned management, maintain an AAA rating, and practice more formal risk and safety management procedures.
Agency Relationships
IBM Cognos Business Analytics has also been a useful tool to help Selective effectively manage agency performance and profitability. Through multi-year agency performance trends reports, regional managers are better able to identify which agencies are either not meeting key targets or are in danger of missing them. They can then analyze results with individual agents, isolate the causes and develop a formalized agency profitability improvement plan, or APIP.
For example, one agency was not meeting anticipated growth objectives despite having a high-caliber agent. An analytical review revealed that the automobile line of business was underperforming. An APIP was developed that balanced a targeted approach to re-underwriting automobile coverage together with an aggressive new business growth strategy. Since then, the agency’s commercial lines book grew from $4 million with a 115 percent combined ratio, to $11.4 million and a 73.7 percent combined ratio. Selective also wanted to put the power of performance management in the hands of agents.
“We talked to our agents to understand their workflows and processes,” said Marchioni. “We then set to work building automation that allows them to issue business in their offices in real-time. We have better underwriting templates and a pricing structure that helps simplify the process. We offer them predictive modeling capabilities and a book of business segmentation that helps them make decisions with confidence.”
Another example of supporting their agents is the Leads Program which was developed to help grow an agents business quickly by providing prequalified accounts. By proactively scoring accounts using predictive modeling and business segmentation, agents have confirmed new business ready to write. Selective looks for coverage advantages and competitive pricing in prequalified accounts and ensures that producers have all they need to close the business.
“We’ve built a field model that hinges on agency relationships,” continued Marchioni. “We provide operational and technical efficiency that empowers agents to make sound underwriting decisions. When you link our precision pricing tool with our agency management specialists – the agent has everything they need to be successful.”
Next Steps
As Selective continues to expand its use of IBM Business Analytics it is already experimenting with mobile device reporting. With Cognos Mobile, Selective will be able to extend the value of its IBM Business Analytics platform by providing users with access to timely, secure and personalized information on their mobile devices and operating systems.
Just as IBM Cognos’ platform is systems and data agnostic, Cognos Mobile is equally flexible delivering to mobile devices. With the publish-once-consume-anywhere attributes of this solution, Selective will be able to arm home office and field managers with business intelligence wherever they are.
Summary
The insurance industry will be reshaped and won by those innovators who can develop more flexible products, deliver new breakthrough services, and create new business models and operational efficiencies. Advances in business intelligence and analytics are helping Selective to tailor products to address changing customer demographics, reduce underwriting risk and fundamentally alter traditional industry boundaries.
“With IBM Cognos Analytics delivered directly to their desktops, Selective executives and managers are now more empowered to make quick, accurate decisions that are critical to helping the company outperform the competition,” says Hall. “Our analytics capabilities, our ability to deliver realtime underwriting information to the underwriters’ desk, and our sound agency relationships collectively ensure that we are continuously improving our performance and driving optimal results in the long term.”
For further information or to reach a representative: www.ibm.com/cognos/insurance.
Products and services used
IBM products and services that were used in this case study.
Software:
Cognos 8 Business Intelligence, Cognos Mobile
Legal Information
© Copyright IBM Corporation 2010 IBM Canada 3755 Riverside Drive Ottawa, ON, Canada K1G 4K9 Produced in Canada March 2010 All Rights Reserved. IBM, the IBM logo, ibm.com, Cognos and TM1 are trademarks or registered trademarks of International Business Machines Corporation in the United States, other countries, or both. If these and other IBM trademarked terms are marked on their first occurrence in this information with a trademark symbol (® or ™), these symbols indicate U.S. registered or common law trademarks owned by IBM at the time this information was published. Such trademarks may also be registered or common law trademarks in other countries. A current list of IBM trademarks is available on the Web at “Copyright and trademark information” at www.ibm.com/ legal/copytrade.shtml. Other company, product and service names may be trademarks or service marks of others. This case study is an example of how one customer uses IBM products. There is no guarantee of comparable results. References in this publication to IBM products or services do not imply that IBM intends to make them available in all countries in which IBM operates. Any reference in this information to non-IBM Web sites are provided for convenience only and do not in any manner serve as an endorsement of those Web sites. The materials at those Web sites are not part of the materials for this IBM product and use of those Web sites is at your own risk. YTC03018