Transcript Implementation

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Commercial Insurance
Product Development
Justin VanOpdorp ACAS, MAAA
GE Commercial Insurance
Introduction
Product Development Framework
• Idea Generation
• Exploration
• Implementation
How would I do it?
Product Development
Idea Generation
Idea Generation
• Comparison/Benchmarking of Competitors
• Customer Interviews
• Idea Generation Teams
• Data mining
• Claim Audits
• U/W Reviews for Emerging Risks
• Internet Research
• Employees
Where do all of the ideas come from?
Initial Idea
•
I have an idea:
•
The main concern with this idea:
•
This is a good idea because:
•
One way to handle this concern:
•
The main benefit of this idea:
•
My next step:
Source: Idea Champions, “Banking on Innovation”
Evaluation
How will management wade through each idea?
• Feedback
• Qualitative Approach to Product Evaluation
Tools for idea evaluation
Idea Feedback
LCS Approach
• Likes
• Concerns
• Suggestions
Idea Survival versus Idea Killing
Source: Idea Champions, “Banking on Innovation”
Sc
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3
Qu
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2
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Weight
Product 1
Product 2
Product 3
Qu
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1
Product Evaluation
0.5
1
3
5
0.2
5
1
3
0.3
3
1
5
2.4
2.0
4.6
Keeping Score
Idea Generation
No one best approach
• Success for one does not guarantee success for another
• Utilize most promising ideas and modify to meet
organization’s needs
Steal the best, improve the rest
Product Development
Idea Exploration
Ownership
Step #1: Identify an Owner
• Passion
• Leader
• Driver
• Organized
Projects without owners lack focus
Gathering Information
Quasi Due Diligence
• Product Definition
• Data Gathering
• Data Analysis
• Recommendation
What do I need to know?
Gathering Information
Input from all functional areas
• Marketing/Sales
• Accounting
• Claims
• Risk Management
• U/W
• Actuarial
• IT
• Policy Processing
• Legal
• Other Functional Areas
• Finance
Expertise and team environment important
Product Definition
Do you know the answer?
•
Who are my experts?
•
How will premiums be billed and collected?
•
What are the specifics of the product?
•
How will we rate, quote and issue polices?
•
Who are the target customers? How large is the
target market?
•
What policy forms and rates will be used?
•
Does competition exist?
•
Internal or external claims handling?
•
What will my competitive advantage be? Price,
service, innovation?
•
Are there any regulatory considerations?
•
What data will be collected and stored?
•
What distribution channel will be used to market and
•
sell the product?
•
Who will be responsible for underwriting the risks?
•
Which IT system(s) will we use?
•
What are the risks of this product?
What information do we need to monitor?
Be willing to ask a simple question
Data Gathering
Frequently limited internal data to support actual product.
• Internal or External Relevant Product
•
Probably the most utilized
•
Competitor filing, Bureau Data, Adjusted Internal Data
• Internal or External Proxy
•
Most overlooked, Good for reasonableness checks
•
Non-related products, Internet, Publications
What sources of data are available?
Data Analysis
Analysis generally consists of many subjective assumptions due to limited
information and data
• Understand the source of the data
• Make appropriate adjustments and relationships
• Quantify risk loads for imperfect information
Actuarial Creativity
Recommendation
Provide Recommendation to Management in a consistent
format
• Minimize turnaround time
• Meets requirements of management
• Ease of Use
Consistency
Product Development
Implementation
Implementation
• Infrastructure
• Communication Plan
• Compliance
• Program Introduction
• Monitor
Develop Infrastructure
•
Distribution Channel
•
Policy Forms and Rates
•
Underwriting Risk Selection
•
Policy & Premium Processing
•
Claims
•
Data Collection Plan
•
IT Systems
•
Billing and Collections
•
Financial Reporting
Foundation of Success
Additional Steps to Implementation
Communication
Introduction
•
Internal
•
Pilot
•
External
•
Achieve Goals prior to further
release
Compliance
Monitor
•
Regulatory Filings
•
Production
•
Legal Entities
•
Profitability
Execution
Product Development
Conclusion
Principles for Success
• Management Support
• Ownership
• Collective Project
• Infrastructure
• Expertise
• Data Collection
No secret recipes