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g 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 o re 3 Qu es tio n 2 tio n Qu es Weight Product 1 Product 2 Product 3 Qu es tio n 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