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P U B L I C S E R V I C E S Workshop on Microinsurance Insurance and Regulatory Development (IRDA) Institute of Insurance and Risk Management (IIRM) United.

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Presentation on theme: "P U B L I C S E R V I C E S Workshop on Microinsurance Insurance and Regulatory Development (IRDA) Institute of Insurance and Risk Management (IIRM) United."— Presentation transcript:

1 P U B L I C S E R V I C E S Workshop on Microinsurance Insurance and Regulatory Development (IRDA) Institute of Insurance and Risk Management (IIRM) United States Agency for International Development (USAID) Hyderabad 14 & 15 October 2005 Pricing Microinsurance Products An Overview John J. Wipf Consultant BearingPoint Inc. Indian Insurance Reform Project www.bearingpoint.com

2 P U B L I C S E R V I C E S Page 1 Presentation Outline Market research Importance of data Rate components and key determinants Health insurance- additional considerations Modeling techniques Conclusions

3 P U B L I C S E R V I C E S Page 2 Pricing begins with Market Research 1. Conduct client interviews to determine the following: -How much premium can the clients/members afford? -What frequency can they pay? Annual, quarterly, monthly, weekly, etc. -What risks do they face and what are their coping mechanisms? 2. Since premium is limited, have to determine priorities: -What are the risks that they want to insure? -Which benefits do they prefer, and what is the order of preference? -What benefit amounts do they expect? (minimums, maximums) -Who should be covered? Breadwinner, spouse, children? 3. Other info: Attitudes, institutional trust, risk-pooling knowledge, etc. -Philippines clients prefer to own and govern the MI -Cambodia where community trust has been destroyed they prefer that another entity such as an MFI manage and own the MI 4. Confirm demographic profile vs. the database -If no database, use the sample demographics

4 P U B L I C S E R V I C E S Page 3 Importance of Data Credible data is the foundation of MI pricing Data must be complete, consistent, timely, accurate Best: specific data for the target group. -Demographics -Claims experience, etc. -Exposure to risk Without specific data, actuary must rely on -Population statistics (census, WHO population mortality, etc.) -Theory: statistical, risk, life contingencies, etc. -Experience data from similar MI programs (if available) -Reasonable assumptions

5 P U B L I C S E R V I C E S Page 4 Data Accumulation & Management Data must be managed as a valuable resource. Database design: relational database easy to update and expand - databases need to be updated periodically as info requirements change Database design: should be designed with actuarial input. - to make sure that the correct data elements are captured for pricing purposes Documentation: Actuary must know how to interpret the data and how it was accumulated. - this will help to determine the credibility of the data System Requirements: Data gathering rules Consistent formats- eg. Dates, names, primary keys Reasonableness checks- maximums, minimums, menu of choices, etc. Tools and reports for data verification and analysis vs. other sources Data must be warehoused and accumulated- more data, greater credibility

6 P U B L I C S E R V I C E S Page 5 Minimum Data Requirements Institutional and branch information MI participants’ information (DOB, gender, photo, promoter, address etc)- Dependents and beneficiaries information Coverage history for each product -each person, each product… used to reconstruct exposure to various risks Transactions history for each product -to determine who is covered or lapsed, time value of money considerations, etc. Product rules history for each product -used to reconstruct exposure to various risks, for administration reasons, etc. Claims history -for health, record all costs whether covered or not, split by benefits category -need cause of claim; for health use ICD codes Interest rates history -for valuation of savings products, actual rates to credit Others

7 P U B L I C S E R V I C E S Page 6 Price: Main Components Mortality cost- by age, sex, region, etc. Morbidity cost- by age, sex, region, etc. Dropout costs (lapses, surrenders) and reinstatements - may have positive or negative effect on the price Risk premium- provision for adverse deviation from expected claims, or PAD Uncertainty premium- if data isn’t credible Profit- contribution to member equity Expenses- marketing, administration, claims payment, depreciation, etc. Investment earnings- use to discount expected claims and expenses Others- depends on products

8 P U B L I C S E R V I C E S Page 7 Price: Important Factors Product features and benefits, maximums, co-payments Timing and frequency of premium payments -expenses, interest earnings Group size- scale of economy, expenses, risk premium needed, etc. Participation and renewal rates- affects expenses, mortality, morbidity Projected MI growth - affects trends in mortality and morbidity since it affects demographic mix Stability of the group- affects expenses, renewals, etc. Occupations, livelihoods of the members/participants - affects mortality, morbidity Premium collection system -affects expenses, lapses, investment earnings Communication of benefits -affects claims -client satisfaction which in turn affects dropouts and renewals Exclusions and pre-existing conditions- affects claims Inflation- expenses, claims, investment earnings

9 P U B L I C S E R V I C E S Page 8 Health: Additional Considerations Expected claims by benefit: incidence, claim amounts Trends in utilization - pricing should anticipate High inflation rates - need benefit maximums -need to negotiate tariffs. Changes in treatment, advances in technology - need treatment protocols Claims management - determines how well moral hazard is controlled. Co-payments: deductibles, co-insurance -will reduce rates Geographic location -affects access to provider, mortality, morbidity, etc. Rates should be reviewed every 6-12 months if possible

10 P U B L I C S E R V I C E S Page 9 Actuarial Modeling Techniques Models are not a substitute for data. Models enable more effective use of existing data. Models outputs are indicative in nature, are not promises. Can price multiple products, multiple sub-groups at once -example, can use different assumptions by state, by branch, etc. Models parameters such as group demographics are set using existing data and market research Projected expenses, MI growth etc. determined from management input and MI business plan Process: iteratively adjust rates and benefits until a suitable combination is achieved. Model outputs are projected financial results for the MI -expected income statements, balance sheets, cashflow statement, IRR, surplus requirements, expected trends, etc. “ What if” scenarios possible

11 P U B L I C S E R V I C E S Page 10 Conclusions Inputs from marketing research are needed Accurate pricing is only possible with credible data MI must collect and manage data in order to succeed Health is especially challenging to price For health, rates should be reviewed every 6-12 months if possible Pricing is complex; an actuary should assist the MI Actuarial / business modeling techniques work well and should be developed


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