Sources, Uses & Challenges of Statistics in Life & Health Insurance by Prof. Manoj K Pandey, Associate Professor, BIMTECH

1. Prof. Manoj K Pandey,
Associate Professor, BIMTECH
manoj.pandey@bimtech.ac.in
Plot No. 5, Knowledge Park 2, Greater Noida
Uttar Pradesh, India 201306

2. Agenda
 Principles of Insurance
 Broad Classification of life insurance
 Life insurance Industry at a glance
 Data & Sources – National & International
 Limitations of the data
 Challenge of Comparability

3. Insurance Principles
 Insurable Interest - The person / organization must have
interest in the life/lives of the person/s to be insured (Self ,
Lender , Employer)
 Utmost Good Faith - Both the parties in the contract
must reveal the facts truthfully more particularly the
factors linked with risk (Health , Occupation , Residence
etc)
 Indemnity - Purpose of insurance is to compensate for the
loss. Not strictly applicable to life insurance but it remains
a guiding principle.
 Proximate Cause - The loss should be linked to the peril
/ cause for which the insurance has been taken.

4. How to value Life
 The concept of Human Life Value is used to assess the maximum
permissible insurance offer to a human life .
 In simple term it is the sum total of discounted value of all
possible future earnings.
 It requires assumption of the earning life , escalation rate and
also the discount rate. More of a theoretical value.
 However in real life situation it is decided on the basis of income
 Thumb Rule - Annual income * (60 – age )

5. Classification of Life Insurance
 Life Insurance - Term Assurance , Whole Life ,
Endowment , ULIP etc.
 Annuity - Deferred & Immediate Annuity
 Health Insurance - Indemnity based products
offered by general insurance companies and fixed
benefit products offered by life insurance companies.

6. Life Insurance Industry at a glance
 Total Premium Income – Rs 4.18 lakhs Cr.
 No of Policies Sold – 2.64 Crores
 Contribution to GDP - 2.72 % ( 2.15% in 2001)
 Per Capita Premium - $ 46.50 ( $ 9.1 in 2001)
 No of Offices – 10954 ( 2042 in 2001)
 Employment – 2 million (1.2m in 2001 – majority is sales
/distribution )
 No of policies in-force – 34 Cr ( 22cr in 2001)
 No of companies – 24 ( only LIC in 2001)

7. Life Insurance Industry …..
 Market Share LIC – Policy - 76%, Prem. 72%
 Total Benefits Payout – Rs 2.63 lakhs Cr. (56.50% of
premium )
 death claim – Rs 14,000 Cr, Withdrawal / surrender –Rs
90,000 Cr
 Health Insurance Premium – Rs 34,520 represents 27% of
GI premium. CAGR 30%
Source: IRDA Annual Report 2016-17

8. Data Levels
 Base Economic Data – Census ,Mortality , Morbidity , Life
Expectancy , Investment Returns , Overall Economic
Growth etc.
 Insurance Industry Level Data - Mortality , Claims,
Withdrawal , Commission payouts, Management
Expenses, Reinsurance data etc.
 Company Specific Data – Based on companies own past
performance & experience on critical parameters giving
distinctive advantages

9. Data Sources-Base data
 Registrar General of India
 Central Bureau of Health Intelligence (Mortality- 2007)
 NSSO - Directorate of Statistics & Program
implementation (Morbidity- 2004)
 Reserve Bank of India / SEBI Reports
 Planning Commission Reports
 World Bank / IMF

10. Data sources- Industry Level
 Dept. of Financial Services – Insurance Division Reports
 IRDA – Annual Report / Committee’s/ Statistics
 Life / General Insurance Council Reports
 Insurance Information Bureau (IIB/IRDA)
 PFRDA Reports
 Handbooks on Indian Insurance Statistics
 National Health Expenditure Account – MOHFW
 CGHS / ESIS Reports
 Country Specific Reinsurance Companies Reports
 Actuaries / Consulting Companies Reports

11. Company Data
 Mortality / Morbidity data
 Claim outgo data
 Return on investment – long term horizon
 Expense Ratios (Salary / Commission/ Admn.) –
Regulatory Control
 Lapsation / Withdrawal – Dominant risk in past
 Asset / Liability , Solvancy ratio , Annuity Provisions
 Regional Variance in claim pattern –Medical
 Profitability / Loss of a line of business

12. Data- International sources
 World / global Organizations – World Bank , IMF , WHO ,
OECD etc.
 Organizations Representing a group of Countries – EU ,
GCC etc
 Government Organizations – Census Bureau , Health
Department etc. of respective countries.
 Association of Regulatory Authorities - Mutual Co-
operation , NAIC (USA)
 Professional Bodies – IDMA , LIMRA , CII , ABI ,IRMI
 Reinsurance Companies Reports – Swiss Re / Sigma
 Global Actuarial / Insurance / Risk Management
Consultancy Firms – KPMG , IBM , Oracle , Indiastat.com

13. Usages of Data
 Entry in to new market / launch of a new product
 Product pricing (Life) - Mortality (Claims) , Management
expenses, Lapsation , Estimated Investment Return
 Product Pricing (Medical) – Morbidity Data , Cost structure of
service providers & Uses pattern
 Business analysis- Review of business portfolio, Withdrawing /
re-modeling the products
 Valuation Exercise – Asset / Liability , Solvency Margin, Policy
reserving – Outstanding, IBNR & IBNER
 Risk management- Underwriting & Reinsurance Tie-up
 Financial accounting – Regulatory Compliance (IRDA/SEBI)
 Experience analysis- Accident rates, frequency & severity, loss
ratio analysis

14. Analytics & Modeling
 Data mining – Data sampling , cleaning, formatting,
tabulating for meaningful inference
 Data analysis – Estimation Exercise
 Forecasting- Projection of the future trend
 Final Adjustment – Competition, Marketability &
Regulatory)

15. Limitations
 Credibility of the data – Collection & processing. Bulk of
the data are on estimation basis.
 Reliable – Authority / Source / Time frame
 Relevance - Mortality / Morbidity (CRS/SRS)
 Confidentiality – limited sharing
 Most base data are of general nature not linked to
industry requirements
 Manpower expertise – Scarcity of Actuaries / Analyst
 Cost of expert data - Reinsurance data are costly

16. Problems of comparability
 Different data format & Software Structure
 New Vs. Old companies
 New Vs Existing Products
 National Vs International Products
 Different Regulatory Parameters & its effect
 Different Underwriting / Risk Selection parameters
 Data handling capacity & expertise
 Credibility , Reliability & Relevance of the source