NGO Experiences in Implementing Insurance Products in Agriculture in Bangladesh Professor M. A. Baqui Khalily Executive Director Institute of Microfinance July 5, 2014 Malaysia
Three Basic Arguments 1. Disaster Risk Reduction strategies should encompass insurance and non-insurance interventions 2. Traditional insurance markets are not appropriate for poor households characterised by vulnerable economic conditions, non-affordability, nonaccessibility and non-acceptability 3. Community-based insurance mechanism along with non-insurance interventions of community organisations like NGOs/MFIs is more appropriate. The draft BangladeshNational Insurance Policy 2014 and Micro Credit Regulatory Authority Act recognise micro insurance as a product of NGO-MFIs.
Disaster Risk Reduction Strategies Disaster Risk Fund Used for smoothing the process of stability and back to predisaster state; In Bangladesh, a DRR fund of USD500 million has already been created with contribution of PKSF, Government and contribution of 10 percent of surplus of the NGO-MFIs. Targeted to make a Fund of USD 5 billion. Ex-ante access to finance Our three empirical studies covering lood prone-areas, cycloneprone areas; and hilly-region clearly show that ex-ante access to finance of the households affected by flood or cyclone has higher ability to cope because of higher amount of savings, assets and off-farm economic activities. Insurance Mechanism Transfer of risk to insurance companies; Transfer of risk to NGOs/MFIs
Traditional insurance market not appropriate for vulnerable HHs Traditional insurance companies have several choices: Do business with high and middle income HHs (largely still uncovered) at low amount of risk and low transaction cost (maximizing profit); Expand horizon of business to low-income or vulnerable HHs at high risk and high transaction cost (minimize profit or incur loss) Cross-subsidize second group with the gains from covering the first group or with subsidy from government (not an option for profit maximizing companies) BUT what should be their choice?
WHAT should be the behavior of poor HHs or members or MFIs? Poor HHs will not have access to traditional insurance for several reasons: Non-affordability (because of high cost) Non-accessibility (because of the screening behavior of insurers) Non-acceptability (because of moral hazard problem on the part of insurers) Principal-Agent model has not been encouraging for NGO- MFIs. InM experiment on implementation of pilot health insurance product with principal-agent model reveal: MFIs did not find insurance commission as attractive; MFIs do not have any role in claims settlement but have lots of liabilities because of their associated regular ties with clients; Higher risk for core NGO-MFI activities in the event of default on the part of insurer in claim settlement
NGOs/MFIs provide alternate mechanism: perhaps better! 1. Risk reduction strategies: Awareness building Skill development training Increase in income, savings and assets creation through IGA financing and savings mechanism (flexibility introduced since 1998) 2. Risk transfer mechanism targeting HHs and individual loan-financed activities: Informal insurance (risk coverage of lenders and borrowers)) Formal insurance (under enacted regulatory framework) 3. New evidence of formal insurance by MFIs in Bangladesh.
Formal Micro-insurance Selected number of MFIs implement selected number of micro insurance products under Developing Inclusive Insurance Sector Project of PKSF financed by ADB: MI Products of DIISP Life Insurance Livestock Insurance (Beef Fattening) Health Insurance & Health Service Endowment Life Term Life Credit Life Health Insurance Health Service In-patient Care Hospital Cash Benefit Primary Care Paramedic Service Health Loan
Credit Life Insurance - Results so far Risks Covered Eligibility Benefit Term Credit life insurance Death of the borrower or spouse/main earning member of the household. Only the borrowing members of MFI and their family. Waiver of outstanding amount of the borrowed loan and a lump sum of BDT 5,000 for funeral cost. Until the end of loan cycle (Usually 1 year or less) Premium Structure Not more than 0.7% of the loan amount + BDT 40 Premium payment Mode Paid at the start of a loan 1.3 million received actuarial based credit insurance service up to January 2014.
Livestock insurance results so far Livestock insurance Risks Covered Eligibility Benefit Term Premium Structure Premium payment Mode Death of the Cattle. Only to borrowing members of beef fattening program. Waiver of the full amount of the borrowed loan. 6 month 10 month (actual loan cycle) 1. Not more than 0.7% of the loan amount + BDT 20 as part of the Para-vet fee. 2. For covering the risk of member s death, 0.3% premiums would be added. Paid at the start of a loan
Low mortality rate of livestock It was found in benchmark survey that cattle mortality rate was 5.43% in Bangladesh; The mortality rate of cattle was found 0.33% under the compared to 0.49% under the Beef Fattening program of PKSF; A total of 112,821 beneficiaries received loan in 2013 to procure 124,669 cattle for beef fattening program. Total premium collected in 2013 was USD 233,609 and USD 98,561 was paid to settle 408 claims in 2013. Low mortality rate of cattles because: MFIs provide veterinary services to the poor farmers, Beef-fattening program of short duration, and Better rearing management.
Paramedic services as a tool of reducing healthrelated risk Paramedic Service Paramedic Service has been introduced as a preparatory step for providing Health Insurance Eligibility Benefit All the microfinance borrowers and their family members; Paramedic provides health awareness and basic health services; Fee MFI can project the cost of paramedic, the supplies needed and the cost of the facility divided by the number of policyholders that are paying the premium. Or, MFI can bear the cost of Paramedic service from the service charge of microcredit. In January 2014, a total of 11,873 members received treatment from the paramedics; 485 patients were referred to doctor/hospital by paramedics; and Awareness campaign covered 25,197 target people.
Hospital cash benefits. Risks Covered Term Premium & Benefit Structure Premium payment Mode Hospital Cash benefit If hospitalized for more than 24 hours, a pre-decided benefit would be provided for each day hospitalized up to a maximum of 30 days for a family, excluding the first day. One year from policy purchase date. Benefit/per day (BDT) Premium/Year (Highest 5 Members) (BDT) One shot payment at the of policy purchase Premium/Year (Per Additional Members) (BDT) 400 500 100 300 375 75 250 300 60 200 250 50
Reinsurance approach Greater risk is absence of reinsurance services To cover this drawback, PKSF has been working to create a Covariant Risk Fund (CRF) as an alternative to reinsurance to be contributed by PKSF, participating NGO/MFIs and donors; According to actuarial estimation, some USD 6 million would be sufficient to one catastrophy and maintain adequate capitalization. InM and PKSF are planning to create historical data health shocks, crop loss, loss of cattles from different survey data of InM and systematic data collection from PKSF projects at the farm and off-farm household levels. It will set the stage of greater accuracy in actuarial estimation of risk.
What indicators that can be used to assess insurance effectiveness (assuming multi-functioning MFIs)? Coverage-related indicators: Number of households/members/borrowers targeted Number of households/members/borrowers covered Number of households/members/borrowers received training and related services Outreach-related indicators: Number of NGO-MFIs and its branches implementing insurance Number of staff associated with and trained Operation-related indicators: Number of policies issues Number of claims received and settled Amount of annual and accumulated premiums received Amount of annual and accumulated claims settled Efficiency-related indicators: Duration of claims settlement Number of policies per staff Average amount of premium and overhead cost per staff associated with insurance Dependency on government subsidy