MR Microinsurance_2012_03_29.indd - International Labour ...

470 Insurers and microinsurance
Box 21.3 Financial limitations and liquidity of low-income households
In Chennai, India, a slum dweller, like others in his community, has miniscule
savings of US$2 at his disposal for emergencies. When he has to see a doctor, he
asks his relatives and neighbours for a loan to to pay for medication (outpatient epiepi- sode costs costs are usually US$2 to US$7). If the treatment exceeds US$10, he resorts
to borrowing from a moneylender to fi nance outpatient or in-patient services.
On the basis of observations from several focus groups of urban MFI clients,
low-income low-income households usually have have access access to a a social network to to support minor minor
expenses (US$10). (US$10). Participation in in the social lending of this type of network is an
obligation deeply deeply ingrained in in the the culture of the the community. Despite the the limited
fi fi nancing accessible through through social networks, networks, they are valued valued for for their their fl exibility.
As an alternative, moneylenders may provide emergency relief, but charge
exorbitant interest rates. rates.
Th ese details serve as clues to a product type and product design suitable for a
slum dweller in Chennai. Th e product design, along with information such as
disposable emergency funds, income and WTP, can help check that the
suggested premium is reasonable.
21.2.2 Prudence in utilizing data with limitations
Th e risk premium for any insurance product should be determined from a quantitative
basis. Unfortunately, if the product or the market is new, historical data is
not likely to exist. Th e event frequency, loss and severity, and demographic data
from which assumptions can be derived are often insuffi ciently documented to
permit accurate pricing. Except for a mature product for which a suffi cient
volume of risk data has been properly collected, loss data is often not available,
not readily usable or not as reliable as for a mainstream insurance product. Th e
fi rst step is then to determine the type of data needed and available data sources.
Following data collection, the quality of the data must be assessed and analysed
to set appropriate assumptions.
Data sources can range from public data (e.g. census or academic) to distribution
channel records (see Table 21.1). Th is data is usually not the same as the
claims data maintained by a commercial insurer. For a health product, information
on the average annual family medical expenses or the frequency of a particular
disease may be available, but it would be diffi cult to obtain a complete record
of illnesses aff ecting the target segment. Depending on the type of risk, data
availability will vary. As another example, records on livestock losses are usually
diffi cult to obtain.
Although demographic information on the target segment may be limited,
delivery channels that serve this segment may be a source for this type of data. For