Insurance contracts to lower income households (micro-insurance) are typically for one year. This implies that when the contract expires, the household needs to renew the purchase for the next year. It is intuitively appealing to consider that micro-insurance is truly an effective means of smoothing consumption when households continuously renew their contract. The question arises: do households choose to repurchase micro-insurance and enjoy continued cover? In Sane and Thomas (2016), From participation to repurchase: Low income households and micro-insurance, we evaluate this question for life and accident micro-insurance, along with what drives the repurchase. We also ask how long it takes customers to repurchase once the policy has expired. We especially focus on two such drivers: access to credit and wealth.
We use data from the IFMR Rural Channels and Services Private Limited (IRCS) which implements the Kshetriya Gramin Financial Services (KGFS) branch-based model of distributing financial products across India. KGFS branches distribute two insurance products: the term life (TLI) which covers mortality risk, and the personal accident insurance (PAI) which covers mortality risk or permanent disability risk of customers arising due to accident. The data includes demographic and wealth information for 132,000 micro-insurance customers whose first policy expired between March 2011 and March 2014. The data also includes information about micro-credit contracts between KGFS and these customers prior to the purchase of the micro-insurance. To this dataset we add rainfall data gathered for the relevant districts and time periods, to indicate if the policy expired in a period when rainfall was scanty, versus when rainfall was normal.
We find that 65 percent of the sample renewed their insurance policy at least once, after their first policy expire. Five characteristics stand out:
First, there is a large difference in re-purchase probability (almost 33 percent) between the group with a micro-finance (Joint Liability Group) loan before the original purchase of the insurance policy, compared to those without a JLG loan. What could be the reasons?
When we examined the date of insurance repurchase and the take-up of a JLG loan, we find that 17 percent of those who renew insurance have taken a new JLG loan within 7 days of the insurance purchase, and another 18 percent have taken a new loan within 14 days of the insurance purchase. This suggests that while some part of the loan may be used to pay the insurance premium, it does not appear to be an over-whelming driver for the purchase, at least for two-thirds of those who renewed insurance.
A popular voiced perception is that life or accident insurance acts to protect the credit payments in case the borrower dies or suffers a debilitating injury. In this case however, most lenders would waive repayment of loans in the event of death of the debtor, giving customers little reason to purchase insurance to ensure repayment. Further, the insurance producer has nothing to gain from the point of view of repayment. There is little incentive for either intermediary to push the insurance product only to loan clients.
However, a common financial intermediary for credit and insurance may be important in other ways. Since credit and insurance are offered in the same branch, a higher demand for credit may translate into higher repurchase of insurance as customers visit the branch more frequently, and get more exposed to other financial products, and are perhaps able to build trust about the financial service provider.
Finally, there could be unobserved differences between those who have chosen to take a JLG loan and those who have not. It could be these differences that are driving the result, except that we are unable to test for this in the present data-set.
A second feature is that when the policy expires in months with scanty rainfall, the repurchase probability reduces by almost 7 percent. This is statistically significant at 1 percent. It suggests that collecting premiums during a lean period (caused by poor rainfall) restricts the ability to pay premiums.
The third feature is that repurchase probability rises with assets, but falls for those in the highest asset quartiles. This suggests that individuals only consider the purchase of insurance when they do not have enough buffer stock wealth. Households primarily demand life insurance when they lack accumulated reserves, or wealth, for self-insurance.
A fourth feature is that the largest number of repurchases occur within the first one to two months of expiry. Repurchases then continue to fall further after 12 months. This implies that if an insurance customer does not repurchase her policy within 12 months of expiry, she is unlikely to do so after. This helps to guide policy on improving insurance uptake: the first few months are the right time for an intervention to improve repurchases.
The fifth feature is that only 28 percent of those who repurchase the policy, increase the amount of cover purchased. We also find that 47 percent of those who increased their cover had gone from having one policy (accident cover, for example) to purchasing both policies (accident and term life cover).
Improving insurance participation of low-income households has become an important objective in the access to finance movement. The market for micro-insurance products will mature once people continuously purchase these products, and also make decisions on the sum assured purchased. Our research on understanding repurchases can provide inputs to the design of government programs as well as private sector initiatives. This is also the start of what we hope is an exciting research agenda on the drivers of sustained participation in micro-insurance.
Sane and Thomas (2016), From participation to repurchase: Low income households and micro-insurance, FRG WP. http://ifrogs.org/releases/SaneThomas2016_microInsurance.html