Building alternative MFI model: Economic Times 22nd August 2011

The evolution of microfinance in India can be put in a theoretical context. There is a case of the existence of 'asymmetric information' where the lender has little in his armory to know that the borrower will repay the loan. In the absence of a clear credit evaluation process, this asymmetry will continue to exist. When there is such asymmetry in availability of information, we run the risk of 'adverse selection'. As long as we are dealing with communities that are known to perform, it will work. But, as we scale up this trust model, then we run the risk of selecting the wrong people.

This triggers default and the reason attributed can be high rates being charged in the face of adverse economic conditions for the borrowers. This has a backward linkage with the MFI and lending bank creating financial chaos. The MFIs cannot use strong-arm techniques to recover money. Borrowers now know that if they borrow, they do not have to repay as there is a constituency which will speak for them when the time comes. This raises the issue of 'moral hazard'.

The MFI's Yunus model appeared to be a panacea for the so-called unbankable people and the rate of 30% charged did not raise a stink as these poor people were anyway borrowing from the moneylender at a higher rate. As they had no collateral to offer except peer pressure, banks did not find this social collateral acceptable. With an increase in suicides on account of strong-arm tactics used by the MFIs for non-repayment of loans, regulatory action is being taken to bring this system back on the rails. Is there any alternative way out?

There are some interesting models being experimented with to make MFI credit work. Some of the names that come to mind are Rangde and Milaap - both are startups that have pursued some innovative techniques. The model here aims at targeting investors who are willing to put in money with no expectation of a return on capital or a minimal of 2%. Funds gathered are then lent to MFIs or NGOs that have been carefully screened on the basis of past performance.

The final cost to the borrower varies from 8% (for Rangde) to 12-18% (Milaap). Basically, these startups cover their costs with zero profit. The MFIs add their cost to this and are able to lend money at a substantially lower rate than other MFIs. This model has worked with virtually negligible NPAs and is able to deliver credit at a cost comparable with what, say an SME, gets funds from a bank.


In the earlier system, MFIs had a genuine point of paying substantially high cost for credit from banks, which actually pushed up costs. The lower cost of final credit here is evidently due to sourcing of cheaper funds from investors. Prima facie, there is nothing amiss in this model as the organisations are registered with the RBI and their activities are known. But the issue is whether this model is scalable. Tackling communities within specific geographies is easier to accomplish than widening the canvas.

Where does one get such philanthropic funds from to scale up operations? And further, while the model has worked well so far, it still does not tackle the problems of asymmetric information, adverse selection and the moral hazard. Banks with their superior credit evaluation skill-sets still encounter problems of NPAs in the organised sector where information is relatively more transparent. Logically, it appears that the system has to crack at some point of time, either in flow of funds or NPAs.

The thought which comes here is to address the two issues together: cost of funds and adverse selection. A way out is to first make relatively large sets of funds available for this purpose. The government is evidently the entity that can make these sources available as philanthropy has its limits. Corporates would prefer to create trusts with their names embossed rather than donate anonymously to these organisations.

While there will be some noise on the fiscal front, central and state governments can actually proportionately keep aside these funds for this purpose. Besides, the government is already subsidising agriculture by keeping rates at 7% and taking on the interest rate differential burden of banks. In fact, given the success of entities like Rangde and Milaap, these could be one-time allocations for specific geographies as it may be assumed that the money would largely return to the lending institution.

These funds could be given to either banks or panchayats or organisations like Milaap and Rangde. Banks have the skill-sets of evaluation and are located in rural areas. With funds coming in at zero cost, they could actually lend to MFIs or directly to the borrowers at a low cost.

Panchayats would be another option, given that they actually have knowledge of their people and hence the issues of asymmetric information and adverse selections are simultaneously addressed here. For governments, these are capital expenditures and hence will be analogous to the project expenditures incurred by them. For society, the basic lending cost of say 8-18% charged by banks to the MFIs actually comes down substantially, which can make a difference.

Quite clearly, the MFI space is one of interest and challenge as it offers better living standards to the poor people. Solutions need to be found within the contours of retaining the sanctity of the financial system in which they operate. Organisations like Rangde and Milaap need to be complimented for showing the way and we need to embellish their operational models with strong financial support to ensure that they are sustainable and scalable.