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Knowing Me Knowing You, as seen in Indian bank lending

Summary:
Ah, I see we share many of the same social characteristics?So yeah, my subconscious is giving you a fast track to validation. Or, perhaps more charitably, I am simply better able to gauge your creditworthiness via “soft” private information? Either way, you can have a loan.That’s a crude summary of a recent paper by Raymond Fisman, Daniel Paravisini, and Vikrant Vig which looked at a large state-owned bank in India where they had access to caste and religious affiliation data, and where, crucially, an “explicit officer rotation policy among branches provides variation in the matching between lenders and borrowers”.With our emphasis:We find strong evidence of preferential in-group treatment. In the baseline results we define two individuals as belonging to the same group when both are

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Ah, I see we share many of the same social characteristics?

So yeah, my subconscious is giving you a fast track to validation. Or, perhaps more charitably, I am simply better able to gauge your creditworthiness via “soft” private information?

Either way, you can have a loan.

That’s a crude summary of a recent paper by Raymond Fisman, Daniel Paravisini, and Vikrant Vig which looked at a large state-owned bank in India where they had access to caste and religious affiliation data, and where, crucially, an “explicit officer rotation policy among branches provides variation in the matching between lenders and borrowers”.

With our emphasis:

We find strong evidence of preferential in-group treatment. In the baseline results we define two individuals as belonging to the same group when both are members of the same minority religion (Christian, Muslim, Sikh, Parsi, or Buddhist) or, conditional on belonging to the majority religion (Hindu), when both belong to the same official caste (General Class, Scheduled Caste, Scheduled Tribe, or Other Backward Classes). In our preferred (and most conservative) specifications, we find that on average, the total amount of new loans to borrowers in a group increases by 6.5 percent when the officer assigned to the branch belongs to the same group. Having an in-group officer also increases the number of new loan recipients by 5.7 percent and the probability that a member of the group receives any credit by 2.5 percent…

We then go on to examine the effect of in-group lending on the quality of credit provision and the cost of credit to borrowers. Loans made to in-group borrowers have better repayment performance ex post. The economic magnitude of this effect is large: in-group borrowers are 0.6 percentage points less likely to be late in loan payments, a 7 percent decline relative to the average default probability in the sample (8.6 percent). The decline in default probability persists even after the in-group officer is replaced by an out-group one, implying that the effect on loan quality is not driven by officers rolling over loans to bad borrowers (evergreening). Since all loans have the same interest rate, we evaluate the effect of proximity on the cost of borrowing through its impact on the collateral required per rupee of credit. We find that cultural proximity lowers the cost of borrowing measured this way. Under mild assumptions, our credit quality and quantity results also imply that cultural proximity improves the profitability of lending.

Standard models of in-group favoritism predict resource misallocation, as transacting agents trade off efficiency against higher payoffs from the utility gain of favoring their in-group counterparts. In our context this would imply loan officers bearing the cost of higher default rates in exchange for lending more to their own group. In contrast, standard models of credit markets with asymmetric information predict that, if cultural ties reduce information asymmetries (either ex ante because of better communication or ex post because of better enforcement), they should lead to less credit rationing, e.g., more and cheaper credit to lower risk borrowers. The prima facie evidence from our main results is consistent with the latter type of models

Lowers the cost of borrowing for those who have a cultural connection with their loan officer? Improves the profitability of lending? In short, “cultural proximity improves the quantity, quality, and cost of lending”?

So, this is less a ‘tyranny of cousins’ than a case of greater information (via lower information frictions) producing a better result. Language alone can present a large barrier in what is an enormously diverse country. It’s a win-win folks.

Except:

Our study has a number of implications for theories of discrimination as well as economic policy. First, we note that the preferential treatment we uncover can itself perpetuate income inequality among minorities. In our context, 74.4 percent of the officers belong to the General Class category. This implies that the probability of a backward caste borrower (SC, ST, or OBC) facing unfavorable loan conditions is nearly 75 percent, purely for reasons of cultural affiliation.

Moreover, our findings suggest one possible mechanism through which statistical discrimination against minorities can arise. Minorities will not often be “matched” with a loan officer of their own group and will hence have inferior loan outcomes on average. As a result lenders may form what are ultimately self-confirmatory beliefs about the creditworthiness of minorities if they rely on past average group performance to generate lending rules (Kim and Loury 2009).

Now, if only there was a way to increase the number of minority loan officers to at least start to mitigate that problem… Maybe the overwhelming presence of the state in Indian banking could be a useful tool here?

Do read the full thing.

Related links:
The Origins of Political Order by Francis Fukuyama – Guardian review, have a ctrl-f for “tyranny of cousins”
In defence of cows as safe assets – FT Alphaville
What exactly is in those Bible-based ETFs, anyway? FT Alphaville

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David Keohane
(Spending some time as FTAV’s Bombay wallah. Noticeably sweatier but not much else has changed.) David studied economics, politics and journalism before joining the FT in 2011 as a Marjorie Deane fellow. He covered emerging markets, equities and currencies before making the jump over to FT Alphaville in May 2012. In between his degree and masters he wandered into the real world of business where he learnt how to manipulate a spreadsheet and organise meetings where nothing gets decided.

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