Anthropologies of Risk: Credit Scoring in Coercive Political Economies. Ethnographic notes from North India

by Lucia Michelutti and Tommaso Sbriccoli

Lucia Michelutti

Professor of Anthropology

Head of the Social Anthropology Section

Department of Anthropology

University College London



Puchri ka pau dhan

Adha dhan to ghena

Pura dhan to iman hai

marag marag rehna


One with a tail [whose honor is low, like that of an animal] gets 25% of the capital

If you put a collateral, you get 50%,

If you are an honest man, you will get 100%

Therefore, follow the right path

This popular Marwari saying crystallises how the capacity of getting loans at a just interest (or without interest) is linked to the borrower-family/household’s honour rather than being just a matter of bank statements’ analysis and financial projections. In rural Rajasthan issues of status, honor, gender and individual/group (caste) identity are of paramount importance in shaping credit worthiness and local vernacular practices of credit risk.[1] Ijjat, badnam, reputation, are terms often mentioned when discussing debt and the possibility of defaulting. Importantly, honor is not individual, but is socially shared by the family and entire lineage. These are systems where what is shameful is not to be in debt but not to be given credit. Taking money on loan (len-den – give and take) is at the heart of the local social fabric. In this world ‘distance’ both spatial and social, becomes a function of a person/family reputation and is integral part of indigenous practices of ‘risk checks’. The further away one needs to go in order to get credit, the higher is interest.  Similarly, the closer is someone socially with the local moneylender, the lower the interest is. Collaterals are also partly indicators of the kind of relations existing between moneylenders and borrowers. Their presence (or non presence) tells a lot about a person/family’s reputation. During fieldwork members of the local Adivasi communities by being both socially and physically “distant” from village’ social life, were usually charged higher interests (up to 60-120% per year) and asked to provide collaterals. Since many of them did not have assets to pledge, they often ended up mortgaging their work risking being captured in bonded labor relations.


Does cashless social financing reduce extortive relations between moneylender and laborers?

Over the past decade digital social financing has been promoted as a way to reduce poverty, drive inclusive growth and combat patronage practices such as bonded labour across India. Cash is said to facilitate ‘the black economy’ and with it the extortive relationships between moneylender/bosses and laborers in coercive political economies. In contrast the digital money is seen as a way to create non-predatory relationships, inclusion and socio-economic development in particular among marginalised economic communities. However on the ground cash less and cash economies are often false dichotomies. In the digital social business sector it is often forgotten that the proportion of the black economy in ‘money-cash’ represents only 1 to 6 per cent of the total.[2] The rest is in estates, gold, jewellery but also cows and buffalos and services. ‘In kind cash’ rather than ‘money cash’ is crucial to understand both processes of finacialisation of the poor as well as the accumulation of capital by businessmen-cum-bosses. In rural Rajasthan Adivasi take often goods on credit from shop-owners and do not repay the debt in cash. Their debts are often bought by their bosses in exchange for non-payed work.  In such instances ‘money-cash’ is never exchanged. Recent research on the modus operandi of systems of government informed by coercive economies across India, Pakistan and Bangladesh[3] and a collaboration with a social lending Fin-tech operating in India,  taught us that indigenous understandings of risk and ethnographically informed socio-political analysis of over-indebtedness, dependency and extortive relations are largely ignored by new digital social financial models whose aim is to promote rural prosperity across South Asia (in particular in India).


How can statistical credit rating tools take into consideration vernacular evaluations of risk and local systems of extraction and dependency?

Vernacular evaluations of credit risk and relations that produce credibility through cash (‘money-cash’ and ‘in-kind’ cash) at the local level are not taken into consideration and integrated in the statistical centered credit rating tools – developed by banks and social fin-techs. The result is that marginalised and cash dependent groups remain excluded by impact investing initiatives. For example, the Rajasthani Adivasi we met hardly befit from cashless bank loans. Digital Finances Services (DFSs) play no role in increasing their access to credit as these communities are often not served or are underserved by formal financial institutions.  Their lack of credit history and collateral make them too risky for commercial banks and other formal institutions to lend to them.  In fact, their actual risk levels and creditworthiness are seldom assessed, due to the lack of systematic data about their households’ finances. 

In the field we learnt that that at the local level risk assessments and the demands and needs of the informal/criminal economy continually transformed cashless into cash. Social financing products need to take into account these realities and the fact that risks are ‘not simply a mathematical calculation of statistical probabilities but something that requires a fuller understanding of the social, cultural, and political dimensions that constitute perceptions of riskiness’.[4] Supported by an ERC- Proof of Concept we took this challenge on board and are currently developing and trialling EDRAF – an Ethnographic Driven Risk Analysis Framework. By innovatively taking into account indigenous understandings of risk and ethnographically informed socio-political analysis of over-indebtedness, cash and cashless, EDRAF aims to provide fairer assessments of households’ creditworthiness among cash-dependent rural households. It is composed by a) A research toolkit to assess political, economic and social risks for social financing in rural South Asia; and b) A mobile software application for android to collect and map households’ debt and credit histories in joint/extended family systems and monitor and track impact. The tool kit aims to take into account the anthropological dimension of credit scoring and with it the materiality of money and ‘cash-less’. Our involvement with a Fin-tech and with the social financing world helped to ensure that our fieldwork-based ethnography did not turned us away from engaging with the wider trends in the national and world economy in which debit and credit exchanges are deeply imbricated. Such engagement shows the potential of putting into dialog classical anthropological discussions of risk with the ethnography of ‘the digital finance turn’ in South Asia and beyond.




Kar, S. Finacialising Poverty. Labour and Risk in Indian Microfinance Labour. Stanford: Stanford University Press.

Harriss-White, B and Michelutti L. (2019). The Wild East? Criminal Political Economies in South Asia. London: UCL Press

Michelutti, L. A. Hoque, N. Martin, D. Picherit, P. Rollier, A. Ruud and C. Still. (2018) Mafia Raj: The Rule of Bosses in South Asia, Stanford: Stanford University Press.

[1] Research was conducted between 2012-2016 and 2018-2020 and funded by ESRC (ESRC/1036703) and ERC-Starting Grant (AIMSA/284080 and an ERC- Proof of Concept (780143).

[2] Harriss and Michelutti (2019: 346).

[3] Michelutti et al (2018); Harriss and Michelutti (2019).

[4] Kar, S (2018; 147).