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Trust and Social Collateral: Implications for P2P Lending

Trust is an inevitable topic

Every time I shared the concept of P2P lending, the question of trust inevitably comes up. Trust is an imperative component for P2P lending.

“How can I be sure that I can get my money back?”

“Will the borrower pay me back?”

“What if they took the money and ran away?”

The Social Collateral Model

So I started researching about trust. I came across an authoritative paper “Trust and Social Collateral” by D Karlan (Yale University), M Mobius (Harvard University and NBER) and others.[1]

In the paper, the authors present a social collateral model, showing how network connections breed trust and how they influence economic outcomes. The authors made a number of assumptions in the model, here I mention 2 conceptual ones[2]:

  1. Social Sanctions => Friendly feelings often cease to exist when a promise is broken.

  2. Circle of Trust => Social distance matters, the closer the links are to the centre, the stronger the trust. The converse is also true – the further away, the weaker the trust.

The main result concluded by the authors was:

In general networks, the level of trust equals the sum of the weakest link values over all disjoint paths connecting borrower and lender, also known as maximum network flow.

Sounds Greek at this point? Perhaps a better understanding can be gleaned from its applications.

Three Applications

First Application: The effect of network structure

Two schools of thought exist in this area. One school maintains that a high closure network is better because having many common friends will facilitate the enforcement of a high level of cooperation. Peer pressure will bring people into compliance and to shoulder responsibility.

The other school prefers a low closure network – a large, open network but with little inter-connections between the nodes. This school believes that loose networks provide greater access to information and other resources.

The authors’ social collateral model amalgamates these two schools of thought. They identify a trade-off between trust and access. The relative benefit of high or low closure depends on the value of the assets being transacted.

Closure is more attractive in the exchange of valuable assets, because it maximizes trust among a small number of individuals. Conversely, in the exchange of small (less valuable) favors, large and loose neighborhoods are better because they maximize access to these resources.

Second Application: Trusted recommenders can reduce asymmetric information.

Here, the authors illustrate the application of their model in job search and trusted recommendations. Their model concludes that[3]:

  1. Network based trust should be more important for high skilled jobs, where the employer’s profits are more sensitive to worker type

  2. Jobs obtained through the network should earn higher wages than jobs obtained in the market

  3. Due to the increased importance of trust for high quality jobs, the wage differential between network-based and market-based hires should be positively related to skill intensity

  4. When filling high-skilled vacancies, employers should search more through their networks

Linkedin is becoming a stellar proof of these. Fortune magazine recently ran a cover on Linkedin, you can read about their success here. (As an aside, do invest some time in updating your profiles on Linkedin.)

Third Application: Social networks and informal lending

The authors put their model to the test by performing an empirical field study of informal lending in Lima, Peru. They buy cheap isotretinoin online found a strong positive correlation between social collateral and borrowing. Another interesting finding is that direct (e.g. A knows B) and indirect (e.g., A and B don’t know each other but have C as a common friend/trusted recommender) paths have similar effects on borrowing, demonstrating the importance of network closure for building trust. They observe that a key structural implication is that borrowing should be determined by the weakest link on a path. [4]

For instance, consider the following:

  1. C is the bridge between A and B (i.e. A ? C ? B)

  2. C is the best friend of B, hence the trust level between them is very high.

  3. A and C on the other hand are ex-classmates, their relationship is amicable but not as strong as that of B and C.

  4. The trust level between A and C is lower than that of B and C.

  5. The economic outcome should therefore be only determined by the trust level of A and C (the weakest link).

Implications for P2P Lending

Since trust is imperative, a sustainable platform should firstly curate borrowers with some transparent hygiene factors as a bridge and subsequently provide the means for a borrower to present and develop their own trustworthiness to prospective lenders.

For borrowers

Recognise the trade-off between trust and access. In order for a lender to commit bigger loan amounts, there must first exist a high level of trust (which could either already be existent or otherwise be cultivated). For smaller loan amounts, trust becomes a lesser constraint, but that also means that in order to secure meaningful amounts of funds, access to a larger (loose) network of lenders is necessary.

Be mindful that trust is dynamic. It can easily dissipate via social sanctions. If a borrower breaks his promise to pay up, he can almost be assured that he will not be able to obtain another loan from the same lender.

Trust can also be cultivated over time with multiple rounds of exchange. When promises (no matter how small) are kept, the strength of a relationship grows and it becomes the sum of its direct value (as per the basic social collateral model) and the indirect value (i.e., the ability to conduct transactions through the link in the future).

For lenders

Reduced cost of information discovery. A well designed platform will reduce the cost of information discovery for p2p lenders. By bringing about transparency and accountability from borrowers, p2p lenders will then be better placed to determine the trustworthiness of a borrower from the information collected through the network.

Diversify and Risk Share. When a platform develops in scale with a diversity of borrowers, lenders will then have greater choices to risk share, and have more opportunities to discover long-term trusted relationships that maximise their economic outcomes.

Formalizing lending. The paper studied the effects of trust and social collateral on informal lending (i.e., with no written enforceable contracts). With technology, p2p platforms can formalize loans into legal contracts. The prospect of additional legal sanctions should augur greater responsibility in the network.

My two cents on the topic. Welcome any comments!

[1]Karlan, D., Mobius, M., Rosenblat, T., & Szeidl, A. (2009). Trust and social collateral. The Quarterly Journal of Economics, 124(3), 1307-1361.

[2] Ibid, 1316

[3] Ibid, 1332-1333

[4] Ibid, 1334-1342

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