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Community Risks

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The Risks and Rewards of Community-Driven Business Models

The Risks and Rewards of Community-Driven Business Models

Understanding the hidden dangers of leveraging social capital in low-income communities.

Rooted in the work of microfinance pioneers like Grameen Bank and BRAC, community-based business models have been hailed as a new way of doing business that can viably address the needs of low-income customers that would otherwise be excluded from the market economy.

The core insight has been that tapping into the tight-knit social ties within rural communities in emerging markets can help ensure that customers influence one another to collectively meet their obligations towards a firm. In the context of microfinance, this means guaranteeing that individual borrowers, who often lack the credit history or collateral required by traditional banks, can still be trusted to repay their loans.

Microfinance lending has been widely successful, bringing financial inclusion to hundreds of millions of people from Asia to Africa to Latin America. But the insight has also been applied beyond the microfinance sector. It has unlocked various business models related to essential products and services not otherwise accessible for the poor – from agricultural tools and water filters to home construction and solar lighting systems. 

However, our recently published research, which studied the aftermath of demonetisation in India in 2016 and its impact on microfinance, reveals a more nuanced narrative around the social influence processes taking place within communities. The core lesson, one that extends even beyond microfinance, lies in understanding the delicate balance between the risks and rewards associated with relying on local networks and community ties. 

The shock effect

A surprise announcement in November 2016 that all 500- and 1,000-rupee banknotes would suddenly be invalid sent shock waves throughout India. The decision to demonetise removed 86 percent of the currency in circulation at the time. 

While the government guaranteed that all invalid notes could be exchanged for new notes, the scale and scope of the process led to massive scarcity. It also created disruptive delays and long queues of people panicking about when they would be able to make the exchange. This disruption of the cash economy greatly affected poor rural Indians most heavily dependent on cash for everyday needs. 

This seismic economic event led to a catastrophic rise in defaults on microfinance loans – which are typically repaid in cash. Based on a dataset from a large for-profit microfinance organisation, comprising of approximately two million borrowers, we found that the number of defaults suddenly jumped from just two percent to 40 percent around demonetisation. 

When we dug deeper, we discovered that the defaults were not distributed evenly. Instead, they were heavily clustered within a subset of the communities. This may to some extent be expected, given that locations differ in economic conditions. For example, the cash dependence of livelihoods or that access to new bank notes varied across India. However, what was really interesting was the strength of our findings even when accounting for this.

The above pattern suggested that localised social influence had played a major role in the disproportionate number of defaults in particular communities. We further confirmed this by directly studying how recent loan defaults by some borrowers influenced future decisions by others in their community. It was clear that local borrowers were not making independent decisions on whether or not to make their loan payments in time.

The ‘dark side’ of social capital

Our study’s findings highlight the risk businesses face when their business model relies on interconnectedness among customers. What makes a given model work under normal circumstances can also cause its unravelling when things go wrong.

Imagine a scenario where, instead of isolated individual decisions, an entire group of customers disengages from a firm. Such a situation was triggered by a macroeconomic shock in our study, but it could also be driven by an unexpected natural disaster or even a corporate scandal. The collective action by customers poses a substantial risk to businesses that have built their models around communities.

Navigating the right path

Our findings on the potentially outsized importance of social influence and community dynamics offer valuable lessons for businesses operating in any setting where the interconnectedness within a community of customers is important. 

  1. Risk management is crucial: Business models reliant on community ties must integrate robust risk management strategies. Anticipating potential downsides and crafting contingencies becomes essential when dealing with interconnected social networks.
     
  2. Context matters: Recognising that community dynamics vary across regions and demographics is important. What works in one community might not in another. Tailoring business models to fit local contexts and understanding the intricacies of community relationships is crucial.
     
  3. The role of leadership: Authenticity and involvement of local leaders that can shape community engagement may play a pivotal role. For example, how a firm’s field officers build relationships with the community could influence the community’s decision to cooperate in adverse situations.
     
  4. Balancing act: Rather than abandoning community-driven models, the goal should be to appreciate both their benefits and their risks, and manage accordingly. Risks can be mitigated by investing in relationships and by showing genuine understanding and real commitment towards making a positive impact for the customers served. 

The journey towards any business model innovation demands not only creativity but also a keen awareness of the social dynamics at play. As businesses navigate through this intricate path, the above insights from community-driven models can provide valuable lessons.

Edited by:

Nick Measures

About the author(s)

About the research

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Sustainable Development Goals
Research for the World
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