The BRICS (Brazil, Russia, India, China, South Africa as founding members) Summit held in New Delhi on September 12-13 brought together a coalition of nations with increasingly divergent geopolitical priorities, but a shared inevitability of the impact of large-scale and frequent climate catastrophes.

The recent landslide and resulting flash floods near the Nepal-Tibet border, as well as those in Assam before have caused immense loss to life, property, and livelihoods.

Nearly 1,800 hectares of crops were damaged, threatening farming and fishing community livelihoods. These circumstances leave residents in a vicious cycle of precarious livelihoods. Institutional response for disaster management usually comes post facto – the flow of aid is curative, not preventative. The resulting delays in disbursal exacerbate food scarcity, job loss, and compromised safety for residents and their families.

In the wake of inevitable climate catastrophes, adaptation is as critical as, if not more than, mitigation. Measures to address climate change, such as parametric insurance, have been piloted worldwide, including India. One such scheme in Delhi-NCR (National Capital Region) paid workers between INR 100 and 500 if temperatures hit 45.27 degrees. The temperature was used as a metric, pre-determined on the basis of a weather index. Insurers rely upon similar weather and satellite datasets to assess potential damages and craft payouts for those affected.

However, pilots often fail to bridge a critical gap in assessing claims – a gap that can be filled only through an understanding of local capacities, vulnerabilities, and aspirations. For instance, a catastrophe caused by low rainfall has differential impacts on irrigation practices in geographically diverse regions and communities – some regions may need more support than others. This is a consideration of counting what matters.

Community-oriented perspectives are missing throughout the value chain of parametric insurance

To understand touchpoints for community voices while designing parametric products, we outline three layers:

	LAYER 1The indices(What data points support us in identifying triggers?)	LAYER 2The stakeholders (Who is facilitating claims and payouts?)	LAYER 3The service delivery (What is the type of payout?)
What is usually included	Geospatial dataHeat indexAQIFlood dataIoT devices and environmental sensors	Insurance andre-insurance firmsGovernmentsNGOsPhilanthropies	Cash
What is usually not included	Localised knowledge	CooperativesInformal community-led groups	LoansIrrigation systemsEnergy infrastructure Early response systemsCrop restorationTechnological support

The indices

Parametric insurance pilots for Hurricane Maria, a catastrophic cyclone that killed over 4,000 people in Puerto Rico in September 2017, failed to cover damages for affected persons because although wind-speed data was used as the trigger, the actual damage was caused by rainfall and flooding. This invites what is termed as ‘basis risk’: where a pre-determined trigger is unmet, or a payout is inadequate to community needs. To avoid incurring losses due to basis risk, high reliance is placed on ensuring greater precision and accuracy in setting indices based on satellite data. Many insurers use AI to mitigate this, as AI-linked layers can observe subtle changes in environmental patterns in real time.

However, AI-assisted predictions are only half the battle. A community of farmers may benefit from precise weather data and still need bottom-up structures for payouts capturing the unique consequences of weather events on their livelihoods, i.e., loss of shelter, farming equipment, and so on. Data ecosystems in the Global South are relational; hyperlocal forms of identification tie communities to practices that may or may not reflect in institutional data.

The stakeholders

In the Global Majority, community-centric groups are intermediaries in mobilising support for social protection tools. Jan Sahas, through its Migrants Resilience Collaborative (MRC), mediated an AQI-based parametric insurance pilot in Delhi-NCR to combat livelihood risks due to construction bans, allowing workers to avail cash-based payouts.

Successful parametric projects have demonstrated that an insurance product can be scaled by building it through trust-based community structures: cooperatives, credit unions, associations, and informal groups. Some insurers offer payouts through agricultural cooperatives where members don’t file claims; payouts are disbursed by virtue of trust in the cooperative. The presence of an entity between implementers and beneficiaries bridges gaps in accessibility and credibility of the parametric product.

The service delivery

In remote islands of the Philippines, where income is predominantly agri-based, food practices adapt to climate constraints.¹ Which is why during climate crises, medical supplies and crop restoration efforts take precedence over food packages as relief.

Examples of payouts within crop insurance for farmers have included facilities like agronomic advice, drought-resistant seeds, and digital soil monitoring. This bundling of facilities helps communities recover losses while building sustainable productivity.

International bodies fail in localising aid, i.e. tailoring it to specific contexts based on local knowledge and agencies, instead of working through international intermediaries. Colonial underpinnings in deciding what affected persons need beyond food and cash offer solutions that communities do not resonate with.

Using data justice to reimagine participation

Through the above three layers, we reiterate the need for parametric insurance indices and payouts to go hand-in-hand with community data. Data justice advances the role of data in championing local perspectives, beyond myopic views of efficiency and privacy. It questions how communities can be identified and recognised in society when indigenous practices are unsuccessfully slotted into Westernised models of aid and resilience.

In Global South communities, force-fitting data-driven metrics based on evaluations in the Global North can have harmful consequences for mitigating vulnerability. Can satellite data solely be a metric to formulate community-sensitive social protection? Are cash-based payouts the sole route to indemnifying disaster-struck communities? Data justice offers a way to mitigate these power asymmetries when delivering social protections in the Global Majority. A collaborative approach to issuing parametric insurance re-evaluates what accuracy and representation in data mean for affected persons. Consulting with communities on what payouts should look like, having atleast one community member or organisation in insurance strategy teams, and yearly reviews of triggers and payouts can bring social protections like parametric insurance closer to the communities they serve. Climate change has increasingly become an inevitable reality in our daily lives, and adaptation must be informed by bottom-up imaginations of welfare delivery.

Lead up to the BRICS Summit

Drafted in the aftermath of the BRICS Summit, the New Delhi Declaration emphasises on financing green initiatives and climate resilience across BRICS countries. While the focus was largely on energy financing and carbon markets, the role of the New Development Bank to co-finance larger adaptation projects could potentially expand to

¹ Key informant interviews with community organisations in the Philippines.

climate-centric welfare instruments like parametric insurance. This was not directly addressed, but the value of community-centric adaptation was highlighted indigenous knowledge sources to combat environmental catastrophes like droughts, floods, and so on.

BRICS priorities on climate remain similar, owing to most members being impacted by large-scale and frequent climate catastrophes. Welfare delivery in this context must support long-term adaptation needs, like disaster-resilient energy infrastructure, early warning systems, and agricultural support to sustain livelihoods after catastrophes.