exposure to one or more ecosystem services, at the risk of underestimating the exposure of firms dependent on ecosystem services with lower materiality ratings. In addition, we break down this exposure by source of funding (earmarked vs. non-earmarked), banks’ size,<sup>13</sup> borrowers’ size, and loan quality.

Overall, our physical risk assessment should be considered as a lower bound as it only considers the first-order dependencies of an economic sector on ecosystem services. As noted by DNB (2020), in the ENCORE database a production process such as the cultivation of crops is directly dependent on animal pollination. Nonetheless, the processing of foods, a secondary industry, depends indirectly on animal pollination but this is not captured by the database.

# _Biodiversity loss and banks’ loan quality_

Loss of ecosystem services potentially impacts banks’ balance sheets. To provide an illustrative exercise of these effects, we leverage the existing literature. We first obtain trend estimates in ecosystem services and economic indicators through 2030 under a scenario of ecosystem collapse, that is, a scenario where pressure on ecosystems pushes them to tipping points, resulting in a collapse in the provision of ecosystem services. Next, the variation on banks’ NPLs associated with the macroeconomic conditions following such a collapse in ecosystem services is determined.<sup>14</sup> By incorporating select ecosystem services into a computable general equilibrium model, a novel World Bank study attempts to quantify the nexus between economies and nature (World Bank, <u>2021). The study provides country-specific estimates of the decline in GDP growth through 2030</u> (using 2021 as baseline) due to a collapse in a selection of four ecosystem services: pollination of crops by wild pollinators, climate regulation from carbon storage and sequestration, provision of food from marine fisheries, and provision of timber. The ecosystem services collapse is benchmarked to a business-as-usual scenario where no ecological tipping points are reached.<sup>15</sup> Limitations, including un-exhaustive incorporation of feedback loops, and the consideration of a limited number of ecosystem services, suggest that this exercise only provides conservative estimates of the economic implications of collapsing ecosystem services.

> 13 We follow the BCB classification of banks’ size. Particularly, large banks are those with a total exposure to GDP ratio greater than 10 percent or those with foreign assets greater than US$ 10 billion.

> 14 Due to the lack of data on loss given default, we are only able to consider information on frequency/probability of default and unable to extend to an expected loss framework.

> 15The World Bank ecosystem-economy modeling combines a general equilibrium model with a set of ecosystem service models that cover pollination, timber provision, fisheries, and carbon sequestration, whose interactions with the economy are projected to the year 2030. For that purpose, the model relies on three building blocks: (i) a general equilibrium economic model (CGE) that allows modeling of land-use change and incorporate the notion that sectors only compete for land that is suitable for their use; (ii) a set of spatially-explicit ecosystem service models to reflect the fact that the economy is embedded in the biosphere; and (iii) a simulator that allows converting outputs from the economic model into spatially explicit variables that serve as inputs to the ecosystem models. The model sequentially runs each of the building blocks.

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