avoid double-counting, exposures should be examined individually and cannot be aggregated across different ecosystem services. As noted by van Toor et al. (2020), these estimates should be considered as a lower bound as it only accounts for the first-order dependencies of an economic sector on ecosystem services.

• _Method 2 – Ecosystem services with high or very high dependencies._ This method gauges the total share of the portfolio with business processes that are highly or very highly dependent on at least one ecosystem service. Following the illustration in Figure 2, this is equivalent to assuming that the dollar borrowed by a firm in NACE division “Crop and animal production, hunting and related service activities” is equally distributed across six business processes associated to this economic sector. Some of these six processes will by highly (H) or very highly (VH) dependent on ecosystem services. For example, “Largescale rainfed arable crops” depends VH on three ecosystems and H on another nine, and so the process is flagged as highly dependent. In the unlikely case that the other five business processes exhibited no H/VH dependency on any ecosystem service, then one-sixth of each dollar borrowed by a firm in this NACE division would count as dependent. This approximation is then replicated for all economic sectors, and the exposures can be added for the entire portfolio. A caveat is that this metric is related to a diverse range of ecosystem services and could underestimate the exposure of firms dependent on ecosystem services with lower materiality ratings. Figure 6 addresses this limitation by integrating all ecosystem service materiality ratings.

# **3. Estimating financial physical risks of biodiversity loss**

This section presents the findings on countries’ bank exposure to physical risks by comparing their dependency on ecosystem services.

Banks in our sample of emerging markets allocate around half of their total credit portfolio to firms whose business processes are highly or very highly dependent on one or more ecosystem services.<sup>11</sup> This metric appears to be negatively correlated with the countries’ income level (Figure 3). In lower-middle-income economies, banks allocate on average 55 percent of the loans to firms subject to potential financial losses due to a deterioration of ecosystem services. Within this group, countries with the highest dependency are Mauritius (73 percent), Pakistan (60 percent), and Indonesia (52 percent). In upper-middle income countries the dependency is lower, at 47 percent on average. Additionally, upper-middle-income countries show a lower dispersion compared to other country groups, ranging from 56 percent in Argentina to 43 percent in the Russian Federation. High-income countries in our sample show on average the lowest direct exposure to nature loss, with 45 percent of banks' credit portfolios directed to firms highly or very highly dependent on one or more ecosystem services. Within that income group, Hungary exhibits the highest dependency at 52 percent and Chile the lowest at 37 percent.<sup>12</sup>

> 11 We use the high or very high to one or more ecosystem services metric to allow for comparability with available literature. We present alternative metrics in Table 5 in the Appendix.

> 12 As highlighted before, this paper is based on publicly available data, and thus the results may only be interpreted as a broad indication that would require more in-depth and detailed assessment, relying on unpublished data from local authorities. For instance, Banco de Mexico estimates a comparable dependency metric at 36.5 percent using

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