This paper studies the impact of climate risk on credit supply and tests its predictions using data on all wildfires and corporate loans in Spain. The findings reveal a significant decrease in credit following climate-driven events. This result is driven by outsider banks (large and diversified), which reduce lending significantly to firms in affected areas. In contrast, local banks (geographically concentrated) reduce their loans to opaque affected firms to a lesser extent without increasing their risk. We also find that employment decreases in affected areas where local banks are not present. The paper develops a bank lending model under climate shocks and with asymmetric access to information. There are two types of banks – local banks (geographically concentrated) and outsider banks (large and diversified) – and two types of firms – transparent and opaque. Local banks can better monitor opaque firms because they have better access to soft information than outsider banks. The model includes shocks to the banks' deposits at the bank level and firms' productivity shocks at the firm level, as well as shocks at the economy level. It also incorporates firm-specific climate shocks, which have a different impact on the marginal returns of the loans depending on each bank's ability to monitor firms. Banks face the costs of raising external financing and choose loan amounts to maximize their expected profits subject to their balance sheet constraint. In equilibrium, local banks are more effective at absorbing the impact of climate shocks because they experience a smaller decrease in their marginal returns of lending after a climate shock compared to outsider banks. Our findings uncover that the differential use of soft information by local and outside banks in their lending decisions may be a primary mechanism influencing bank credit allocation following a climate-related disaster. According to our model, after a climate event such as a wildfire, there is a decline in the credit amount extended to the affected firms. In addition, outsider banks cannot assess accurately the impact of physical climate risk on opaque firms and, therefore, they tend to respond by significantly reducing credit. Local banks have access to soft information, which allows them to restrict their lending less to those affected firms that are opaque, without taking on more risk. We test the model’s predictions using data on firms, banks, and wildfires in Spain. We do so for three main reasons. First, we focus on Spain because we can construct a unique dataset –with monthly detailed information on all companies, all banks, and all bank-firm credit relationships– that covers a long period (i.e., 2004-2017). Second, we focus on wildfires due to the level of accuracy in ascertaining whether a firm has been impacted by a fire and the growing number of such extreme events. Third, we focus on wildfires in Spain because it is one of the countries most affected by wildfires in Europe. The total area burned annually in Spain has been greater than 50,000 hectares in 13 of the last 18 years and at least 46.35% of Spanish municipalities are locatedThis paper studies the impact of climate risk on credit supply and tests its predictions using data on all wildfires and corporate loans in Spain. The findings reveal a significant decrease in credit following climate-driven events. This result is driven by outsider banks (large and diversified), which reduce lending significantly to firms in affected areas. In contrast, local banks (geographically concentrated) reduce their loans to opaque affected firms to a lesser extent without increasing their risk. We also find that employment decreases in affected areas where local banks are not present. The paper develops a bank lending model under climate shocks and with asymmetric access to information. There are two types of banks – local banks (geographically concentrated) and outsider banks (large and diversified) – and two types of firms – transparent and opaque. Local banks can better monitor opaque firms because they have better access to soft information than outsider banks. The model includes shocks to the banks' deposits at the bank level and firms' productivity shocks at the firm level, as well as shocks at the economy level. It also incorporates firm-specific climate shocks, which have a different impact on the marginal returns of the loans depending on each bank's ability to monitor firms. Banks face the costs of raising external financing and choose loan amounts to maximize their expected profits subject to their balance sheet constraint. In equilibrium, local banks are more effective at absorbing the impact of climate shocks because they experience a smaller decrease in their marginal returns of lending after a climate shock compared to outsider banks. Our findings uncover that the differential use of soft information by local and outside banks in their lending decisions may be a primary mechanism influencing bank credit allocation following a climate-related disaster. According to our model, after a climate event such as a wildfire, there is a decline in the credit amount extended to the affected firms. In addition, outsider banks cannot assess accurately the impact of physical climate risk on opaque firms and, therefore, they tend to respond by significantly reducing credit. Local banks have access to soft information, which allows them to restrict their lending less to those affected firms that are opaque, without taking on more risk. We test the model’s predictions using data on firms, banks, and wildfires in Spain. We do so for three main reasons. First, we focus on Spain because we can construct a unique dataset –with monthly detailed information on all companies, all banks, and all bank-firm credit relationships– that covers a long period (i.e., 2004-2017). Second, we focus on wildfires due to the level of accuracy in ascertaining whether a firm has been impacted by a fire and the growing number of such extreme events. Third, we focus on wildfires in Spain because it is one of the countries most affected by wildfires in Europe. The total area burned annually in Spain has been greater than 50,000 hectares in 13 of the last 18 years and at least 46.35% of Spanish municipalities are located