[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-126919-en":3,"doc-seo-126919-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},126919,2336474459895,"Aria","https://ap-avatar.wpscdn.com/avatar/22000baeef7a5ed0655?x-image-process=image/resize,m_fixed,w_180,h_180&k=1786071322749376916",8,"Research & Report","Machine learning-based climate risk sharing for an insured loan in the tourism industry","Higher risks for commercial banks reduce the likelihood of accessing financing transactions, while climate change risk materially affects bank loan supply. In tourism, lenders may charge higher mortgage rates where sea-level rise risk is greater. Because loans are central to bank business, innovative approaches support resilient composite loan supply, particularly against physical climate risk. This study proposes an insured-loan tool with a climate risk-sharing mechanism using a bioclimatic composite indicator developed via a machine-learning naïve technique.","Machine learning‑based climate risk sharing for an insured loan in the tourism industry  \nMaria Carannante1,2 · Valeria D’amato3 · Paola Fersini4 · Salvatore Forte5  \nAccepted: 6 August 2024 © The Author(s) 2024  \nAbstract  \nHigher risks for commercial banks correspond to lower probability of access to financing transactions. Climate change risk strongly impacts bank loan supply. In particular, in the tourism industry, it is noteworthy that lenders charge higher interest rates for mortgages that face a greater risk of rising sea levels. As loans are one of the most important businesses for commercial banks, innovative strategies can lead to the design of a composite bank loan supply for building resilience, especially against physical climate risk. In this work, we propose a new tool, which is an insured loan relying on a climate change risksharing mechanism, where we develop a bioclimatic composite indicator based on machine learning naïve technique.  \nKeywords Climate change · Insured loan · Machine learning · Random forest  \n1 Introduction  \nFinancial planning in the beach tourism industry consists of controlling special financial security, which includes climate change risk as a relevant component of its risk profile. The impact of climate change that cannot be avoided such as sea level rise, flooding, heat  \n* Maria Carannante [maria.carannante@collaboratore.uniparthenope.it](maria.carannante@collaboratore.uniparthenope.it)  \nValeria D’amato  \n[Damato@uniroma1.it](Damato@uniroma1.it)  \nPaola Fersini  \n[paola.fersini@unisannio.it](paola.fersini@unisannio.it)  \nSalvatore Forte  \n[s.forte@unifortunato.eu](s.forte@unifortunato.eu)  \n1 Department of management and quantitative studies, University of Naples Parthenope, Naples, Italy  \n2 Difarma Department, University of Salerno, Salerno, Italy  \n3 Memotef Department, University of Rome Sapienza, Rome, Italy  \n4 DEMM Department, University of Sannio, Benevento, Italy  \n5 Faculty of Law, Giustino Fortunato University, Benevento, Italy  \nwaves, desertification, crop failures, etc. leads to strong direct effects on tourism, which has become one of the world’s fastest-growing industries. In particular, seaside industry activities generate significant revenues in coastal and marine areas, even if the areas that attract tourists are also coming under increasing pressure from the damage and pollution caused by tourist facilities and the supporting infrastructure and from the increase in the frequency and severity of adverse climate events. There is a strand of recent literature in the field of climate change impact that stresses the climate-tourism relationships (Gambarelli and Goria 2004 ; Sygna et al. 2004 ; Hamilton and Tol 2007, Hein et al. 2009, Jennings 2004 ; Phillips and Jones 2004 ; Surugiu and Surugiu 2009 ; Surugiu et al. 2011, Filho 2022) . The World Economic Forum highlights the alteration of traditional tourist trends due to rising temperatures that are likely to result in tourists travelling in spring and autumn rather than summer (World Economic Forum, 2023) . Some authors emphasise the duality of climate change risk in the tourism sector, which is highly vulnerable to climate change and contributes to the emission of greenhouse gases (GHG), which cause global warming (for instance see Nazir 2023) .  \nIn particular, climate change impacts on the coast, such as storm surges and rising sea levels, are inevitable, and, in some regions, they are already damaging coastal tourism economies making coastal tourism a vital part of the world economy. The big issue is that climate change has become very prominent, causing new risks also to the banking sector. This is why regulators in several countries have increasingly emphasised macroprudential supervision and control of systemic financial risks, as well as the severe challenge of climate change.  \nAs loans are one of the most important businesses for commercial banks, innovative strategies can lead to the design of a composite ","cbCaig9Xoxo3u9Qe","https://ap.wps.com/l/cbCaig9Xoxo3u9Qe","pdf",881008,1,14,"English","en",105,"# Introduction\n## Climate change and bank loan supply\n## Climate risk in tourism and coastal impacts\n## Motivation and research aim\n## Proposed insured loan and bioclimatic indicator","[{\"question\":\"Why does climate change risk affect commercial banks’ financing availability?\",\"answer\":\"Higher climate-related risks for banks correspond to a lower probability of access to financing transactions, since climate change strongly impacts loan supply.\"},{\"question\":\"How does climate risk influence loan pricing in the tourism sector?\",\"answer\":\"Lenders charge higher interest rates for mortgages that face greater risk of sea-level rise, reflecting how climate vulnerability can translate into higher borrower costs.\"},{\"question\":\"What tool does the study propose and how is it built?\",\"answer\":\"The study proposes an insured loan relying on a climate change risk-sharing mechanism, developing a bioclimatic composite indicator using a machine-learning naïve technique.\"}]","Machine learning-based climate risk sharing for an insured loan in the tourism industry | 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