The research activity carried out is aimed at analysing specific thematic aspects within the macro-area of 'Earth Observation between Space Law and Space Economics'; in other words, Earth Observation between economic opportunities and legal profiles. The research focuses on the highly interdisciplinary intersection between space law, space economics and technology. The primary objective is to define a flexible legal framework that not only does not hinder, but rather accompanies technological and market development, extending the principles of prevention and precaution to the space environment. The application focus is on the use of EO data and artificial intelligence (AI) in the insurance sector - with a view to risk management aimed at enhancing the principles of prevention and precaution - to mitigate and contain catastrophic risks, with particular reference to index-based policies in agriculture. Once it has been established that the spread of this insurance product would bring considerable benefits to both insurance companies and customers, the analysis carried out leads to the identification of various legal issues and problems, in other words, various 'grey areas'. The research identifies three macro-critical issues that undermine confidence in the index-based policy system. The first concerns basis risk and algorithmic opacity and the risk that the calculated index (based on EO/AI data) does not reflect the actual damage to the crop, leading to disputes. The opacity of the calculation algorithms (black box) makes it almost impossible for farmers to prove the fault of the data provider. The second macrocriticality is the probative value of the data and the need to guarantee the integrity, incorruptibility and reliability of the satellite data used for compensation. The third and final macro-criticality investigated concerns space governance and the obsolescence of current space law, which is insufficient to regulate the rapidly growing private economic initiative and the associated risks. To overcome these challenges, various operational and regulatory proposals have been put forward. To guarantee data integrity, it is proposed that blockchain technology be associated with the EO data analysis process in order to certify, in an immutable manner, the integrity of the chain of custody of the processed data. This establishes a standard of procedural responsibility for the operator (DOS), borrowed by analogy from Article 2423 of the Italian Civil Code. In order to ensure contractual transparency, it is suggested that legal design be applied to clarify the semantics and structure of IBI contracts, making the causal link and compensation mechanism transparent. Furthermore, in line with the AI Act, an explainability obligation is required for AI models used in actuarial calculations, classified as high-risk systems. With regard to data governance, in order to modernise space law, it is proposed to move beyond the idea of exclusive ownership of primary data, adopting a model of access and reuse of raw data inspired by the Copernicus paradigm. Finally, given that the context analysed is characterised by the presence of dynamic risk, a risk management model is proposed that calculates insurance rates in a geolocalised and dynamic manner (based on Vulnerability, Exposure, Impact and Probability). This model creates an incentive for farmers to adopt ESG practices (e.g. precision farming), as a reduction in vulnerability measured by satellite leads to an automatic reduction in the insurance premium. The methodological approach adopted during the project is hybrid in nature, as it requires the overlapping of several methods of analysis and study attributable to the humanities but also to the STEM (Science, Technology, Engineering and Mathematics) disciplines. Therefore, the interconnection of knowledge and skills was relevant. The starting point is the analysis, in terms of positive law, of the national and international regulatory framework currently in force in the field under investigation. Looking also at doctrinal and jurisprudential formants, the modus operandi is characterised by the identification and framing of the legal problem in order to advance the most appropriate resolution through problem solving. Economic Analysis of Law (EAL) and Regulatory Impact Analysis (RIA) are integrated to quantify social costs and assess regulatory impacts. In addition, game theory and futures studies are used to model risks and anticipate the strategies of the actors. More specifically, the methodological tools of EAL have proved indispensable for identifying the optimal allocation of rights and protections provided for in legislation (i.e. for identifying regulatory gaps) and the dangers that may arise from them. RIA techniques were also used to assess the cost-benefit ratio resulting from the evolution of the technological tools covered by this investigation. All this was done using an approach consistent with futures studies, in the awareness of the uncertainty of the future and the consequent opportunity to think and act with a view to prevention and precaution.

EO data in insurance: opportunities for the market and legal issues

FABROCINI, ALESSANDRA
2026

Abstract

The research activity carried out is aimed at analysing specific thematic aspects within the macro-area of 'Earth Observation between Space Law and Space Economics'; in other words, Earth Observation between economic opportunities and legal profiles. The research focuses on the highly interdisciplinary intersection between space law, space economics and technology. The primary objective is to define a flexible legal framework that not only does not hinder, but rather accompanies technological and market development, extending the principles of prevention and precaution to the space environment. The application focus is on the use of EO data and artificial intelligence (AI) in the insurance sector - with a view to risk management aimed at enhancing the principles of prevention and precaution - to mitigate and contain catastrophic risks, with particular reference to index-based policies in agriculture. Once it has been established that the spread of this insurance product would bring considerable benefits to both insurance companies and customers, the analysis carried out leads to the identification of various legal issues and problems, in other words, various 'grey areas'. The research identifies three macro-critical issues that undermine confidence in the index-based policy system. The first concerns basis risk and algorithmic opacity and the risk that the calculated index (based on EO/AI data) does not reflect the actual damage to the crop, leading to disputes. The opacity of the calculation algorithms (black box) makes it almost impossible for farmers to prove the fault of the data provider. The second macrocriticality is the probative value of the data and the need to guarantee the integrity, incorruptibility and reliability of the satellite data used for compensation. The third and final macro-criticality investigated concerns space governance and the obsolescence of current space law, which is insufficient to regulate the rapidly growing private economic initiative and the associated risks. To overcome these challenges, various operational and regulatory proposals have been put forward. To guarantee data integrity, it is proposed that blockchain technology be associated with the EO data analysis process in order to certify, in an immutable manner, the integrity of the chain of custody of the processed data. This establishes a standard of procedural responsibility for the operator (DOS), borrowed by analogy from Article 2423 of the Italian Civil Code. In order to ensure contractual transparency, it is suggested that legal design be applied to clarify the semantics and structure of IBI contracts, making the causal link and compensation mechanism transparent. Furthermore, in line with the AI Act, an explainability obligation is required for AI models used in actuarial calculations, classified as high-risk systems. With regard to data governance, in order to modernise space law, it is proposed to move beyond the idea of exclusive ownership of primary data, adopting a model of access and reuse of raw data inspired by the Copernicus paradigm. Finally, given that the context analysed is characterised by the presence of dynamic risk, a risk management model is proposed that calculates insurance rates in a geolocalised and dynamic manner (based on Vulnerability, Exposure, Impact and Probability). This model creates an incentive for farmers to adopt ESG practices (e.g. precision farming), as a reduction in vulnerability measured by satellite leads to an automatic reduction in the insurance premium. The methodological approach adopted during the project is hybrid in nature, as it requires the overlapping of several methods of analysis and study attributable to the humanities but also to the STEM (Science, Technology, Engineering and Mathematics) disciplines. Therefore, the interconnection of knowledge and skills was relevant. The starting point is the analysis, in terms of positive law, of the national and international regulatory framework currently in force in the field under investigation. Looking also at doctrinal and jurisprudential formants, the modus operandi is characterised by the identification and framing of the legal problem in order to advance the most appropriate resolution through problem solving. Economic Analysis of Law (EAL) and Regulatory Impact Analysis (RIA) are integrated to quantify social costs and assess regulatory impacts. In addition, game theory and futures studies are used to model risks and anticipate the strategies of the actors. More specifically, the methodological tools of EAL have proved indispensable for identifying the optimal allocation of rights and protections provided for in legislation (i.e. for identifying regulatory gaps) and the dangers that may arise from them. RIA techniques were also used to assess the cost-benefit ratio resulting from the evolution of the technological tools covered by this investigation. All this was done using an approach consistent with futures studies, in the awareness of the uncertainty of the future and the consequent opportunity to think and act with a view to prevention and precaution.
30-gen-2026
Inglese
Ciocia, Maria Antonia; Gatt, Lucilla
CRESPI, Mattia Giovanni
CRESPI, Mattia Giovanni
Università degli Studi di Roma "La Sapienza"
223
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14242/357569
Il codice NBN di questa tesi è URN:NBN:IT:UNIROMA1-357569