# The Role of Data-Driven Methodologies in Weather Index Insurance
## 1 Introduction  
Climate change has resulted in acute difficulties for low-income economies. Extreme weather events, such as droughs or heat waves, can cause crop failures and threaten the livelihoods of farmers and the food security of communities [1]. Mainly, these concerns can be severe due to underdeveloped financial services, where communities have access to limited financial services or even none at all [2]. Crop insurance is a tool that mitigates risk in farmers' investments and is a growing market that reached USD36.6 billion globally in 2021 [3]. Globally, traditional insurance is one of the most widely used forms of protection for farmers, and traditional insurance calculates the indemnity by assessing losses after the occurrence of a weather event. However, it has two main problems: adverse selection and moral hazard [4]. Adverse selection occurs when there is a lack of symmetry in the information prior to establishing a deal between a buyer and a seller. A moral hazard occurs when there are fraudulent behavioural changes that might occur which could likely increase the risk of loss when a person knows that insurance will provide coverage. An approach to mitigating risk is the use of index insurance which estimates the indemnity with an independent indicator of crop loss, such as a weather index [5]. In addition to reducing expenses, index insurance allows researchers to predict an individual farmer's losses at different costs and different levels of accuracy [2]. The primary distinction between these different kinds of insurance is that the payoffs for the index insurance are determined by measuring weather variables [6]. Moreover, these types of insurance programs can also be beneficial for rural areas with social conflicts [7; 8], as in the case of crop-productive regions in Colombia. Recent studies reveal that index insurance uptake reduces conflict risks caused by rangeland conditions by 17 to 50% and helps reduce poverty traps [9]. Therefore, social protection programs primarily represented by index insurance programs act as a protective factor in regions with complex risk profiles, where farmers are exposed to weather and conflict risks that may interact. This information is needed by governments to promote this type of insurance adoption. When designing and implementing index insurance, it should also be recognized that it is vulnerable to high-basis risk due to imperfect relationships between the weather index and the risk it covers. Basis risk represents the difference between the payout or indemnity, as estimated by the weather index, and the policyholder's actual losses [5]. This basis risk can take three forms: design, temporal, and spatial. Design basis risk occurs when the selected index does not correctly explain the target crop [5]. Temporal basis risk arises as a result of inappropriate period selection used to derive the index, while spatial risk arises from the spatial distance between the location where climate index data are collected and the location where losses occur [5]. Larger amounts of basis risk lead to high levels of remaining uninsured risk. Consequently, the index insurance contract is not cost-effective for farmers [10]. In Colombia, agriculture is one of the most important socio-economic sectors, accounting for 7.43% of the gross domestic product (GDP) in 2021 [11]. Agricultural land constitutes 35% of the national territory or 39 million hectares of land [12]. According to the National Administrative Department of Statistics (DANE by its Spanish acronym), 48.2% of the total agricultural production is concentrated in the departments of Antiquia, Valle del Cauca, Tolima, Cundinamacra, Meta, and Narino, where agro-industrial products such as tubers, bananas, and cereals are grown [13]. Despite the sector's importance, agricultural insurance in Colombia has a low penetration rate. As of 2014, only about 2.4% of the sown crop area of about 7.1 million hectares was insured [2]. Therefore, farmers are exposed to different types of risks and have to manage them.