Operational risk is the risk associated with an organization’s business operations. According to the Basel II accords, this risk is described and defined through the aggregate loss distribution (LDA), which establishes a series of parameters for risk management, giving rise to the basic principles for creating insurance indices. For this reason, this article develops and analyses a Hidden Markov Model to evaluate the future impact of climatic events on different tourist destinations worldwide, integrating the structure defined by the PANAS-t scale (Positive and Negative Affective Scale) in order to integrate the experiences shared by travellers on a social network such as Twitter into the LDA distribution, taking weather conditions in a tourist destination as a common element. The latter establishes the basis for developing index insurance to protect travel, experiences, and tourism packages that may be affected by an adverse weather event. The results show how the LDA distributions evolved towards leaner LDA distributions with positive skewness coefficients for weather patterns that determine low rainfall, while these distributions showed higher associated losses and skewness indices close to zero; this is following the postulates that define parametric insurance or agroclimatic insurance for the protection of activities in different sectors of the economy, including the agricultural sector.