Reduzindo a Incerteza no Mercado de Seguros: Uma Abordagem via Informações de Sensoriamento Remoto e Atuária

Any insurance contract includes two key parameters: the premium rate and the indemnity. The methodology for calculating the premium rate is fundamental to avoid information asymmetry problems while methods to monitoring the insured object can be useful to measure and control losses. Usually uncertainties in relation to the cash flow of companies in a contingent market are high. This study proposes that this uncertainty can be reduced through alternative pricing methods based on Bayesian hierarchical models and geotechnology. The methodology allows for a better understanding of the temporal and spatial dynamic of the cash flow of an economic agent in the crop insurance market in Brazil at municipality level. The results show that fair premium rates can be precisely estimated using the pricing methodology and that geotechnology brings about significant improvements in quantifying crop losses.