Analysis and Use of Telemetry Data for Car Insurance Premiums

Sammanfattning: Paydrive is a pioneer in the Swedish auto insurance market. Being able to influence your insurancepremium through your driving is a concept that is still in its early stages. Throughout this thesis,an attempt to consolidate the vast amounts of data gathered while driving with neural networkshas been made, together with comparisons to the currently existing generalized linear models. Inthe end, a full analysis of the data yielded four distinct groupings of customer behavior but becauseof how the data is structured the results from the modeling became sub-optimal. Insurance datais typically very skewed and zero-heavy due to the absence of accidents. The original researchquestion is whether it is possible to use two neural networks, calculating the probability of anaccident, r, and the size of a potential claim, s respectively. These two factors could be multipliedto determine a final insurance premium as c = r · s. Using statistical standards and tools such as the Gini-coefficient, R2 values, MSE, and MAE themodels were evaluated both individually and pairwise. However, previous research in the fieldshows there haven’t been big enough advancements in this area yet. This thesis comes to the sameconclusion that due to the volatile nature of neural networks and the skewness of the data, it isincredibly difficult to get good results. Future work in the field could result in fairer prices forcustomers on their insurance premiums.