  Data driven approaches to problem solving are, in many regards, the holy
grail of evidence backed decision making. Using first-party empirical data to
analyze behavior and establish predictions yields us the ability to base
in-depth analyses on particular individuals and reduce our dependence on
generalizations. Modern mobile and embedded devices provide a wealth of sensors
and means for collecting and tracking individualized data. Applying these
assets to the realm of insurance (which is a statistically backed endeavor at
heart) is certainly nothing new; yet doing so in a way that is privacy-driven
and secure has not been a central focus of implementers. Existing data-driven
insurance technologies require a certain level of trust in the data tracking
agency (i.e. insurer) to not misuse, mishandle, or over-collect user data.
Smart contracts and blockchain technology provide us an opportunity to
re-balance these systems such that the blockchain itself is a trusted agent
which both insurers and the insured can confide in. We propose a "Smart Auto
Insurance" system that minimizes data sharing while simultaneously providing
quality-of-life improvements to both sides. Furthermore, we use a simple game
theoretical argument to show that the clients using such a system are
disincentivized from behaving adversarially.
