- Motivate the relevance of insurance
- Describe analytics
- Describe data generating events associated with the timeline of a typical insurance contract
This book introduces the process of using data to make decisions in an insurance context. It does not assume that readers are familiar with insurance but introduces insurance concepts as needed. Insurance may not be as entertaining as the sports industry nor as widely familiar as the agricultural industry but it does affect the financial livelihoods of many. By almost any measure, insurance is a major economy activity. On a global level, insurance premiums comprised about 6.3% of the world gross domestic product (GDP) in 2013 (Source: International Insurance Fact Book: 2015). To illustrate, premiums accounted for 17.6% of GDP in Taiwan (the highest in the study) and represented 7.5% of GDP in the United States. On a personal level, almost everyone owning a home has insurance to protect themselves in the event of a fire, hailstorm, or some other calamitous event. For another example of how insurance affects people personally, almost every country requires insurance for those driving a car. So, although not particularly entertaining nor widely familiar, insurance is an important piece of the economy and relevant to individual livelihoods.
Insurance is a data-driven industry. Like other major corporations, insurers use data when trying to decide how much to pay employees, how many employees to retain, how to market their services, how to forecast financial trends, and so on. Although each industry retains its own nuances, these represent general areas of activities that are not specific to the insurance industry. You will find that the data methods and tools introduced in this text relevant for these general areas.
Moreover, when introducing data methods, we focus on losses that potentially arise from obligations in insurance contracts. This could be the amount of damage to one’s apartment under a renter’s insurance agreement, the amount needed to compensate someone that you hurt in a driving accident, and the like. We call these insurance claims or loss amounts. With this focus, we can introduce generally applicable statistical tools and techniques in real-life situations that can be used directly.