Mining Insurance Data at Swiss Life

Abstract Huge masses of digital data about products, customers and competitors have become avail- able for companies in the services sector. In order to exploit its inherent (and often hid- den) knowledge for improving business pro- cesses the application of data mining technol- ogy is the only way for reaching good and ef- ficient results, as opposed to purely manual and interactive data exploration. This paper reports the first steps of a project initiated at Swiss Life for mining its data resources from the life insurance business. Based on the Data Warehouse MASY collecting all relevant data from the OLTP systems for the processing of private life insurance contracts, a Data Min- ing environment is set up which integrates a palette of tools for automatic data analysis, in particular machine learning approaches. 1 Introduction The exploding amount of available digital data in most companies due to the rapid technical progress of hard- ware and data recording technology has even more in- creased the tradeoff between just managing the data on the one hand and analyzing resp. exploiting the knowledge hidden in the data for business purposes on the other hand. The supply side of data management is characterized by huge data collections with a chaotic structure, often erroneous, of doubtful quality and only partially integrated. On the demand side we need ab- stract and high-level information that is tailored to the