How does risk management change as a result of the new supervisory requirements? And what benefit does an insurance company derive from data warehousing?
Not only the theoretical risk models themselves but also the data on which the models are based are supervisory certification aspects in the context of the EU’s Solvency II project.
That is why data warehouse structures are increasingly seen not just from a sales angle nowadays.
The MaRisk (VA) requirements, in force since the beginning of 2009, are a foretaste of the trend towards proof of integrity and transparency of data. An enterprise-wide data warehouse offers many benefits other than the fulfillment of regulatory criteria.
A data warehouse supports separation of the planning environment from the operational business world and creates a data history that is independent of the inventory system. It facilitates company-wide, incontrovertible indicators, flexible and expandable reporting and analysis options as well as audit safety.
The basic principle of a data warehouse is the use of a central data base for all discretionary applications (a “single point of truth”). The data is consistent and harmonized and the data flows are transparent.
A layer architecture has established itself for the implementation and standard models are frequently used for data modeling. So including new business areas in the data warehouse does not jeopardize the parts that have already been implemented (security of investment).
Fundamental success factors for a company-wide data warehouse are the gradual build-up of the data base and its swift implementation with measurable successes.
mgm consulting partners has extensive expertise in this area, uses its own standard model for modeling, and supports companies in the conception and implementation of a data warehouse.