The tools developed as part of the SLIPO project were tested during the last half-year by Munich Re on the basis of a concrete example of use. The project was intended to show how SLIPO technologies can support Munich Re in evaluating and finally merging geodata from different sources.
Munich Re is one of the world’s leading reinsurers. Munich Re offers a full range of products, from traditional reinsurance to innovative solutions for risk assumption. Especially when clients require solutions for complex risks, Munich Re is a much sought-after business partner. Munich Re has clients – generally insurance companies – worldwide.
For Munich Re, geo-analytics is an integral part of risk management. Until the late 1990s, Geographic Information Systems (GIS) were at most used as “isolated solutions” to support geo-experts. Today, many insurance professionals (mainly property underwriters) use complex GIS applications in their day-to-day business since they are integrated as a key component into their company IT. Meanwhile, the range of possible applications covers virtually the entire underwriting process. Everything from data collection and geocoding of insured risks through risk analysis (accumulation and identification of value concentrations and patterns), all the way to risk modelling and the visualization of results.
Risks usually have a geographical reference. If there are objects to be insured, e.g. in the immediate vicinity of a river, this may result in an increased flood risk. In order to be able to analyze, assess and evaluate the risks of insured objects as accurately as possible in advance, it is therefore necessary to have more precise and as far as possible complete spatial data and appropriate, sophisticated analysis methods. On the one hand, the data are based on classic natural hazards maps, which Munich Re makes available via its own service called NATHAN. Further bases for a risk assessment are addresses, properties or exact positions of the objects to be insured. These so-called points of interest (POI) must be complete and geographically accurate. Of course, the General Data Protection Regulation (GDPR) must be considered here.
Munich Re combines a large number of different and globally available data sets when creating risk analyses. In addition to in-house POI databases of insured objects or objects to be insured, information from various commercial and OpenData POI data providers is also included.
The objective is to examine, compare, merge and unify the POI data sets from different sources in an automated process. From the various individual data lists, a homogeneous and as complete as possible target data set is to be generated that also contains no duplicates. The data management processes associated with data homogenization currently present a challenge for Munich Re, since the combination of different data sets currently entails high manual effort.
Concrete example of use:
In the concrete test example, the use of SLIPO technologies brought together address lists of hotels based on four different providers. The address lists of the various providers had different numbers of POIs and also had different attributive characteristics. For example, some vendors have information about the number of employees and phone numbers, while others only include addresses and geographic coordinates. Even deviations that result from different hotel and company names had to be taken into account in a reconciliation.
As a special challenge for the test case, different alphabetic spellings of hotels could be identified for an example of use in Thailand (e.g. hotel names in Thai). Here, a transliteration and standardization of the spellings in the context of a pre-processing was considered.
Results & Benefits:
The example of use showed that the SLIPO tools meet the current requirements of Munich Re in the area of POI data processing and provide good support. As part of an internal project, Munich Re examined and evaluated the results provided in detail. Currently, the possibilities and perspectives for a SLIPO integration and the further and future application possibilities of SLIPO are being evaluated at Munich Re. WIGeoGIS supports Munich Re as a SLIPO partner in this project and provides information on current developments and project progress.
The test project identified valuable new practical requirements for SLIPO, which will be incorporated into the further development of the SLIPO project. For the long-term success of SLIPO, it is essential to incorporate concrete practical requirements during the development phase.
“For me, this parntership is a promising example of how goal-oriented, practical and successful research and business have to work together,” says Andreas Siebert (Head of Geospatial Solutions at Munich Re).