The FINANCIAL -- Big data is now being used to improve the identification, modelling and insurance of risks. Munich Re is taking advantage of these opportunities to develop new insurance solutions and services in conjunction with clients and partners. Extended IT and analytic competence is already being utilised – for example, in the early detection and trend analysis of fire losses.
Digitalisation and new technologies mean that far greater volumes of data are becoming available for evaluation within a much shorter time frame. Data analysis can be used to examine client portfolios to reveal trends, improve processes, optimise holdings, and provide targeted support to sales. The more global and comprehensive the data basis, the more valuable the data will be. The new dimensions of data and their analysis require some competences that not all insurance companies have. New competitors may be able to analyse data sets more quickly and apply the results in new applications – thus placing traditional insurers under pressure, according to Munich Re.
So there is also a strategic dimension to big data. "The most important aspects are the will and ability to invest in sufficient resources and work together with the right partners”, explained Ludger Arnoldussen, member of the Board of Management of Munich Re. "That is exactly what we are doing when building up our own know-how and IT structures." In order to be able to harvest information more quickly, the topic of big data is a key part of innovation processes at Munich Re. "It means new, clearly defined and more flexible insurance solutions and support services for our clients. We are seizing these opportunities – with our own resources, and supported by external specialists. We are also regularly involving the clients at an early stage in order to develop perfectly customised solutions and applications that can also be adopted at a global level."
There are already examples of how big data tools can be used to improve the pooling of information and make processes more efficient so as to create customised or totally new insurance solutions:
A fully automated monitoring of 7,000 digital news channels with a daily volume of 250 gigabytes allows fire losses in the United Kingdom and the USA to be recorded more quickly and cheaply. Comparing this data with the risks in portfolios allows for better identification of risk patterns, so that claims management can be faster and more effective.
In order to allow for better loss assessment and resource management, 16 terabytes of data volume from Munich Re, its clients and third parties have been combined on a nat cat platform for risk management purposes. The platform is already in use in Mexico, and will shortly be available in the UK.
Artificial intelligence will play an increasingly important role in the collection and processing of big data volumes in the future. It is already a fixed part of such processes – for example, in the analysis of large volumes of text and in loss assessments using photo analysis, based on data derived from satellites and drones. Such technology was recently used in the USA, for example, in the wake of Hurricane Matthew.
Artificial intelligence should be of great assistance to people in supporting their work and standardising routine processes. "But even in the long term, automation cannot replace strategic decision-making and maintaining good customer relations," stressed Arnoldussen.