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Underwriting methods and tools

Process support for fast processing

Methods and tools for the life/health sector

Process support for the primary insurer

A core part of the life insurance application process is the biometric risk assessment. To automate this process, the primary insurer often turns to a reinsurer, who in many cases provides such systems. Modern, flexible tools that draw on all available sources of information are needed to keep up with the constantly evolving requirements across all areas.

New sources of information open up new opportunities to collect data – also for use in the application review process.

  • Use of ERP data or doctor’s letters
    • An electronic patient record (EPR) contains structured and unstructured data. The structured data can be used to collect and further process information. The unstructured data, which includes doctor’s letters or hospital discharge reports, can be used directly in the risk assessment for complex applications. adesso supports easy access to the policyholder’s data, if necessary also with a context-sensitive logic. Access is not available unless the policyholder consents to this.
  • Data and analytics Predictive underwriting
    • Data and analytics methods make it possible to predict how a situation may unfold in the future based on data models. The data-driven predictive insights lead to more informed decisions. In combination with experience from processing claims, for example, the combinatorics of application data can help minimise risk.

Process support for the reinsurer

In order to review complex claims, the primary insurer provides information in every imaginable form and quantity. The systematic classification of these records and the extraction of data from them tie up valuable resources. We have the perfect solution for this problem: Aisaac.

Methods and tools for the non-life sector

Support during the underwriting process

In underwriting, the data provided by the primary insurer to the reinsurer is usually checked in a series of steps performed by hand. As a result, the data often has to be manually prepared, analysed and transferred to the individual experts – such as a natural disaster modeller, an actuary or even a lawyer – for review and analysis.

Tools that automate individual processes or support the manual ones can be of great help here. With the support of an AI, it is possible to check the wording with regard to the reinsurer’s UW guidelines and imprecisions in the wording in a different language. Thanks to the options available with semantic analysis, there is no need for a large number of contracts, meaning that this method can also be used at reinsurers for their individual and highly complex contracts. The wording is the basis for hedging risk. Oftentimes, however, it is given short shrift in reinsurance underwriting, not least because of the limited time available during the renewal phase.

Data analysis for major claims

Elaborate simulations with relevant assessments and possible recommendations for action for the primary insurer must be developed and carried out with regards to potential major claims especially in relation to natural disasters, which are occurring at increased frequency and becoming more intense and destructive. To assess the data required for the simulations, it is necessary to connect to existing systems at the reinsurer and employ data analytics methods to utilise the data accordingly.

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