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Insurance sector
Projects from the insurance industry
We use our expertise to support insurance companies in optimising their data management processes with advanced business intelligence solutions. In doing so, we benefit from our understanding of operational data structures in existing systems as well as in the intermediary, broker and direct business across all insurance sectors.
The challenges
In the insurance sector, data plays a crucial role in risk assessment, policy design and claims settlement. However, insurance companies are often faced with an outdated IT infrastructure and the challenge of efficiently extracting relevant information from a flood of data and making it usable. In addition, new regulatory requirements such as Solvency II and the IDD Directive require precise data processing and analysis. Competition from digital insurance platforms and insurtechs is increasing the pressure to bring innovative and customer-centric insurance products to market faster.
Our contribution
Our contribution
29FORWARD has acquired in-depth expertise in the insurance industry since it was founded in 2013. We know the specific requirements and regulatory standards of the industry inside out and support you in optimising your data architecture, from legacy systems to the use of cloud technologies. Our goal is to make your processes in risk management, policy administration and claims settlement more efficient and effective through intelligent data solutions.
1. example project
Review data mining project
For the marketing department of an insurance client, we reviewed an innovative data mining system that enables the efficient development and testing of various analytical models. The client, already well versed in statistical methods and the use of specific software, was looking to optimise and refine its capabilities, particularly with regard to the interpretation and communication of key figures. Through our collaboration, the client was able to significantly expand its competences in these areas, resulting in increased confidence in using the software and analytical models. A particular success of the project was the improvement in the communication of analysis results to internal target groups, which significantly accelerated and optimised decision-making within the company.
Successes
Faster interpretation of the models
Improved communication
of characteristic values to the recipient group
More flexibility
in the use of the software
More flexibility
in the use of the software
2. example project
Property insurance portfolio system migration in an international insurance group
In this project, the data from the legacy application of the portfolio management system of an international insurance company was transferred to the new portfolio management system. Both the contract data and the associated collection/disbursement and commission data were migrated. In order to check the quality and correctness of the migration, we developed a test concept that took into account both cross-interface (end-to-end) and detailed tests at contract level. By carrying out the tests correctly, the following aspects of the data migration could be checked for correctness:
Successes
Completeness and correctness
of the migrated data
Smooth production transition
thanks to prior process testing in the target system
Direct functionality
of the peripheral systems with production transition
Direct functionality
of the peripheral systems with production transition
Specialist KPIs
verified in advance
3. example project
Test automation with Tosca/HP ALM for portfolio system migration of a life insurance company
Migration of the portfolio system to a proprietary development of the customer for the life division. This involved migrating data from the current time slice as well as from the history. Migrating the history is always a challenge during migration, as not only the data from the policy management system has to be migrated in historicised form, but also the associated claims and benefits, payment transactions, partner data, commission and documents.
Successes
Integration of the automated migration tests
into the existing and familiar test environment
Reduction of the test effort
by including the standard test cases in the test automation
Automated test documentation
für Aufsicht und Revision bei Auftreten von Testfehlern
Automated test documentation
für Aufsicht und Revision bei Auftreten von Testfehlern
Other sectors
Banking sector
Retail trade
Public sector
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