Actuaries and underwriters face multiple data processing challenges when incorporating insurance companies’ portfolios, be it diverse or proprietary file formats, data structure, low-quality data or fragmentation.
This is especially acute each winter, when reinsurance companies renew their customer contracts. Each data file can grow to tens of gigabytes in size, and this adds up to over hundreds of terabytes. These must be stored and processed in a secure and sustainable manner, and must also comply with regulatory requirements such as GDPR and corporate policies.
Actuaries or underwriters experience difficulties analysing the data thoroughly as they are working on multiple policies at the same time, and are unable to efficiently clean up the high volumes of data in order to perform annual portfolio or market analyses.
We propose storing the most common file formats in Microsoft Azure Cloud. This technical solution is scalable, with virtually unlimited storage space. Based on Microsoft Azure’s automatically scalable infrastructure, users can access the data through a web interface to perform analysis and run benchmark models. This solution enables data representation to support different types of analytics while increasing data quality.
Who should attend:
Chief Technology Officers
Chief Information Officers
Chief Data Officers
Heads of Data
Underwriters
Actuaries
Architects
Insurance and reinsurance professionals
Technical level:
This is an intermediate-level webinar for insurance and reinsurance professionals with a working proficiency of data architecture frameworks.
High-Volume Exposure Data Processing with Microsoft Azure | Wednesday 26th July 2023 (12:00 - 13:00 BST)
Webinar: High-Volume Exposure Data Processing with Microsoft Azure | Wednesday 26th July 2023 (12:00 - 13:00 BST)
Processing high-volume data to accelerate policy renewal in reinsurance.
What you will learn:
- How Microsoft Azure can leverage your treaty renewal process through automation
- How to apply data scalability and data quality to your exposure data workflow
- How to engineer a stable and future-proof solution based on real-life use cases