Chinasoft International Ltd (CFTLF)

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Chinasoft International launches an independent and controllable life insurance actuarial localization program to efficiently help the digital transformation of insurance industry customers.

source
http://www.chinasofti.com/news/2194.htm

2021-05-08

Introduction
The business of insurance companies has grown rapidly, and the number of insurance policies has increased exponentially. Traditional actuarial systems can no longer support the operation of such a huge amount of data, which seriously affects the accuracy and timeliness of financial evaluation results; based on the innovation trend of the insurance industry and the development requirements of actuarial systems, ChinaSoft International relies on its own expertise in big data and insurance actuarial fields. Rich implementation experience and R&D capabilities, drawing on the implementation experience of the IFRS17 life insurance actuarial big data system of large insurance companies, launched a targeted life insurance actuarial big data platform system solution, which is a localized alternative solution for life insurance actuarial systems.

The life insurance actuarial big data platform system adopts mainstream big data technology, which plays an important role in supporting and promoting the accounting work of the actuarial department, providing more accurate and efficient data evaluation support for the operation and development of insurance companies, and comprehensively improving the speed and operation of the system Efficiency and data accuracy of the system. ChinaSoft International will continue to innovate on the road of building an industry-leading actuarial accounting and experience analysis platform, and provide a safer, more stable and efficient overall solution for the digital development of customers in the insurance industry.

Solution
The life insurance actuarial big data system provides a complete set of solutions for the reserve accounting and data experience analysis of the life insurance actuarial department. It realizes from data collection, reserve calculation to the output of the final model point data. Under the premise of ensuring data quality, greatly Improve the actuarial operation efficiency and meet business requirements. In the experience analysis module, through the in-depth analysis and processing of various dimensions of data, the analysis of operating experience is strengthened, and the in-depth development of insurance company characteristic products is expanded.

Data collection:
Daily batch processing and regular collection of data, and data such as insurance policies, accounts, income, expenditures and other information in the collection module are generated on the actuarial big data platform for use by the reserve settlement and experience analysis modules.

Reserve calculation:
After the collected data is calculated and processed, it will enter the reserve calculation node; when calculating the life insurance reserve, it needs to be calculated and calculated separately according to different insurance categories (such as traditional, dividend, universal, investment chain, etc.) Stored in separate tables; at the same time, during data calculation, the data will be automatically corrected according to the set data correction rules to ensure the completeness and accuracy of subsequent data.

Model point calculation:
After the reserve calculation data processing is completed, it will enter the model point calculation node; in the model calculation, data processing is performed according to the data of the calculation node to generate the wide table data required by the model, and then according to the wide table data, Generate single-order and grouped model point data for data analysis and processing.

System function module
Based on ChinaSoft International's life insurance actuarial big data implementation plan in the insurance industry, we sorted out the technology and functions of the life insurance actuarial big data system, and designed and generated corresponding implementation plans.

Data storage architecture
According to the storage structure from the source layer, basic data layer and analysis data layer, the data storage, data verification, data standardization processing and data summary processing are carried out on the data imported into the big data basic platform to realize the universality of the data. And repeatable data conversion.

Business integration on the cloud
Provides a hybrid cloud integration platform for on-cloud and off-cloud applications, which can realize single or hybrid cloud integration scenarios such as cloud applications and local applications, master data, IoT, and cross-network integration.

Customer case
A large insurance company's life insurance actuarial big data system project:
With the digitization process and the development requirements of the future actuarial system, a large insurance company needs to build an accurate and efficient actuarial big data platform to support the rapid increase in business in order to improve the efficiency of operation and development Safe and stable operation of volume and data evaluation.

ChinaSoft International provided an overall solution for the project based on the localized replacement of the life insurance actuarial big data platform, and completed the construction of the two major functional modules of reserve accounting and experience analysis; at the same time, the system was based on the requirements of IFRS17 International Accounting Reporting Standards and implemented IFRS17 Actuarial reserve module construction and interface docking. The system uses the mainstream spark ecological big data computing engine, which greatly improves the timeliness and accuracy of data processing.

Two functional modules
Reserve accounting:
Mainly includes actuarial data collection, data calculation, DCS calculation and income and expenditure checking functions.

Empirical analysis:
It mainly includes functions such as short-term insurance calculation, serious illness calculation, critical illness calculation, warning line, surrender rate, commission and other functions.
In the data collection function, Spark-SQL technology is mainly used to collect the data into the data collection table; after the collection is completed, data calculation and verification will be carried out. Since this module involves the operation of a large amount of data, this module mainly uses Spark-Core technology; during calculation, the correct calculation data will be put into HIVE, and the data that needs to be corrected will be put into Hbase, and the data will be corrected and recalculated later; after the data calculation is completed, the calculation result will be Perform DCS data calculation, and then generate the corresponding model point file.