Improve data quality and correct defects as quickly as possible
Systematic data quality management (DQM) came into the world of MEAG (the asset manager of Munich Re and ERGO) in 2016 with a prototype. The goal was to develop a system that performed fully automated quality checks as soon as data was entered and thereby noticeable improved the quality of data. The motto was thus: Correct defects as quickly as possible.
More than 200 MEAG users in various systems
Since 2016 several more IT systems have been linked up, including parts of operating systems and the risk management system. By 2020 more than 100 MEAG users were actively using the DQM system. Further operating systems were linked up in the course of subsequent projects.
In this use case, for example, there are therefore now 750 daily automated triggers of plausibility checks which are performed on up to 10 GB of data per day for almost 100 users at several locations and in several teams.
DQM as a Key Component of Digitalisation
Thanks to DQM, additional risks are identified and damage is avoided. The identification and handling of inaccurate data is also significantly more efficient. ‘DQM is a key component of digitalisation in the property sector and sustainably improves data quality,’ says Siegfried Korb, Head of Property Management Germany at MEAG MUNICH ERGO Assetmanagement GmbH.
Besides the plausibility checks, the existing approval tool has also been replaced by fully integrated automated plausibility checking in DQM.
Q-THOR’s Track Record
As a result, the DQM system has an excellent track record: Several hundred active users in a two-figure number of teams and almost 2,000 transactional plausibility checks performed per day. The next milestone is expansion to incorporate the issue of IFRS 9. The group will use the DQM system for data supply and plausibility checking and the number of users will more than double.
Using the standard software Q-THOR from BIG.Cube GmbH, MEAG is therefore able to guarantee its data quality in DQM, among other things.
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