Following its merger with Dresdner Bank in 2008, Commerzbank opted to integrate its risk management processes and instead of building an in-house solution for the data underlying those processes, it selected Asset Control’s AC Plus platform for the job. Speaking at last month’s A-Team Group Data Management for Risk, Analytics and Valuations (DMRAV) conference in NYC (see details of the London sister event coming up on 17 October), Alexander Natter, market data project lead and senior business analyst at Commerzbank, gave delegates a progress report on the rollout as it comes to a close.
Commerzbank has been moving towards a more integrated data infrastructure over the last few years; as noted by Reference Data Review back in September 2010, the focus has been on integrating both the customer and internal data acquired as part of its takeover of Dresdner Bank back in 2008. Natter explained to DMRAV delegates that now that much of the groundwork has been done, the most recent focus has been on quality assurance for the raw and derived data across the German bank’s business.
“The concern has been to ensure that there is a high level of quality of this data for internal and external reporting purposes,” he explained. On that note, the bank has opted to add the vendor’s AC Connect solution to its current setup in order to replace its in-house interface and supply data to downstream clients.
When the project kicked off back in the first quarter of 2009, the initial goal was to use AC Plus as a data hub on which all of the bank’s other systems could sit and pull data from. There were three main workstreams within the project to complete, according to Natter, comprising of synchronising the process of adding new instruments to the system with the front office, dealing with derived data and supporting the two risk systems (one from Commerzbank and the other from Dresdner) in terms of data feeds.
Natter noted that the risk management function remained a “very important client” for the project throughout; a theme that was reprised by many speakers during DMRAV. He also stressed the importance of the changing regulatory environment and its impact on the project as it went along. In the autumn of 2009, for example, when the project was a third of the way through, the team had to take into account new data requirements for value at risk (VaR) calculations. The volatility of the market meant that calculations such as stressed VaR were required and this necessitated changes to the underlying data flows into risk systems.
Overall, the system must also be very robust, he told delegates, due to the high data volumes involved: the infrastructure must support around seven million instruments contained in a two layer data model (one vendor dependent and the other a normalised layer of data).