IBM’s planned acquisition of Algorithmics, which was announced earlier this week (timed nicely on 1 September alongside two other acquisition announcements – NYSE Euronext buying Metabit and SunGard buying Finace), is just another example of the increasing trend within the vendor community and (to some extent) the industry at large of the alignment of risk management with data management. Two functions that were previously considered separately are now being at least mentioned in the same breath as each other; no wonder the vendor community is seeking to capitalise on that trend.
As ever with developments such as this, the main driving force can be put down to the barrage of regulatory requirements coming down the pipe. Just check out the recurring refrain of data quality throughout recent consultation papers, industry guidance and even regulation itself (see my previous blog on which here). Data transparency and reliability is being especially emphasised by regulators with regards to the risk modelling and management function. For proof, just check out the UK Financial Services Authority’s (FSA) guidance from earlier this year on operational risk standards (available to view on the FSA’s website here). The paper highlights the importance of the “clarity, quality and accuracy” of the data inputs to risk management systems and suggests regular data quality testing on the part of financial institutions.
But regulation is not the sole force at work here: the combination of risk modelling technology and reliable data sources can be a differentiator on the business (rather than compliance) level. Vendors have spent the last few years talking up the rise of ‘big data’ and its relevance to risk management and operational efficiency. IBM, Oracle, Teradata, Microsoft, SAS et al have been particularly keen on this space and have been promoting their own versions of a big data approach to risk management: the concept of quickly accessing reliable data for complex risk calculations for the business and regulatory requirements.
Even the US Office of Financial Research (OFR) has got in on the big data discussions with the vendor community. During a government organised roundtable back in July, Dilip Krishna, vice president of financial services at Teradata talked up the benefits of big data for a regulatory community aiming to more accurately track systemic risk (see more on which here). Moreover, the Commodity Futures Trading Commission’s (CFTC) data standardisation subcommittee is consulting Google on its own big data expertise from outside of the financial services community (see more on which here) with a view to understanding how to deal with all of its swaps data.
IBM’s Algorithmics acquisition is therefore a key part of the vendor’s extension beyond pure data warehousing and data management capabilities into the downstream use of that data within the risk function (see more on which here). A joined up approach across previously siloed functions is being championed by both IBM and its rivals, so any advantages that can be acquired along the way could give any player the competitive edge it needs.
Accordingly, IBM’s acquisition strategy is now in full force and Algorithmics will therefore be the first of a number of buy outs in this space. Given the number of risk management solution vendors out there in the market that are up for consideration – Thomson Reuters’ Kondor line, Misys etc – IBM should have enough choice to make a savvy strategic move or two. That’s if it can get there ahead of its rivals.
For its part, Oracle has been spending a lot of time in bolstering its data management related partnerships with EDM vendors such as PolarLake, GoldenSource and Asset Control (see more on which here) and, earlier this year, acquired data quality software provider Datanomic. Other rival, SAS launched a data integration layer for its risk management platform earlier this year: the SAS Detail Data Store (DDS) for Banking (see more here) and is now working on a capital markets specific offering. Dell recently acquired Oregon-based memory virtualisation specialist RNA Networks in July. And the list goes on.
These developments and much more will, no doubt, be up for discussion at A-Team Group’s upcoming Data Management for Risk, Analytics and Valuations conference in London on 17 October (see more on which here). We look forward to seeing you there…