data sources might well have multiplied, there are still manual hand-offs and this is likely to be another area of focus for the regulators. An announcement in early 2009 by Goldensource regarding an extension of its data management platform for derivatives reflected a perceived increased demand, with the supplier creating templates and models for the most widely used exchange-traded and OTC contracts. The approach could be to create a mirrored version of the information, which is updated and available in real-time. This would be much more readily available than the data residing in legacy systems that might have been in place for 15 years and could still be there 15 years from now. It would probably be hooked into a real-time messaging bus from vendors such as IBM with MQ, Tibco and Oracle. Of course, the battle is not won when a solution has been implemented. There is a need to keep moving forward to realise the investment. There needs to be clear data ownership, with business commitment to maintain the data. New ideas from the business should be welcomed and integration and mapping of data should feature in future business projects. There is a temptation to relax after the first phase, said Hare, but data must be kept up to date and accuracy must be maintained – it is easy to under-estimate the ongoing maintenance effort. One bank putting a lot of the theory into practice is HSBC, which has been building a data utility within its One HSBC strategy. This spans investment banking, securities services, wealth management and asset management, and will act as a shared service for the rest of the bank. It constitutes a single front-end securities master, with data distributed out to the bank’s back-end systems. HSBC had been a long-standing customer of Goldensource but on a traditional silo basis; now it is seeking to use this vendor’s platform for the bank-wide utility. The drive was coming from the top, said Neil Vanlint, managing director, Europe and Asia, at Goldensource, in the form of Ken Harvey, the bank’s global CIO/COO. Another part of HSBC’s data management is the Veredata


tool from UK-based Empowered Systems. This is being used to address the problem of data integrity. The issues of missing, duplicate or incorrect records hamper exposure management and enforce overly conservative credit grade assumptions, which ultimately means expensive over-statement of capital requirements. Reflecting the scale of the task, HSBC’s project with Empowered Systems covers more than 4000 corporate customer groups, with over 2.5 million records from more than 200 applications. The aim is to consolidate,


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cleanse and analyse the master dataset, with more accurate grouping of customers, more accurate regulatory reporting and more accurate capital calculations. Some of the more straightforward data cleansing and management is now done offshore, with the bank seeking an enterprise-wide approach to this within One HSBC, as with everything else. Clearly, this isn’t a new revelation, even if the financial crisis emphasised the fact that accurate and up-to-date data was either not available or not acted upon. One reason that things can become no longer tenable


is rapid growth. This was certainly a prime driver at Rand Merchant Bank. The bank decided its finance systems were outdated and ‘like a lot of mid-sized banks’, it was too reliant on spreadsheets for a lot of its accounting, said Snyman. In part, the need had become acute because of the rapid growth at the bank. From being a relatively small investment bank, it had become part of a much larger group, FirstRand Group, which included one of the country’s largest retail banks, First National Bank. The ‘sudden, massive growth’ brought the need for financial transformation, he explained. ‘It was just something we had to get done.’ When the proposal was put to the bank’s board for funding


approval, the emphasis was on a business project, not a technology one. The new solution was meant to cover accounts payable, accounts receivable and i-procurement. If it had been merely about replacing the general ledger, then this would have been straightforward. It had a Dodge Group-derived GL which was neither multi-currency nor event driven. Finance was using different extracts from those being used by the risk department and there was a lot of reconciliation and manual activity. In effect it was seeking a ‘finance transformation’, said Snyman. This meant a new operational model and new end- to-end processes. The situation was summed up by a report from specialist risk consultancy, Lepus, in association with data specialist, Asset Control: ‘The unprecedented levels of data now flowing around the financial services industry are forcing both buy- and sell-side firms alike to reassess the viability of their existing data management systems. As emerging business pressures have taken hold, so well oriented data architectures have lost their shape and descended into a mass of tightly defined silos. In such instances, independent data marts merely serve individual business lines or functions and as such it is liable that multiple versions of the truth come into existence.’ Certainly the scale of the data that needs to be held,


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