It was a start at least but there was some way to go.
Following on from this positive action, in September 2007, a market report commissioned by Reuters and stemming from an international survey of operational managers and CTOs of some of the world’s largest financial services players, showed that the current EDM solutions market was characterised only by siloed specialist capabilities from multiple providers. So whilst security master data warehouse vendors like Goldensource, EAI vendors such as Polarlake, and middleware vendors such as IBM and Tibco fulfilled an important function, Gary Barr, global head of EDM at Reuters, believed that there was no single off-the-shelf offering delivering the one-stop data-shop option for capital markets. Goldensource was a prime building block at Daiwa Securities SMBC. When the bank set out on building its risk and finance architecture, standing data projects were fairly unusual and there were few vendors. Goldensource was felt to be enthusiastic about the project and to have an extensive, albeit complex, data model. That data model proved to be as comprehensive as anticipated, so the main development work was to build the interfaces to Bloomberg and Telekurs. Alongside Goldensource and Tibco, Fujitsu was used for data cleansing and software development, Reuters for implementation assistance with the middleware, and Oracle for database set-up and tuning. Deriving business gains from EDM is dependant on the ability of cleansed and normalised data to automate workflow within the enterprise. Results from the study showed that vendors and capital market participants already had the capability to source, create and store a ‘golden copy’ of this cleansed and normalised data – but there was an urgent demand for a solution that could provide the final building blocks of EDM, to bring together the framework and software to automate end-to-end data distribution across the enterprise. The big challenge in the industry is integration. Sourcing data and putting it into a warehouse is fairly straightforward. It is when you have to get the information out of the warehouse and plug it into the enterprise that the problems start. Often plans for restructuring are subject to degrees of
resistance, even if the logic is sound. Theo van Koningsveld, manager of the electronic distribution unit at Rabobank
International, admitted that some of the older managers within the wholesale unit were reluctant to acknowledge its worth. In the past, he said, some didn’t even share the income figures with more junior staff, but now everybody had become part of the team and could see all the information on a client. ‘It is much more transparent, internally.’ He believed part of the initial resistance lay in the suspicion that the system would uncover lower levels of cross-selling on the part of some older staff. ‘The young and enthusiastic account managers were fully in favour, of course, but everyone got used to it in the end.’ Rand Merchant Bank also found resistance. The all-
embracing nature of its project meant it crossed different divisions and responsibilities. It was seeking to implement a new operational model and end-to-end processes. This brought natural resistance, said Snyman, with each division having its own way of accounting and fearing it would lose some of this ‘uniqueness’. But, as he pointed out, there should not be anything unique about accounting. He emphasised the non-technical aspects: ‘It was an organisational challenge totally’. The
coordination challenge should not be under-
estimated. Not only have there been product silos but also risk silos for the different areas of risk and control, so silos upon silos. The coordination also extends back out to the rest of the business, with a clear emphasis on making full use of the data for decision making, which is a technical but also organisational challenge. There was previously a great deal of emphasis on aggregation geared towards balancing liquidity, market risk and counterparty risk and working out the impact on credit policies as a whole. The end result was virtually meaningless, with this activity needing to come out of the central white tower.
The emphasis now should be on only aggregating to
the appropriate point, which might be product, regional or entity level, with this then approved by the appropriate manager. There needs to be clear ownership, accountability and transparency, with the expertise of individuals captured alongside the numbers. This means the data has much more chance of being used for decision support and there should be much faster reaction.
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