Not to be under-estimated is the extent to which existing systems and databases will need to be adapted. Toronto Dominion Bank found there had been changes to a lot of systems to collect Basel II data and there was a need to build interfaces between systems that had previously not had cause to be linked. Ultimately, all of those huge estimates of compliance spend, made by analysts and consultants, is not theoretical. This is actual money being spent by banks, so no wonder consultants, systems integrators, and software and hardware suppliers are so keen on this market. Underpinning the data quality work at WestLB was a strong technology element. A year or so after Dr Gebauer took on the data quality officer position, he decided that the bank needed a more advanced IT-based tool that could measure elements of data quality such as error rates. This tool would replace its old Excel-based system of ‘juggling rules’, which Dr Gebauer felt was largely deficient. The application subsequently created to meet this need was built in one of the bank’s business units and not in the IT department. It worked directly on data fields and had a strong data profiling component. In practice this, said Dr Gebauer, managed to uncover some ‘very strange relationships in some very old databases’, many of which had long since disappeared off the radar. Now he was able to implement various proposals for business rules, based on any database. These rules were run periodically on targeted data sets, delivering accurate metrics including any variance. This enabled Dr Gebauer to devise further improvements. Sometimes you need to look at the big picture before you know you’ve got a problem. According to Rabobank International’s Theo van Koningsveld, ‘it became apparent the moment we built our CRM system’. With the bank being built up from different divisions, each with its own data system and descriptive language and reference ID codes for each field, the problem was all too obvious. Implementing a new coherent CRM system required a layer of technology to sit on top of the array of data sources. This project would only make sense if those sources were synchronised and mapped. The problem lay not with the quality of the isolated data
per se – ‘every division in itself had good enough quality data,’ said van Koningsveld – but once it was decided to take the overall view, the coherency started to crumble: ‘Everybody knew that if you started looking from a helicopter view on the client data that we had major problems.’ His team first spent weeks analysing the various data and ‘trying to define the real problem’. The bank then brought in consultants from IBM (it was using IBM’s Websphere for its CRM delivery). ‘They taught
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us all the steps in their banking model and the services they have around that,’ said van Koningsveld. ‘It was a very mature, well-thought out approach. They had done it at 40 other banks, so why re-invent the wheel?’ Under IBM’s guidance, the bank recognised that it needed
‘strong project stewardship’ from the outset. As one who had ‘seen the problem’, the bank’s COO in the Netherlands, Ralf Dekker, stepped into this role. Dekker was also a member of the managing board that was overseeing the work, with each division being represented on the project steering committee. From the outset Rabobank decided to make incremental moves on its disparate collection of data. In the first instance, it took it upon itself to ‘guarantee one language’. This, said van Koningsveld, would enable it to pin down all internal definitions to around 500 key terms. From here it could synchronise how each division described each data field. The bank knew this would be the most protracted task and placed it at the head of the queue. Indeed, just securing agreement was major work. The time that it took to talk to people and agree upon one common definition between IT and business divisions proved exhausting. There was much inter-departmental dialogue, but once it was approved by the managing board, it became ‘a kind of Wikipedia for both IT operations and the business’, said van Koningsveld.
As the next step, Rabobank set about reorganising its delivery of business reports so that they were no longer routed through each division but through a single, client-facing customer-care department. The benefit of a central point of view was obvious: ‘If a client has a problem in one division, every other division is also aware of it,’ noted van Koningsveld. But once Rabobank’s desk had been set up, he acknowledged that the bank needed to ensure all of its processes and procedures were ‘aligned and implemented properly’, and that people ‘really know their working instructions’. A lot of banks have been putting in place some form of
transformation layer. This is where the disparate data from the operational systems and other sources is mapped and converted into the required standard formats. This ETL (extract, load, transform) layer sits in front of the data repositories. It might be built in-house (as at ABSA) or sourced from a third party or a combination (as at Toronto Dominion, with this bank selecting Ab Initio Software Corp’s ETL tool on the retail side and in-house ones for other business areas). As mentioned below, ABSA was retaining its existing business/marketing warehouse and was building another for compliance. It was envisaged that once the bank’s Basel II requirements had been met, the ETL layer would be applied to both warehouses, with
Risk Management Systems & Suppliers Report |
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