User experiences
KRM is strong in a number of countries (such as China, Russia and Malaysia) but has little penetration in others (such as the UK). There were eight customers claimed in the Middle East by the end of 2011, with staff recruitment under way for this region.
China Construction Bank (Asia) (CCB Asia) signed for
KRM in December 2007. Created at the beginning of that year when Bank of America (BoA) sold its Hong Kong retail subsidiary, Bank of America (Asia), to China Construction Bank (CCB), CCB Asia soon found that it had lost the benefits of using BoA’s facilities, including its market risk service for systems and day-to-day calculations. Prior to the acquisition, the bank would receive figures for
areas such as its daily earnings-at-risk (Dear) from BoA. ‘We never really understood how that Dear figure came about, it was kind of like a black box to us,’ admitted Michael Leung, CIO of CCB Asia. ‘Bank of America did all the calculations and just gave us a number every day. We reported that number to the management and the regulator.’ Clearly, this situation could not continue. ‘We thought it’s
better for us to work out exactly how this market risk, this Dear figure or the VaR should be calculated for the local Hong Kong and Asia environment,’ said Leung. ‘We started to drill down to the technicalities and we only then realised that it’s such a complicated process.’ This triggered the search for a risk management system.
It looked at a couple, including Oracle FSS’s Reveleus, but a major factor in its decision-making was its existing relationship with Fiserv. Both Fiserv’s core system, ICBS, and KRM ALM were already in use, with CCB in Beijing also using KRM for certain calculations. ‘Not exactly the same as what we are after now, but they do have a relationship with Fiserv, so there was a bit of a referral from that bank,’ said Leung. ‘We looked at other options as well, but in the end we decided that the KRM solution would best fit our needs.’ Leung described the implementation
project that
ensued as ‘quite interesting’. ‘We started off with the usual requirements scheduling. Initially when we went about the project, we did not expect the difficulties and challenges we encountered later on.’ The main challenge came from the Hong Kong regulator insisting on the historical way of calculating the VaR figure. ‘This approach wasn’t the way we thought of earlier, and it’s not the way that the KRM software was meant to be used either. So that was a big surprise to us.’ As a result, there was a need to adapt the system. ‘It was more fine-tuning the KRM system to do VaR runs on a
more aggressive basis,’ said Chuck Rowland, MD, international sales and operations for Fiserv’s risk and performance division. The original functionality had to do with standard market valuation, variance, historical VaR and Monte Carlo VaR. ‘They
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were pretty much standard market risk methodologies,’ he said. ‘Basically, they needed to do some more simulation.’ To meet the regulator’s needs, some programming changes were needed to KRM, ‘but it was not a huge thing. It was more or less just understanding what exactly the changes were that it needed to make, and how many scenarios that the bank would typically want to run.’
The bank also wanted to use the system on Microsoft SQL
Server, where KRM usually runs on Oracle. ‘In this case, even though the bank’s parent in Beijing is using Oracle, it needed SQL. So we needed to do some re-scripting,’ said Rowland. ‘We’ve gone to the test labs with Microsoft and benchmarked the scalability.’ According to Rowland, the fine-tuning of KRM took ‘a couple of months off and on’. The changes for CCB Asia, along with others, went into release seven of the software. ‘CCB didn’t have to pay for all the development work. We said that’s good, we need to do it to better comply with the regulators, which is going to be useful to other clients as well.’ The implementation lasted about nine months, with the bank going live towards the end of 2008. The project team came from both the bank and the vendor with no external consultants involved. After going live, Leung said the system had helped the
bank’s operations, but there were challenges and lessons along the way. ‘Every time when we had a management meeting, our treasurer would report the Dear figure and that gave the management a feel of where we were in terms of the market risk portfolio,’ said Leung. ‘There were not many surprises, we would hear the figure and it was more or less the same every time. After we went live, it has varied a bit occasionally, so for the first time he has ended up having to explain why those variations took place.’ He said the bank had learnt from these incidents. ‘Those occasions gave us opportunities to tune the model and the calculations, to make it better and make it more stable, more predictable.’ Even after going live, there was work to optimise the system for the bank. ‘It was about managing the sensitivity, increasing the stability or at least being able to explain the variation from time to time,’ said Leung. Technical challenges came in the form of extracting the relevant data from other systems. ‘Every single FX contract, term deposit or savings account had to be reflected into the system for this to calculate,’ said Sanjeev Kumar, VP and systems manager at CCB (Asia). This is because the bank needed to do the VaR calculation with the banking book as well as the trading book, he explained. There were hundreds of data elements that needed to be fed into the market risk calculation, from both the banking and the trading books, and some elements could actually tilt the model quite dramatically. ‘Sometimes it’s very sensitive to certain data items. So we need to fine-tune that to manage those sensitivities,’ said Leung. He was happy with the end result of the project. ‘In a
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