I’ve been spending a lot of time recently looking at how the concept of big data might be applied to capital markets. Part of this work will end up in a white paper I’m currently writing, but a lot of it was in preparation for our Data Management for Risk, Analytics & Valuations conference that took place in London on 17 October. And it seems that some savvy practitioners already have a handle on how big data could help them manage the huge amounts of both structured and unstructured data they expect to be required to deal with in the very near future.
Regulatory and business pressures are driving firms to invest in risk management functionality such as on demand analytics capabilities, said Stuart Grant, EMEA business development manager for financial services at Sybase, during his keynote speech at A-Team Group’s Data Management for Risk, Analytics and Valuations conference in London. There has been a serious increase in appetite and budget for these analytics capabilities over the last couple of years and there are solutions out there that enable you to build on existing architecture rather than ripping and replacing, he explained.
Risk management teams should not attempt to boil the ocean by adopting a big bang approach to risk management change projects on an enterprise scale, agreed panellists during this afternoon’s session on data collection, normalisation and orchestration at A-Team Group’s Data Management for Risk, Analytics and Valuations conference in London. Firms should instead adopt an incremental approach at the front office desk level, where the benefits and deliverables are clear to the individual business line owners, said Simon Tweddle, risk management COO and interim head of market risk management at Mizuho International.
Rather than relying on data from external sources, firms should instead aim to create it from source documents, said Stuart Grant, EMEA business development director for financial services at risk management solution vendor Sybase, during this afternoon’s keynote speech. Speaking to attendees at A-Team Group’s Data Management for Risk, Analytics and Valuations conference in London, Grant explained that the industry could benefit from a degree of innovation in the data creation process in order to take that responsibility out of the hands of third party providers.
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PolarLake has responded to market – and regulator – demand for a real-time consolidated view of trade, position, reference and client data that can inform operational efficiency, risk management and compliance with a virtualised data warehouse solution based on service-oriented architecture (SOA) and semantic technologies.
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This week sees the release of an industry briefing we prepared for Sybase entitled ‘Managing Risk Data in the Siloed Enterprise’. I’ll be presenting the key findings at an event in London on Tuesday, where I’ll be joined by a group of risk managers and data architects – as well as Sybase’s Stuart Grant, IDC Financial Insights’ Matt Clay and Deloitte’s Julian Leake – to talk about what’s emerging as our industry’s thorniest problem: how to extract data required to meet the reporting needs of senior management and regulators from the “spaghetti crow’s nest” of data repositories and plumbing connections that is today’s financial markets enterprise.
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