Martijn Groot analyses the impact of the Fundamental Review of the Trading Book on market risk and banks’ data management practices
FIMA: 8th – 9th November, London
Regulation remains a dominant theme, both as a driver of near term requirements and as an agent for change. The industry is holding its breath for January 3rd 2018 when the new MiFID II regime starts; yet on the horizon the GDPR looms large.
The EU General Data Protection Regulation (GDPR) raises a number of questions, including potential regulatory conflicts around data retention and the right for individuals to have their personally identifiable information (“PII”) erased, which raises fundamental questions as to how institutions will manage the regulatory hierarchy. To further complicate matters, the bar to inadvertently violate GDPR is low, especially when using cloud services and multiple data centers. It will therefore become ever more important to closely watch what happens with PII at a granular level.
Other than making sure the business cost-effectively manages its regulatory requirements, data management professionals face a greater challenge in providing high quality data in a timely fashion to a larger set of users in operations, mid office and business enablement for the business lines themselves. This calls for a new view on data sourcing, mastering and integration.
RegTech Summit for Capital Markets: 16th November, NYC
There was a uniformity of consensus regarding the need for better technology to handle the regulatory requirements and the data to support them.
This changing technology landscape highlights a shortage of modern tools to assist; most organisations’ current infrastructure requires manual intervention, with mixed data requirements and a lack of systems that serve this well.
RiskMinds: 5th – 7th December, Amsterdam
Firms are still actively working on FRTB despite regulators in different jurisdictions delaying implementation.
Towards the close of the main event there was a livestream on the press conference from the Governors and Heads of Supervision on the finalisation of the Basel III reforms, in which the revised FRTB implementation timeframe was announced.
However (fortunately), firms have learnt from the regulators’ delay to MiFID II and their resultant decision to slow down their compliance initiatives; this is a mistake the industry is keen to avoid again.
Moreover, several US banks announced their FRTB initiatives, where previously it seemed most were waiting on the incumbent administration’s decisions with regards to regulation.
Trading book regulation aside, many firms are still looking to optimise their market data management to adequately deal with the additional valuation adjustments required under EBA rules. What is clear is that risk and valuation processes have become increasingly data intensive and that many firms’ existing information infrastructures are not equipped to deal with a larger variety of data sources and a steep rise in data volumes.
The Inflection Point
So what does all this mean for data management professionals?
It is becoming increasingly apparent that there is no longer a single, standard data management model that works for very different stakeholder. Enterprise Data Management (“EDM”) in the sense of a single holistic process supporting all use cases is not a realistic goal in itself. Greater risks, data quality issues and increasing costs have compounded matters to the point where technology investments have to move to the utility that they can bring to the data management role. After all, financial data management is a means to an end and a foundational capability that has to support business, compliance and operations use cases alike.
We believe that 2018 will see a change in focus from compliance-led solutions, to those that prove their value by delivering relevant and timely data that empowers business users; addressing compliance requirements whilst enabling business-oriented data projects that improve efficiency and longevity for growth. Key to this will be the adoption of new cloud-based and NoSQL models as part of a wider shift of the overall application landscape towards a cloud- based and managed infrastructure that can support the growing data intensity of business and regulatory processes.
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