Guest Contributer:John Avery, Partner, SunGard
Transparency, Efficiency and Networks (TEN) were three of the key themes for SunGard in 2010, and it’s no coincidence that this is the same year that the greatest set of reforms in generations became law in the US and will soon become law in other jurisdictions.
With this new regulatory regime comes a new era of “transparency” – transactions and aggregated risks, local and global will all be more visible than ever before, and all in the name of systemic risk oversight.
Systemic risk doesn’t end there though, the “network” of relationships between market participants and between derivatives and their underlying instruments are likely to become critical inputs into systemic risk monitoring efforts, especially since these were two of the most purported catalysts for the most recent crisis.
A key question over the next 3-5 years will be how “efficiently” the industry will be able to support new data reporting requirements, with all of the data definition, reconciliation and distribution required to accurately comply with transparency mandates.
“Efficiency” challenges in data management are not unique to financial services, just look at three recent, but profound anecdotes in the mass-consumer market that provide some insight into the trends:
1) The creation & storage of data is growing faster than “Moore’s Law” which up until now has been a tried and true assumption about technology growth that has defined hardware & software development as we know it and has defined the technology industry business cycle for 40+ years
2) Google, Facebook, LinkedIn, Yahoo, Twitter, Amazon and others have resorted to a new approach to “Internet-scale” data management called BigData, supported by the NoSQL technology ecosystem, in order to deliver the services their users require – services that have exceeded the boundaries and capacity of existing relational database technology
3) Social “network” relationships, personally at Facebook, professionally at LinkedIn are voluminous and complex, and yet yield very rich insight into how the world works – once again, these “network” insights are supported by technology that evolved beyond current technology capabilities to solve problems at a scale heretofore reserved for the likes of intelligence agencies.
If we look ahead in financial services, the need for industry collaboration and evolution of technology to “efficiently” support the new “transparent” regulatory regime will be significant, but will also be important to support new opportunities for participants created by additional transparency. Here are three examples to pay close attention to:
1) The Office of Financial Research (OFR) – Risk management for not one, but for all systemically important market participants will require new tools and approaches not only at the systemic level, but also for each individual firm required to aggregate and report its own data. Consider examples like the transactional, counterparty and derivatives underlying relationships we mentioned earlier and even the recent analysis of the flash crash – these may very well become standard analyses for monitoring systemic risk going forward.
2) OTC Derivatives – Data is the critical ingredient in making the newly regulated OTC Derivatives markets “transparent” across execution, clearing and settlement, as well as being critical for managing significant economic impacts to collateral, margining, capital allocation and balance sheet utilization. Competitively, the firms who manage their data more “efficiently” will not only improve their bottom line – they’ll also use this data as top line competitive advantage, as inputs into their margin pricing for the derivatives services they offer their clients.
3) Pre-Trade Analytics – We can’t forget that the front office drives growth in the markets and that the move to “transparency” will create new trading & arbitrage opportunities, more dependent on data than ever before. The data analysis and decision making once reserved for the hedge fund & proprietary trading elite will be augmented by the past 10 years of research & development into semantic data technology. Assumptions on who creates value in the front office and where the line is drawn between algorithmic man and machine will be disrupted as the technology becomes accessible to a broader range of front office participants who will be more equipped to capture and analyze the “network” of semantic relationships and meaning in the markets.
So, even though the devil really is in the data, it’s an exciting time for those of us in financial services and technology as we move forward in our quest for data “transparency” & “efficiency” across the “network” of global financial markets.