In recent years, central counterparties (CCPs) have had the challenge of adapting to a diverse range of regulations, which have forced many to reassess their risk management and valuation activities.
In recent years, central counterparties (CCPs) have had the challenge of adapting to a diverse range of regulations, which have forced many to reassess their risk management and valuation activities. The regulations have had a visible impact on the day-to-day operations of CCPs, by significantly increasing trading volumes. When combined with an increased need for granularity in risk assessment, this has placed huge strain on existing technology systems and the way each CCP manages their analysis and risk procedures. For CCPs to survive and thrive in the new data intensive and highly regulated landscape of clearing and settlements, they are focusing on finding new analytical solutions.
Although the US Dodd-Frank Act, as implemented by the Commodity Futures Trading Commission (CFTC), has been the main driver of the increased workload for CCPs, other regulations have added to the burden, such as the European Market Infrastructure Regulation (EMIR), customer gross margin rules and associated Legal Segregation with Operational Commingling (LSOC) chapter. By changing the ways that CCPs are required to analyse risk, for example, by dictating that risk be measured against individual customer accounts, rather than at a clearing member level, these regulations have greatly increased the volume and granularity of the analysis CCPs need to perform.
To deal with these ongoing changes, while maintaining their competitiveness, CCPs can choose between two tactics: investment in analysis staff or investment in analysis technology. With regulations set to impact more and more on CCPs, making the right investment choice will pay dividends in the future. Should CCPs efficiently manage the changes, there is an opportunity to generate more revenue and expand into other regions, attracting more clients which need real-time swaps clearing, risk management and reporting as part of their compliance strategies.
What’s the risk?
As CCPs contend with the fast pace of the markets, end-of-day or intra-day risk evaluation processes are no longer proving adequate. A change in any of the number of data points that make up the risk profile of a portfolio needs to be assessed and acted on as quickly as possible, to prevent fluctuations impacting negatively on their positions. Portfolio risk is typically calculated by using mark to mark (MtM) valuations to ensure market values match margin call requirements. This method demands real-time analysis of millions of trades and market data points across different source systems—something which limits clearing institutions operating under IT infrastructures capable of only analysing one source stream at a time and generating batch-oriented outputs. Legacy OLAP and SQL-based relational database models are not an option for a competitive CCP any longer because of the speed of analysis and complexity of indicators now required for accurate and compliant risk monitoring.
Technically, that’s not okay
Batch-orientated streams fulfilled their role when trading processes were slower and less efficient. A half hour batch process approach worked well to provide a snapshot of market positions, particularly as the market was relatively unlikely to shift too far in that time. With the advantages that improved communications networks and trading technologies have given the financial industry, however, legacy database models have been left floundering. With the granularity of risk analysis increasing and response times lowering, risk monitoring has become a complicated and time-intensive exercise for relational systems. This has already led CCPs and financial organisations to increase the size of their risk teams to keep their analytical performance at acceptable levels, which has engendered a significant increase in staff costs.
A new wave of analytics
An in-memory analytics platform, such as the ActivePivot system, has the potential to solve the dual challenge of risk management and legacy technology. This type of data analytics solution stores and calculates data in a centralised location in a computer’s memory, avoiding the system lag that can be incurred when data is fetched or sorted prior to calculation. Through the move to a centralised real-time analytics engine, risk analysts can better manage the organisation’s risk exposure and react to market changes effectively. This is because they are able to slice and dice risk aggregations across all asset classes in a holistic view—accelerating some of the manual tasks often undertaken by a risk management team. This has a direct impact on productivity, as analysts can use the system more intuitively, analysing data as the markets move, rather than working with pre-aggregated views or pre-canned reports. It also means that fewer analysts are needed as the extra calculation work is done by computers.
Doing things differently
As regulations continue to bite, and the derivatives markets continue to fluctuate, finding a scalable, cost-efficient solution for CCPs to manage risk is key to their future business prospects. Real-time portfolio risk calculations not only provide a solution to internal resourcing and regulatory challenges, they introduce improved risk assessment capabilities so that CCPs can offer a broader range of services to their existing members and potential clients. By investing in the right kind of technology to optimise risk processes and ensure analysts have access to timely and holistic views of risk exposure; CCPs can redirect their attention to providing the best possible service in an extremely competitive marketplace.
