Why banks need real-time risk data at their fingertips

16 December 2011

By Dale Stevens,
head of Capital Markets,
SAS UK

The global financial crisis and ongoing market volatility in the eurozone are having profound implications for the capital markets. A bout of stringent regulation has swept through the industry in recent years and banks are under pressure to better understand their risk exposure. The global regulatory standard, Basel III, and the Dodd-Frank Act have placed serious demands on risk management officers worldwide. Risk management has never been so high on the agenda.

Current approaches to risk management in many large investment banks are inadequate. At present, the majority of banks are relying on risk information on a daily or, at best, intraday basis. The ability to monitor, aggregate and react to risk events on a real-time, firm-wide basis would give a bank a serious competitive advantage in terms of both profitability and readiness to deal with stress-testing and assumption-testing.

Current approach not fit for purpose

All banks should define their appetite for risk in a Risk Appetite Framework (RAF), which guides an organisation’s approach at every level to risk management. If a bank communicated its RAF to all employees and had a constant aggregated, firm-wide view of risk exposure, traders would have the ability to never execute trades outside of the bank’s predetermined risk appetite nor waste the capacity afforded them.

Traders themselves can already manage their own positions and portfolios on a near real-time basis. Unfortunately many banks are having difficulty in pulling together an aggregated view of risk exposure due to the siloed nature of departments working in different asset classes. The flurry of M&A activity following 2007 only exacerbated this problem, creating institutions which use a variety of different systems collecting incompatible data. A ‘one-firm, one-view’ approach is highly desirable yet something that most banks are
struggling to achieve.

Value-at-Risk (VaR) modelling is widely used as a means of determining whether an action fits within an organisation’s RAF. VaR models are widely used by banks for measuring the risk of losing a particular financial asset. Under normal conditions, VaR models allow financial institutions to adequately monitor and be alerted to the risk exposure of a single trading desk through to an entire institution. However, such models have shown to be unreliable in more volatile financial markets where it is becoming increasingly common to experience significant swings within a day’s trading.

VaR also does not cater well for ‘black swan’ type events, rare but extreme market convulsions, such as the bursting of the dotcom bubble or the collapse of the subprime housing market in the US. VaR models should therefore be viewed as only one string to the chief risk officer’s (CRO) bow.

VaR reports also do not adequately support the implementation of the RAF. It will come as no surprise that RAFs are most effectively implemented on an enterprise-wide basis at banks where there is strong communication between the senior management team, business line managers and CROs. Yet, even at institutions where this is occurring, RAFs are often not being executed at optimal levels because traders receive VaR reports on only a daily or intraday basis. This creates a disconnect between the risk vision of the senior management team and what is actually happening at a trader level. Traders can under- or over-hedge because they do not have an up-to-minute picture of what is happening across their organisation.

Moving to real time

The ability to monitor, aggregate and react to risk information on a real-time basis is becoming an ever closer reality for investment banks as they look to improve their risk technology in 2012.

In particular, banks must seek solutions that can operate holistically - across assets, across traders and across departments and geographies. A bank can then get a true enterprise-wide view of its risk exposure, enabling it to rapidly identify risk events as they happen, analyse them against various risk models and then take appropriate risk-mitigating action where appropriate.

Benefits

The benefits of such a solution are numerous. Financial institutions using real-time risk solutions can: hedge far better against possible losses as traders would not step outside of the bank’s risk appetite; manage risk-taking better as traders would use all the risk capacity available; reduce counterparty risks by preparing for the impact of market shocks which affect their counterparties; and more efficiently allocate their capital.

A real-time risk solution can also help banks identify rogue traders. Many institutions currently employ an overnight reconciliation process. With such a process a lot of intraday exposures can be hidden, rectified, and covered to disguise potential fraudulent trading, or intra-day gaming. A real-time solution gives much greater trade-book visibility and fraudulent trades can be picked up much more quickly.

Stress testing is another area in which a real-time risk solution is greatly beneficial. Banks are currently known to spend days or even weeks undertaking stress testing to meet the European Banking Authority’s capital requirements, leading to an inaccurate picture of their liquidity. With a real-time risk solution, firms would have the potential to reduce the time it takes to run stress tests from days to just seconds, dramatically improving the stress test positioning of the bank. By receiving stress testing and assumption testing results almost instantaneously, heads of trading desks and risk managers can make informed judgements on the current and forecasted health of single or aggregated portfolios.

No longer a pipe dream

There are obstacles that stand in the way of a bank moving to real-time risk solutions. Banks running multiple systems must change the way their information is processed - different systems tend to use different securities identifiers. Thus disparate data must be first reconciled and then submitted to a centrally managed database. The data must also be continuously available and highly secure from
unauthorised access and tampering.

This may seem like a huge challenge to investment banks that grew so rapidly in previous decades as a result of mergers and acquisitions. Many are running numerous systems and databases, siloed from one another and supplied with hardware and software from different vendors.

However, recent developments in risk management technology have made real-time risk management no longer a pipe dream. Solutions are being developed that can present traders and risk managers with an aggregate view of events as they happen - enabling better trading decisions and the ability to respond faster, more accurately, and on a firm-wide basis. This new breed of solution can inform decisions on a single trade or position, through to assessing the risk exposure of an entire global firm.

Conclusion

When simply used as a reporting tool, intraday risk reports might be regarded as adequate. However, if a trader is required to act on that risk information, as is surely desirable, information must be provided almost instantaneously. A real-time risk management model would allow banks to undertake more and greater trading positions and traders to operate with more confidence. While most individual traders already manage their own portfolios on a real time basis, it is the top level of an organisation which requires a real time aggregated view of the overall risk exposure.

It is obvious that many banks require an upgrade technology to enable them to move to a real-time risk model. However, moving to real-time risk management does not have to require a complete IT overhaul. The best solutions can be easily set up within a matter of weeks. These solutions are unobtrusive and complement existing systems while also managing incomplete or conflicting data.

In a new era of risk management, a bank’s success might be defined by whether it embraces or rejects new technology. It is clear which sort of bank will come out on top.

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