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Real Time Risk Management at the Touch of a Button - the challenge of managing 'big data'

Real Time Risk Management at the Touch of a Button - the challenge of managing 'big data'

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New regulation, more frequent risk scenarios, faster trade flows and higher volumes are accelerating data velocities. Current risk systems need new architectures to scale.

Systems that have previously been able to deliver only in hours and days must now capture, aggregate and report accurate accounts of risk positions in minutes directly to regulators. Risk managers and traders often require reports in seconds.

IRS and CDS volumes will surge as they transition to the electronic market. This could be the perfect storm for firms without a robust, real time data management strategy.

Managing 'big data' has become the central challenge for risk and technology managers.

Technology is in the spotlight as failures to meet reporting requirements are met with large fines directly hitting the bottom line. Either timeliness is impossible or only achievable at vast expense. Some banks can't aggregate risk across different asset classes, while others are already under the gun from regulators to improve their risk management systems.

As a result many investment banking systems today are ill equipped to cope with the demands of a more regulated, high frequency market.

Symptoms of systems that may be at risk include.

  • System outages during peak trading windows
  • Regional DB replication times exceeding minutes when volume increase.
  • Declining performance of end of day feed extractions.
  • Slower report generation times and UI response times as data volumes increase.
  • Missed SLA's for downstream feeds both internal and external.

 Business data models and aggregation schemas that do not take into account a robust data-error-aggregation strategy e.g. (a trade is unable to be valued and represented correctly in an aggregate view) result in increased:

  • Operational Risk (wrong risk displayed to trading),
  • Regulatory Risk (wrong risk reported to regulators)
  • Reputational Risk (wrong risk/value reported to external clients).

Robust, volume insensitive data systems are rare in investment banking and the expertise to support them. Few have experience of dealing with data volumes exceeding 50 gigabytes and beyond. Aggregation technologies such as OLAP fall into a grey area within IT organizational structures typically leading to ownership within a development team with little experience of best practice and pitfalls to avoid.

One firm that has an answer to this problem is IMGROUP.

Their Risk Insight solution for the Enterprise "big data platform" will not only leverage best practice experience of handling "big data", but also result in a lower cost of ownership by standardizing processes and simplifying the framework around how the data is interacted with. By leveraging their unique QA framework surrounding the platform, their clients will see shorter release cycles and improved technical governance to reduce lights on and enhancement costs.

While Enterprise Risk Management remains a long term goal, IM Group clients are upgrading systems one line of business at a time, mainly in FX, Equities and Fixed Income. Buy side firms too can benefit from IM Group's technology and manage their portfolios in real time, literally at the touch of the button.

Due to strong demand IM Group are opening an office in New York to support their U.S. market. Real time risk management is finally here, literally at the touch of a button.