Commodity trading risk management and Energy trading risk management

1. #CTRM/#ETRM #GAP
Feb 23, 2015
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#"Commodity #risk #management" is emerging
as a critical differentiators of business performance. Many leading companies have established
"Commodity #Trading" and #Risk Management (#CTRM /ETRM) ‘functions’ which are
delivering significant performance and control improvements.#CXO's need to know where and
how they can make or lose money, which requires access to a wider variety of data types and
sources that can be translated into ready-to-use information. Volatility needs to be actively
managed because the uncertainty and variability it feeds directly into a company’s
financial performance attracts the attention of external commentators. It impacts cash flows
and margin and influences share price and market reputation. We know that trading and risk
management organizations are inherently both data intensive and highly data driven. As such,
there is a great reliance on accessing this information in a timely manner, as well as
implementing strong IT disciplines, governance and processes to support management decision
making. Managing risk in trading the #energy portfolio, for example, may rest on the ability to
access and convert data from upstream and downstream, on-demand, to improve the value of the
total group portfolio. This capability puts sophisticated demands on technology and supporting
staff to collect, collate, model, sort and aggregate vast amounts of data. Increasing calls for such
input requires a highly responsive operation in which accuracy and traceability are key. Timely,
accurate and relevant data, analyzed and presented as user information for front, middle and back
office staff, is critical for a high performing #CTRM/#ETRM function. Underpinning the
delivery of this critical user information is the need for a robust data and information architecture
which sets the framework to determine the systems configuration required to deliver the
architecture. In our experience, many #CTRM/ETRM functions fail to adequately define the

2. data/ information architecture and this leads to sub-optimal decisions on the use of supporting
systems.
A number of common myth and misunderstanding undermine the success of #CTRM/ETRM
system implementation and it's overall impact on business and the subsequent #Return on
investment (#ROI).

3. Missing Blocks of the E/CTRM ecosystem :

4. Conclusion :While the #ETRM/#CTRM is good for capturing the trading lifecycle from
Pre-deal analysis to Settlement and Invoicing but not all E/CTRM can efficient to
handle the market data/exchange data on it's own product architecture and also
lacks an internal expertise on #Bigdata handling and good #Visualization and
self-service #analytics which normally is best to integrate with a third party
application though it is an additional cost but worth the investment in the best of the interest of
the
business. Besides, #Fowardcurve building methodology is not transparent enough to
to go back and check exactly the formula used for the calculations which is a

5. mandatory requirement under the various data compliance Act and audit
compliance procedure.