Lacima Analytics implemented to risk manage a portfolio of derivative and physical refinery assets in Australia
The Project
The client has successfully implemented Lacima Analytics to undertake risk management of their portfolio of financial contracts and physical assets in Australia. Lacima was selected primarily because of its multi-commodity, multi-currency capabilities as well as the ability to analyse the risk position of sub-portfolios delivering management the analysis it needs to make more informed and confident decisions.
The Client
The client is one of Australia’s leading transport fuel suppliers. The principal activities are purchase, refining, distribution and marketing of petroleum products and the operation of convenience stores throughout Australia. It operates an oil refinery which produces petrol, diesel and jet fuel along with small amounts of fuel oil and specialty products, liquid petroleum gas (LPG) and other gasses. It also buys refined products on the open market both overseas and locally and, along with the products they refine, markets these products across retail and commercial channels. These products are supplied to customers via a network of pipelines, terminals, depots and company-owned and contracted transport fleets.
The Solution
Lacima Analytics has been implemented for both value-at-risk and earnings-at-risk metrics. As part of the implementation, Lacima developed a large set of new models representing various petroleum refinery products. With these new models and the ability to capture and model contracts that represent both their physical positions and derivatives, the client is now better able to hedge their physical operations. In addition, the client is now benefiting from having a detailed view of the risk in their portfolio and sub-portfolios, with proper consideration of correlations between the various market prices.
The Outcome
Lacima Analytics was able to model multiple commodities and currencies including cross-commodity correlations and structural relationships (such as crack spreads) between prices. The solution allowed the client to analyse the risk position of sub-portfolios; for example, based on entities within the parent company, or other user defined attributes.
This depth of analysis is enabling the client to make more informed and profitable decisions.
