The COVID-19 pandemic, the Ukraine war, and the rapid shift to renewable energy commodities is driving firms in the commodities space to rethink their approach to making trading decisions, forcing them to adapt in almost real time.

How advanced analytics addresses key challenges in commodity trading

The COVID-19 pandemic, the Ukraine war, and the rapid shift to renewable energy commodities is driving firms in the commodities space to rethink their approach to making trading decisions, forcing them to adapt in almost real time.

Identifying and collecting appropriate sources of data and information is a critical first step in developing insights and actionable information necessary to succeed in these challenging and constantly evolving markets. Gone are the days when businesses could make decisions based on news reports. Market forces demand businesses to capture real-time measurements around movement, storage, supply and demand of commodities. This is where advanced analytics for commodities come into play.

Besides daily operations, every stage of the trade lifecycle produces crucial data that must be captured to gain a more complete picture. But collecting data alone is not enough. These massive streams of data need to be filtered via advanced analytics to operate profitably. It’s essential to incorporate advanced data analysis — data must be integrated with workflows and analyzed in several different ways to extract actionable insights.

Common use cases for commodity businesses

Let’s look at some of the most common use cases commodity businesses encounter in their day-to-day operations –

  • Determining parameters of a planned trade and devising an execution strategy to minimize the cost of transacting with an acceptable level of risk
  • Ascertaining market value of trades executed at any given period requires aggregating and evaluating significant amounts of data and in-depth analyses
  • Ensuring each trade is validated accurately given its impact on the P&L and balance sheet.
  • Offsetting risk by employing hedge accounting strategies to reduce volatility
  • Tracking and quantifying risk expected within portfolios by comparing potential market scenarios from multiple simulation methods to assess impact
  • Nearly all commodity businesses work extensively with third party vendors making it necessary to assess their ability to meet contractual obligations

The collection of data to execute each of these activities, is daunting. Compounding the challenge is data trapped in multiple, siloed systems or spreadsheets. In such scenarios, collecting data itself is cumbersome – it could be days if it’s a large enterprise. Chances are, by the time they collect all data and complete the analyses, the markets have already moved.

The need for a better approach

Given the current market volatility, any process that creates latency in the businesses information flow, such as manual data compilation, complex reconciliations or reports that require hours or days to run, can and will invariably, result in lower profits, missed opportunities and increased risks. It is nearly impossible to extract insights on time without an advanced analytics solution.

Cloud driven advanced commodity analytics is the answer

To put things in perspective, let’s understand how cloud driven, advanced commodity analytics solutions help in the use cases outlined earlier –

  • Pre-trade analyses

    Be it to evaluate cost of products, logistics routes, processing or customs and finance, advanced analytical solutions built for commodity markets can help examine all possible options of fulfilling a sale offer and further evaluate most traded scenarios while optimizing equipment utilization for cargo movement.

  • Accurate position and mark-to-market

    It’s wholly possible to turn multiday manual reconciliation process into a 30-second task thereby providing a single point of truth on exposure. Some solutions come with embedded predictive algorithms that help provide real-time visibility into inventory, position, and exposure that lets users take advantage of opportunities and mitigate risks without delay.

  • Reconciliation

    Imagine being able to collect, blend, and analyze commodity data from disparate systems automatically. By employing sophisticated analytical tools, users can execute complex grouping, matching and mathematical calculations to reconcile reports across all functions, including accounting, trades, stocks, commissions and more – in minutes and not days!

  • Hedge accounting

    Key stakeholders in accounting and finance and risk office stand to gain full visibility into their exposure in real-time with solutions that can automate the whole process of hedge accounting which is crucial for hedging risks. Eka for instance provides a Hedge Accounting application that supports IFRS 9 and US GAAP compliance requirements and helps businesses efficiently execute hedge accounting strategies with methods of hedge allocation, hedge designation, prospective and retrospective effectiveness tests.

  • Calculating Value at Risk

    Analyzing risk to assess its maximum impact on trade portfolios involves simulating different market scenarios using several complex calculations – the most popular being Monte Carlo Method. When you leverage cloud driven analytical tools, the entire process gets automated – from pulling data from multiple sources to arriving at crucial insights. Users can create flexible VaR risk portfolios and multiple market scenarios to predict the potential impact of price shocks and ‘what-if’ trades. The process can be automated to run at set times or intraday (on demand) as needed – something you can’t accomplish with spreadsheets.

  • Credit risk

    Identifying and analyzing credit risk requires a structured approach. To accomplish this in a manner that is practical and efficient, cloud driven solutions can conduct advanced data analysis by pulling in data automatically from physical trades, supply chain, derivatives or any other source with data that contributes to analyzing credit exposure. Having data and insights at your fingertips, makes it easier to monitor and mitigate counterparty credit exposure that allows traders/risk managers to make more informed decisions.

These use cases form a gist of operations that require analyses for businesses to stay ahead in the market. With improved decision-making via real time scenario and advanced commodity analytics capabilities, businesses stand to gain market insights necessary to excel in an increasingly complex marketplace. Barring a few forward-looking companies, most simply rely on spreadsheets that just compounds the challenge.

Conclusion

It has taken some time for participants in commodity markets to fully embrace the benefits that new age technology has to offer. Though the recent market scenario is finally pushing businesses to employ some, it’s becoming increasingly clear that those who do adapt faster and leverage sophisticated and advanced analytics tools, will dominate the market in the coming years.

To understand more about how analytics can aid in navigating complex markets, download this free ebook on ‘Navigating volatile markets with speed and intelligence’ or get in touch with Eka experts here.

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