In the modern world, any corporate house has huge amounts of data stored in multiple systems pertaining to different domains. In a trading firm – be it an investment bank, an energy company trading in commodities or a hedge fund – there is significant data related to trading transactions, market data (prices, volatilities, correlation), exchange information, accounting and settlement data. Normally, this information is used for regulatory and compliance-related reporting, what we might call “defense,” in sports terminology. That same information can be used to gain a competitive advantage and make better decisions. It can bring enormous value to the company.
Data analytics has become more important than ever. Simply put, we as a society are being asked to share data, and a tremendous amount of data is being gathered. The key here is that a huge amount of data is being collected in various domains as business interactions move to technology platforms: computers, mobile devices and the internet of things.
We should consolidate the information, provide just-in-time information, analyze the information, provide visibility and even apply established knowledge-based rules to drive decisions. Hence, rather than make decisions on a limited amount of information or visibility, we provide enhanced analytical capability, the ability to drill down or roll up information, and apply expert-level rules to drive the right decisions. Thus, a humongous data store, expert level rules and an inference engine to fire those rules becomes the solution to make better decisions.
Dodd-Frank regulations, for example, have forced trading companies to collect data, analyze it, produce reports and submit them to the Commodity Futures Trading Commission. Companies can use that same data for better trading decisions. Based on analysis of trading, position and P&L information, data analytics can give visibility to cash flows/liabilities and inform better future trading decisions.
People voluntarily share information through social media platforms: their opinions, feedback, reviews and honest and open discussions. All that information is collected and available in public forums. Based on social media, data analytics can drive better product decisions, retail marketing themes and even logistical decisions about what to produce and what to send to stores for sale.
With the availability of tremendous amounts of data, we can formulate the right rules to analyze the data and make better decisions. Technology has made the data store and processing power cheaper; it is up to us to formulate the right rules to derive the intelligent decisions. This will revolutionize how we derive value out of the data already being collected. Thus, a system, in the not so distant future, can gather data from multiple sources, apply expert rules collected from a wide gamut of experts, play on the cutting edge of artificial intelligence and heuristic learning and then, represent the analyzed data in a meaningful way for better decision making. In short, a smart virtual expert is not very far away.
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Partha Chatterjee is a Principal within Capco Energy Solutions. As a solutions architect and expert technology strategist in energy and finance, he provides leadership in information technology, energy (upstream to trading/marketing and utilities) and finance.
His expertise encompasses energy and trading risk management (ETRM) systems, risk management and trading analytics, regulatory compliance, and governance. He compliments that with deep technical knowledge in enterprise architecture, web enablement, engineering applications and mathematical modeling.
The content and opinions posted on this blog and any corresponding comments are the personal opinions of the original authors, not those of Capco.