Harnessing Machine Learning in Trading & Risk Data Management


The benefits of machine learning and new technologies for energy trading risk management are gathering a lot of attention. Our customers are interested in access to Python, MATLAB, and R.

For Wendi Orlando, Enverus VP of Trading & Risk product management, these are the top priorities for data management:

  • Ensuring data quality
  • Ensuring data comprehensiveness
  • Delivering accurate and timely data
  • Holding data vendors accountable

Ben Golden, Director of Trading & Risk Managed Services, says clients often come to Enverus asking for more access to all the data the company has to offer. These clients benefit from the Advanced Desktop Plugin, which uses Python to access this data, run internal models, and then also publish the data back into MarketView for visualization and analysis.

The Enverus team constantly monitors many information flows for our clients, from market data to curves. From this perspective, we see a spectrum of what customers are looking to accomplish with our data.

Clients want to feed Enverus data into their ETRMs, into their daily end-of-day processes. Enverus data monitoring and dashboards allow customers to see what data has arrived, to see where the team is awaiting prices, and see what data has made its way downstream to the ETRM system.

Enverus also has developed a proprietary data hub that allows customers to take the ingestion of data into their own hands.

“A lot of times clients just want to get things done. They want to be self-servicing in that nature,” according to Golden. “Our proprietary data hub allows them, as an end user, to upload data into MarketView—it can be Excel based—and imports data right into the system. It puts the power right into their hands.”



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