Quantifi Inc.

05/08/2024 | News release | Distributed by Public on 05/08/2024 17:05

Supplementing your CTRM with advanced counterparty risk, market risk & XVA

Supplementing your CTRM with advanced counterparty risk, market risk & XVA

Quantifi's CCRMS addresses the lack of specialised risk analytics in most CTRM solutions, with a growing list of clients across softs, metals and energy markets.
5 Aug, 2024

This article first appeared on Commodity Technology Advisory's CTRMCenterâ„¢ and is written by Dr. Gary M. Vasey, Founder of Commodity Technology Advisory.

Quantifi has a 22-year history providing risk, analytics, and trading solutions to capital markets. Around 12-years ago, it extended that offering into commodity markets and has since experienced strong growth in that space - both in softs and metals, for its counterparty credit and market risk solutions. Its latest customer is a leading market maker in energy, that trades derivatives in oil, gas, power, emissions and metals, Avadhut Naik, Head of Solutions, told me. "With the client's business growing and its operations expanding, it wanted to incorporate more sophisticated methods for pricing counterparty risk (CVA) on commodity derivatives they make markets in and selected the solution as typical E/CTRMs do not provide the functionality required around CVAs."

Supplementing you CTRM

Another area where Quantifi is seeing traction in commodities is in supplementing CTRMs with 'first-class risk management', he told me. "Quantifi has no plans to get into the trading side as our sole focus is on risk management," Avadhut said. "Our Counterparty credit and market risk solution is a first-class risk solution that companies can use to augment or supplement their CTRM(s), especially if they want to consolidate or aggregate risk into one solution across the business." He pointed to the lack of true risk analytics specialization in most CTRM solutions and the many current trends in the industry that mean better risk management is becoming a key criterion for success. Currently, it has several customers in energy and commodities but sees lots of interest in its solutions. This includes some banks who use the solutions across multiple asset classes including commodities.

Better risk managment: counterparty risk, market risk & XVA

Avadhut sees its origins in capital markets as a differentiator. "Risk has been a priority in those markets for a long time already and there are strong regulations around how to manage risk there as well," he said. "We can bring that experience to bear for commodity firms." He also suggests that Quantifi's long history in risk means that it has acquired significant expertise in the area. For commodities, its Commodity Counterparty Credit Risk Management System (CCRMS) provides "a consolidated, real-time view of exposures and risk globally across the enterprise," he said. "All participants involved in the credit decision making process can use the solution to make optimum credit decisions while managing the associated risk, automate complex manual tasks and eliminate redundant processes, with a solution that can be easily configured". Quantifi has subsequently expanded its offering to support market risk. "We now provide an integrated solution for counterparty risk, market risk and XVA for softs, metals and energy markets."

Avadhut also mentioned that as well as the strength of its analytics, he believes that Quantifi excels in data management by streamlining processes and allowing clients to focus on strategic decisions rather than data quality issues. "This is achieved through centralized data integration, automated data validation, and real-time updates, ensuring accurate and up-to-date information for dynamic decision-making," he said. He also thinks that clients are impressed with the highly configurable reporting framework. "This provides a consolidated view of global risk exposure with real-time reporting using high-performance in-memory hypercube technology, offering full transparency through interactive drill-down, slicing, and aggregation across all data."

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