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Mosaic Extends Real-Time Analytics Into Swaps

Mosaic Extends Real-Time Analytics Into Swaps

Mosaic Smart Data, the fintech which provides data for fixed income, currencies and commodities, has launched the first real-time analytics for swaps as banks increasingly need to analyse transactions at a granular level to win market share.

The new swaps analytics service allows banks to combine their electronic and voice-traded swaps transaction data into a single view on MSX, Mosaic’s real-time data analytics platform.

Matthew Hodgson, Mosaic Smart Data

He launched the company after finding it impossible to get a consolidated view of data on all trades with one client across all products in his previous roles at Deutsche Bank and Solomon Brothers. Mosaic now provides real-time analytics for swaps denominated in US dollar, sterling, euro, and Scandinavian currencies, which make up the majority of the $2.1 trillion a day interest rate swaps market, the largest derivatives market.

“Existing swap analytics are based on historical transaction records,” Hodgson added. “Traders need real-time performance and risk analytics to control their hedging and pricing, especially in an uncertain market environment.”

Mosaic uses technologies such as predictive analytics and artificial intelligence so banks can find value in the trade data they generate as the information is presented visually and using natural language. Through understanding past client behaviour, banks can improve service, and profitability by anticipating their future needs. Buy-side firms have corresponding needs and through analysing their interaction with brokers and clients, they will be able to improve service and profitability.

The ‘3 Cs’

Morgan Stanley and consultancy Oliver Wyman said in a report this year that winning market share will be key to individual banks’ return on equity outperformance.

“For the institutional pool, new technology and increasing transparency drive value to the largest players and technology-driven specialists,” said the report.

The study continued that structural changes and technology are pressuring the traditional value drivers for sellside which it called the ‘3 Cs’ - connectivity, content or capital - and threatening between $20bn and $40bn in revenues. As a result, banks need to develop active solutions to address unmet client needs through combining the ‘3 Cs’ through the integration of previously separate activities, underpinned by analytics.

“Such offerings are geared to avoiding the commoditization of individual activities and enhancing client retention,” said the report. “Active solutions currently drive less than 15% of revenues, but significant new revenue opportunities can be unlocked as wholesale banking learns from Big Tech and expands offerings to meet client needs previously not typically addressed by banks.”

Examples of these active solutions include best execution agency trading models that allow the complete insourcing of buy-side desks for foreign exchange and fixed income; and offering proprietary tools such as risk analytics engines.

Hodgson continued that banks can increase market share and profitability through using analytics to present clients with inventory they will want to see.

“Micro-segmentation is a big focus,” he said. “Banks need to unlock assets in an atomised way for clients through analysing every transaction.”

JP Morgan

Mosaic said in a statement that one of the world’s largest banks is already using the MSX swap analytics.

JP Morgan acquired a minority stake in Mosaic Smart Data this year. Last year Mosaic Smart Data announced that MSX had been deployed across JP Morgan’s entire global fixed income sales and trading division.

Warren Rabin, head of macro sales in America at JP Morgan said in a statement at the time: “Mosaic will use the investment to continue expanding the range of asset classes the platform supports, expand its development  and engineering staff to meet the demand in its pipeline and expand globally in the US and Asia.”

Mosaic can analyse data across fixed income, currencies and commodities in real-time and Hodgson noted that the same data can also be used for compliance, surveillance and risk reporting.

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