J.P. Morgan Invests in Mosaic For Analytics
J.P. Morgan has acquired a minority stake in Mosaic Smart Data, the fintech which provides real-time data for fixed income, currencies and commodities as advanced analytics and artificial intelligence are set to expand in capital markets.
In October last year Mosaic Smart Data announced that MSX, its real-time data analytics platform, had been deployed by J.P. Morgan across the bank’s entire global fixed income sales and trading division.
Matthew Hodgson, founder and chief executive of Mosaic Smart Data 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. He told Markets Media last October: “Mosaic Smart Data is like a financial GPS to see all client interactions and receive intelligence you can use in real-time to map the road ahead.”
The fintech 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.
Warren Rabin, head of macro sales in America at J.P. Morgan said in a statement: “We are investing in our salesforce, and technology is part of that investment. These investments in people and technology reinforce our commitment to putting clients first in every aspect of our business.”
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.
Consultancy McKinsey & Company and the World Federation of Exchanges said in survey this month that the use of advanced analytics and artificial intelligence is set for rapid growth in capital markets as the amount of available data increases. The report, Fintech decoded: Capturing the opportunity in capital markets infrastructure, is based on a survey of WFE membership.
“Respondents were largely positive about the potential of fintechs, and were unanimous in expecting enhanced productivity or new revenues from incorporating their technologies in their businesses,” added the report. “None saw fintechs as a threat, but instead viewed them as potential partners and enablers of growth. They acknowledged, though, that the extent of the impact is difficult to ascertain.”
WFE members ranked the importance of innovations in data analytics on the same level as trading technologies, at 14 choices each from the 46 survey participants. The McKinsey Global Institute has estimated that the global AI spending in 2016 was between $26bn and $39bn.
“Although large technology companies account for most of the spending, the financial services industry is a leading early investor in AI,” said the survey. “This stands to reason: information has always been a crucial resource for financial markets, and financial services firms have long been on the forefront of adapting new information technologies.”
The study gave examples of how advanced analytics can be used including predicting sources of market liquidity when customers place orders and refining the measurement of market impact and other transaction costs. In addition, investors want indicators of market sentiment, comprehensive industry analyses, and analytics of trade flows and best executions.
Approximately one quarter of capital market infrastructure fintechs are active in advanced analytics-based data.
“The availability of more data, and new and more efficient ways to mine and visualize it, results in more sophisticated products and greater demand,” added the study. “Among others, natural language processing and machine learning techniques are being applied to develop more precise smart beta products for asset managers, and unique data streams for the sellside.”
The pre-trade lifecycle can be cut from hours to seconds using existing bots.
For the sell side, remote working has proved possible, but not without its hurdles, Integral CRO writes.
The bank can access data science, artificial intelligence and machine learning for new products.
The platform provides a central limit order book for standardised interest rate derivatives.
New hubs will open across Europe and in North America in cooperation with central banks.