Mosaic Smart Data Adds Reporting Solution to MSX

by David Kimberley
  • The new solution uses machine learning to produce and analyze otherwise time-consuming reports.
Mosaic Smart Data Adds Reporting Solution to MSX
Finance Magnates

Mosaic Smart Data (Mosaic), a data analytics company, announced the launch of a new feature for its MSX platform this Thursday. The new feature allows users to generate text reports on their trading activity using machine learning - a technology whose arrival has been more hotly anticipated by the Davos Crowd than the Second Coming.

As you might expect from a data Analytics company, MSX is a data analytics suite that companies can use to boost productivity and strengthen their sales efforts. Most notably, JP Morgan adopted the solution in October of last year for use in its fixed-income division.

"This new feature allows users to instantly create the narrative around the data analytics," said Matthew Hodgson, CEO and founder of Mosaic Smart Data, "highlighting the key outliers or trends in the data which they need to pay attention to, enabling rapid understanding of the information."

Who Cares about Text Reports? Mosaic Smart Data Apparently

The new addition to the MSX solution may sound dull - who cares about text reports - but could be extremely useful to companies. Using a Machine Learning technique called natural language generation, MSX can automatically generate trading reports on any set of analytics available on the platform. That includes data from both voice and electronic trading.

Reports generated can highlight different trends and anomalies in transaction data - something that both traders and sales teams will find useful. So smart is the technology involved that it can analyze why those anomalies occurred and also report those results to the user.

Purely in terms of time, the new feature should prove extremely useful to firms. The reports it can generate would otherwise take a worthless, non-machine learning human several hours to produce.

“Imagine if the bank’s highest performing, most experienced quant could write all the reports it generates," continued Hodgson. "And now imagine those reports could be produced in seconds across the entire global bank 24 hours a day. The gains in efficiency, performance and business insight would have an almost immediate impact on the bottom line.”

Mosaic Smart Data (Mosaic), a data analytics company, announced the launch of a new feature for its MSX platform this Thursday. The new feature allows users to generate text reports on their trading activity using machine learning - a technology whose arrival has been more hotly anticipated by the Davos Crowd than the Second Coming.

As you might expect from a data Analytics company, MSX is a data analytics suite that companies can use to boost productivity and strengthen their sales efforts. Most notably, JP Morgan adopted the solution in October of last year for use in its fixed-income division.

"This new feature allows users to instantly create the narrative around the data analytics," said Matthew Hodgson, CEO and founder of Mosaic Smart Data, "highlighting the key outliers or trends in the data which they need to pay attention to, enabling rapid understanding of the information."

Who Cares about Text Reports? Mosaic Smart Data Apparently

The new addition to the MSX solution may sound dull - who cares about text reports - but could be extremely useful to companies. Using a Machine Learning technique called natural language generation, MSX can automatically generate trading reports on any set of analytics available on the platform. That includes data from both voice and electronic trading.

Reports generated can highlight different trends and anomalies in transaction data - something that both traders and sales teams will find useful. So smart is the technology involved that it can analyze why those anomalies occurred and also report those results to the user.

Purely in terms of time, the new feature should prove extremely useful to firms. The reports it can generate would otherwise take a worthless, non-machine learning human several hours to produce.

“Imagine if the bank’s highest performing, most experienced quant could write all the reports it generates," continued Hodgson. "And now imagine those reports could be produced in seconds across the entire global bank 24 hours a day. The gains in efficiency, performance and business insight would have an almost immediate impact on the bottom line.”

About the Author: David Kimberley
David Kimberley
  • 1226 Articles
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About the Author: David Kimberley
  • 1226 Articles
  • 19 Followers

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