Mosaic Smart Data Snapshot
Mosaic Smart Data has the ambitious mission of empowering financial market professionals with the best data models to answer the questions they need to ask and provide those answers in real-time and in a visual language they can understand at a glance.
Effective use of data is fast becoming the most important competitive advantage for financial institutions across the capital markets. Financial institutions now spend over USD 30.5 billion a year on data analytics and market data. However, without the right treatment of the data and real-time analytics, they can’t take full advantage of this spend.
Typically, Institutions can’t even answer some fairly fundamental questions about their business, for example: What can we do to improve the service we deliver to clients? How can we make our clients more informed by providing relevant information to them? Who are our most profitable clients? What could we do to attract more business from our clients?
The reason is that they did not have access to the data analytics to provide this information, they require a single view over all the business that they are transacting to provide those answers. Mosaic Smart Data solves this need, helping firms extract maximum value for their data.
Mosaic Smart Data’s platform (MSX) is delivered into the financial institutions in three stages:
Aggregation & normalisation – the foundation of any successful data analytics program. This involves bringing all the institution’s e-trading and voice data together and structuring it into a common processing language as well as plugging any gaps with external market data feeds.
Applying advanced analytics – Mosaic Smart Data’s real-time analytics models are built specifically for the challenges of the capital markets. We help banks understand how to better respond to their clients’ needs and help sales teams become proactive through our predictive ‘reasons to call’ function.
A visually striking display – Mosaic Smart Data is building a product for the financial markets which is as intuitively designed as the iPhone. Its modular dashboard is designed to allow users to ask and answer any question they have in just a few seconds.
The story so far...
In late 2017, Mosaic Smart Data graduated from J.P. Morgan’s prestigious In-Residence programme and announced a major deal to roll its platform out across the bank’s global FICC business, starting with analytics for bonds.
In March 2018, J.P. Morgan invested in Mosaic Smart Data. Warren Rabin, Head of Macro Sales in America for J.P. Morgan, also joined the board.
Mosaic Smart Data became the first fintech firm ever to partner with the European Space Agency (ESA) on an innovative project to explore the potential for some of the ESA’s machine learning models to be used in the financial markets for functions such as market surveillance using advanced outlier detection algorithms.
With substantial demand for Mosaic Smart Data’s technology from the world's largest sell-side and buy-side firms, the company needed to build out its senior leadership team quickly to scale the business globally. In the first half of 2018, it announced Jack Jeffery as chairman, Stephen Caplen as Chief Financial Officer and John Showell as Chief Operations Officer.
In July 2018, Mosaic Smart Data launched analytics for its second asset class, interest rate swaps.
Using cutting edge Natural Language Generation (NLG) technology, Mosaic Smart Data launched the industry’s first instant reports for capital markets analytics in December 2018. The NLG powered feature of MSX creates custom text reports of complex charts, providing users with explanation of their analytics to use with clients.
Mosaic Smart Data welcomed CommerzVentures and Octopus Ventures as investors in a USD 9 million funding round in April 2019. The round also included further funding from J.P. Morgan.
In June 2019, Professor Rama Cont, Professor of Mathematical Finance at Oxford University joined Mosaic Smart Data as Scientific Adviser.
Mosaic Smart Data is currently being used by two global banks. It is actively engaged with +20 other sell-side and buy-side firms. It expects to have eight institutions using the service by the end of 2019.
Effective use of data is fast becoming the most important competitive advantage for financial institutions across the capital markets. Financial institutions now spend over USD 30.5 billion a year on data analytics and market data. However, without the right treatment of the data and real-time analytics, they can’t take full advantage of this spend.
Typically, Institutions can’t even answer some fairly fundamental questions about their business, for example: What can we do to improve the service we deliver to clients? How can we make our clients more informed by providing relevant information to them? Who are our most profitable clients? What could we do to attract more business from our clients?
The reason is that they did not have access to the data analytics to provide this information, they require a single view over all the business that they are transacting to provide those answers. Mosaic Smart Data solves this need, helping firms extract maximum value for their data.
Mosaic Smart Data’s platform (MSX) is delivered into the financial institutions in three stages:
Aggregation & normalisation – the foundation of any successful data analytics program. This involves bringing all the institution’s e-trading and voice data together and structuring it into a common processing language as well as plugging any gaps with external market data feeds.
Applying advanced analytics – Mosaic Smart Data’s real-time analytics models are built specifically for the challenges of the capital markets. We help banks understand how to better respond to their clients’ needs and help sales teams become proactive through our predictive ‘reasons to call’ function.
A visually striking display – Mosaic Smart Data is building a product for the financial markets which is as intuitively designed as the iPhone. Its modular dashboard is designed to allow users to ask and answer any question they have in just a few seconds.
The story so far...
In late 2017, Mosaic Smart Data graduated from J.P. Morgan’s prestigious In-Residence programme and announced a major deal to roll its platform out across the bank’s global FICC business, starting with analytics for bonds.
In March 2018, J.P. Morgan invested in Mosaic Smart Data. Warren Rabin, Head of Macro Sales in America for J.P. Morgan, also joined the board.
Mosaic Smart Data became the first fintech firm ever to partner with the European Space Agency (ESA) on an innovative project to explore the potential for some of the ESA’s machine learning models to be used in the financial markets for functions such as market surveillance using advanced outlier detection algorithms.
With substantial demand for Mosaic Smart Data’s technology from the world's largest sell-side and buy-side firms, the company needed to build out its senior leadership team quickly to scale the business globally. In the first half of 2018, it announced Jack Jeffery as chairman, Stephen Caplen as Chief Financial Officer and John Showell as Chief Operations Officer.
In July 2018, Mosaic Smart Data launched analytics for its second asset class, interest rate swaps.
Using cutting edge Natural Language Generation (NLG) technology, Mosaic Smart Data launched the industry’s first instant reports for capital markets analytics in December 2018. The NLG powered feature of MSX creates custom text reports of complex charts, providing users with explanation of their analytics to use with clients.
Mosaic Smart Data welcomed CommerzVentures and Octopus Ventures as investors in a USD 9 million funding round in April 2019. The round also included further funding from J.P. Morgan.
In June 2019, Professor Rama Cont, Professor of Mathematical Finance at Oxford University joined Mosaic Smart Data as Scientific Adviser.
Mosaic Smart Data is currently being used by two global banks. It is actively engaged with +20 other sell-side and buy-side firms. It expects to have eight institutions using the service by the end of 2019.
