Mosaic Smart Data & Previse named in Europe’s 50 Hottest Fintechs

Last week, Fintech City unveiled the sixth annual list of Europe’s top fintech50 companies. The list is selected by a panel of internationally renowned figures across finance and technology from a long-list of 1,800 companies. We were very proud to see Mosaic Smart Data and Previse added to the list this year for the first time.

Drawn from both B2C fintechs and those aimed at the institutional market, the list includes a wide range of business models and technologies.

Mosaic Smart Data and Previse lead a strong contingent of data analytics and machine learning companies. Both companies have had huge success targeting these technologies at specific, previously unsolvable, business problems.

In the case of Mosaic, it is enabling institutions to, for the first time, see their fixed income, currencies and commodities business in real-time. It uses advanced analytics to enable sales teams to generate useable insights to boost their performance and improve client servicing. In the last twelve months, Mosaic announced its first client, secured funding and expanded its team.

Previse is using machine learning to enable large businesses to have their suppliers paid instantly. It has made it onto the list in just its second year of business after securing funding from the Scottish Government and welcoming senior business figures such as John Gildersleeve and David Tyler to its advisory board.

As well as analytics companies like Mosaic Smart Data and Previse, a big trend in the 2018 list are blockchain companies. The list includes businesses applying the technology to a range of fields, from wholesale payments settlement to digital identity and cybersecurity.

Data analytics and blockchain are moving beyond theory and are now actively transforming global finance. It is, therefore, no surprise that these technologies feature strongly in this list of the most exciting financial technology companies.

We are proud to be working with some of the companies in the vanguard of these changes, both in Europe and the United States.

Banks Are Prioritising Digital Transformation

Fintech has barely even got started if a new report from EY is to be believed. Less than 20% of banks believe they are doing enough as a business to invest in technology, according to EY’s Global Banking Outlook study. This, despite some substantial leaps forward in technological capability and significant investment.

To combat this, more than half of banks surveyed in the report expect budgets for technological investment to rise by 10% this year, and more than half of banks aspire to be digitally maturing or digital leaders by 2020. Banks appetite to invest and partner with fintech firms may in part explain why last year was a bumper year for fintech VC funding, with $1.8 billion raised by UK firms.

This new investment opens up major new growth opportunities for the already thriving financial technology market.

The impact of fintech is being felt in every part of finance, from retail banking to back-office compliance. But one of the key focuses for banks over the past few years has been using technology to try to deal with stringent compliance and regulation, which slows down, complicates and adds expense to transactions.

Solving this is one of the key promises of distributed ledger technology (DLT) which is being touted as a new way to create trust between institutions, lower compliance costs and create information sharing efficiencies. This year, we are likely to see the first examples of DLT moving from proof of concept into market operation.

Data analytics and machine learning are likely to be another hotspot of activity this year. Many banks have begun announcing project designs in all kinds of areas of the bank, from back-office automation to the use of machine learning to improve execution quality.

For example, JP Morgan is working with UK based data analytics company Mosaic Smart Data to unlock insights from its internal FICC data to improve client handling and FICC performance.

In trade finance, Previse is looking to end late payments for SME suppliers with its advanced machine learning and innovative finance model which creates opportunities for buyers, sellers and banks alike.

The last few years have seen an explosion in financial technology. However, emerging technologies begin to mature, and banks continue to strive to be more efficient and effective, it looks like the fintech surge is only just beginning.

 

J.P. Morgan deploys Mosaic Smart Data for fixed income data analytics

As a recent piece in the FT pointed out, traders are searching for ever more inventive data streams to try to make better predictions about their market or get an edge over the competition. Whether that be advanced social media analytics, algorithms to read the news or even using drones and satellite images to look at factories, banks, and hedge funds are investing significant amounts in collecting and analysing data.

But, banks know that there is a vast wealth of data created and stored within the institution created simply through the normal course of the trading day. This is free, and it is completely proprietary.

The problem is, data within the bank is distributed across desks, systems and messaging languages. Bringing that all into one, aggregated and standardised form so that the algorithms can work their magic and deliver valuable insights is a herculean task.

But that is exactly what Mosaic Smart Data has announced it is doing J.P. Morgan.

By using sophisticated historical, real-time and predictive analytics algorithms, the Mosaic’s platform will provide, in the first instance, J.P. Morgan’s rates, sales and trading business with advanced tools to accurately provide tailored client service. This innovative technology enables users to better visualise and anticipate market and client activity and thereby offer better service. It can also reduce the cost and complexity of compliance.

“Having a more holistic view of trading data will improve our service delivery for clients.” Said Troy Rohrbaugh, Global Head of Macro at J.P. Morgan. “The Mosaic platform integrates securely with our existing technology infrastructure, and enables our teams to quickly make better-informed decisions.”

Once these fundamentals of a data analytics platform are in place. Mosaic can roll out advanced machine learning and predictive analytics which will help sales teams to predict their clients’ behaviour, allowing them to better facilitate client needs and improve their performance.

“Data analytics and artificial intelligence are changing the face of investment banking.” Says Matthew Hodgson, CEO, and founder of Mosaic Smart Data. “Banks understand that the insights locked away in their transaction and market data are potentially some of their biggest competitive advantages. They already have the raw materials, but MSX® gives them the tools to aggregate and standardise that data and put it to work intelligently.”

Mosaic shortlisted for fintech company of the year by City AM

Congratulations to the Mosaic Smart Data team which has been named in this year’s top five fintech companies in the City AM awards.

The awards celebrate the best of The City in an aim to identify ‘the most bold, successful, and principled companies and individuals’ of the year. The fintech category recognises some of the most innovative British fintech successes, and celebrates London’s role as one of the world’s centres of fintech excellence.

Mosaic was shortlisted as one of the top five categories by City AM’s editorial staff who, announcing the shortlist in the daily paper, described it as “one of the best financial services tech innovations of recent times”.

With financial institutions facing a challenging period in FICC markets, Mosaic allows banks to see how their entire FICC business is performing in real time and help traders identify much-needed liquidity in FICC markets.

As the volume of data linked to trading activity and interactions with clients increases, the challenge to harness and analyse that data in real time becomes ever more critical. Mosaic Smart Data understands that the true value of data comes not only from the intrinsic individual data streams themselves, but also from the correlations and inferences that can be drawn from the aggregated data from each client.

Its cutting-edge technology addresses the challenges facing institutions trading in today’s FICC markets, including change management, productivity, efficiency, restructuring and the growing automation of trading processes.

The final winners of the City AM awards will be chosen by a panel of prestigious judges from the world of business, including Virgin Money boss Jayne-Anne Gadhia, WPP’s Sir Martin Sorrell and Sky News’ highly experienced City Editor Mark Kleinman.

We wish Mosaic the best of luck for the awards ceremony, which will be held on 9th November at Grange St Paul’s Hotel.

The rise and rise of artificial intelligence

Recent announcements from some of the largest banks show artificial intelligence (AI) working its way further into financial markets.

Credit Suisse has announced it is to deploy 150 new ‘robots’ over the course of the year, with an overall aim of cutting CHF 4.8 billion (GBP 3.7 billion).

UBS has unveiled a new AI system which uses machine learning to develop strategies for trading volatility on behalf of clients. The bank claims that this is the first ‘adaptive strategy’ product offered by an investment bank.

J.P. Morgan is developing a machine learning technology called LOXM which aims to improve execution quality in the bank’s European equities business. As the buy-side increasingly focuses on execution quality, this is driving ever greater adoption of algorithmic trading across asset classes. LOXM is programmed to learn from historical trading patterns and tweak its algorithmic strategies accordingly, using a technique J.P. Morgan calls ‘deep reinforcement learning’.

The ability to adapt and learn without human intervention allows LOXM to optimising the execution gains of algo trading.

Mosaic Smart Data is looking at how AI can improve trading across asset classes, taking on the challenge of providing machine learning capabilities to the FICC markets, which have far less standardised data and a greater portion of voice trading.

Mosaic provides both real time and predictive analytics insights for sell-side FICC traders, giving them a view of their market in a way that takes in far more data than a human being is able to comprehend. This augments the human trader’s capabilities and could lead to significant performance gains for sell-side FICC departments.

While initial uses of AI focused on process improvements, it is significant that the technology has reached a level where its insights are now helping to influence trading itself.

Although we are still some way from a fully automated robo-trader, this represents a significant increase in confidence in AI technology.

Mosaic Smart Data named Best Use of Data and Analytics Innovation at the 2017 FStech Awards

Data analytics technology specialist Mosaic Smart Data has won the Best Use of Data and Analytics award at the annual FStech Awards, held in London on Thursday 23rd March.

Regulatory changes and advances in technology are revolutionising fixed income, currencies and commodities (FICC) markets and driving the need for intelligent data analytics and reporting.

MSX delivers a next generation data analytics platform for FICC market participants. By delivering the insights and real-time intelligence they need to harness exponentially increasing data as well as meeting regulatory requirements, it enables trading and sales teams to significantly enhance their workflow productivity.

The platform standardises and aggregates multiple data sets to enhance audit trails and reporting, enabling banks to comply with mounting regulatory requirements.

Mosaic has fully integrated predictive analytics into MSX, enabling financial institutions to more accurately determine future market activity based on sophisticated algorithms and historical data.

After collecting the award, Matthew Hodgson, CEO and Founder of Mosaic Smart Data, said: “In today’s digital world, banks need to have a deep understanding of the business they are handling in real time. The data is there, but it needs to be standardised and have intelligent analytics applied to it. It is an incredibly intensive undertaking which requires both innovative technology and thorough insight into the bank’s business needs.”

Read more about this story at Mosaic Smart Data’s website here.

Big data overdrive hurting bank profits

With more and more data available, making sense of vast amounts of content efficiently can boost profits by at least five percent a year.

Sell-side banks operating in the FICC markets are producing more and more data, and it is widely acknowledged that there is tremendous minefield of value often hidden within this data that can be of great use to an institution’s trading, regulatory, audit and compliance functions.

But for many institutions, aggregating and gauging this data to make sense of key trends accurately remains a significant challenge. So far, it is proving to be timely, costly and hurting banks’ profits.

The 2016 global study released by Qlik and Wall Street Journal (WSJ) surveying financial service companies about the usage of data and analytics revealed 57% found data information too complex to process, analyse and disseminate in a timely fashion. Yet nearly 80% of respondents believed that leveraging insights from data could boost revenues by at least five per cent annually.

As Duncan Ash, a Senior Director of Global Financial Services at Qlik, says: “Analytics is still the most prevalent in head-office functions, and the people in the field that need it the most are getting it the least.” He added that “firms struggle with the volume and complexity of data, and with the basics of communications and data management.”

This potential rewards on offer has led to a rise of specialist technology vendors that scrutinise and standardise data and do the hard work for their clients. One such as example is Mosaic’s MSX platform, which aggregates multiple sources of transaction data into a singular resource. This enables banks to meet regulatory requirements by building a more comprehensive view of client’s trading activity while creating better audit trails for regulators.

Steven Hatzakis, a financial services industry consultant and a registered Commodity Trading Advisor, said in a column on Finance Magnates that as analytic tools have evolved, so have visual dashboards. “These include not just numbers but adding colors or other variables that indicate changes as reporting and related gauges become dynamic. This is a common trait seen within trading platforms in capital markets and it is used in order to make it easier for technical data to be comprehended quickly.”

As Diane Castelino of Mosaic Smart Data says, “The next and most advanced stage is breaking into the field of predictive analytics and machine learning, where the ability to predict future client trading behaviour based on historical patterns sets institutions streets ahead of their peers.

“In what has become a challenging trading environment for all, the real winners in the race to harness and utilise big data will be those institutions that partner with the technology specialists that deliver expertise and innovation on a cost effective, modular basis and educate staff to use the technology effectively.

Diane’s whitepaper on big data and going beyond the hype can be read here.

FICC: How To Profit From Necessity

Regulation is at the top of many bank agendas these days, with multimillion dollar compliance projects now commonplace. But as Matthew Hodgson, CEO of Chatsworth client Mosaic, and Andy Webb, Automated Trader’s founder, explain, banks have yet to seize the opportunity to leverage this existing regulatory investment to generate profitability and competitive edge in FICC.

The scale of recent bank compliance investment is vast. In 2013, JPMorgan added 4,000 personnel to its compliance team and spent USD1bn on controls. In 2014, UBS spent USD1bn on meeting regulatory requirements, while more recently Citigroup reported that it was recycling USD2bn of USD3.4bn cost savings into compliance spending. Goldman Sachs has also been active, with more than half its new headcount of 2800 in 2015 being in compliance. But how can banks turn this investment into a profitable business opportunity? Data analytics holds the key.

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