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Vendors Find Synergies For Merger

With Torben Munch, CEO, Itiviti

torben-munchAs financial firms outsource more technology, there is pressure on service providers to compete.

Itiviti, backed by Nordic Capital Fund VII, announced its intention on 28 November to combine with Ullink to build a full service technology and infrastructure provider for global and regional financial institutions. The deal is likely to be closed within the first half of 2018 after it has gained anti-trust approvals. GlobalTrading spoke with Itiviti’s CEO, Torben Munch

What is the business logic behind the merger?

It is a merger of equals, with each firm providing complimentary areas of expertise and commercial penetration. Basically, Itiviti and Ullink are approaching the financial trading community from two different angles, but with the same underling objective. It is a partnership that should create a one-stop shop for global market participants, and which will build on a subset of clients who are already using Itiviti and Ullink products and services.

Describe Itiviti’s key activities and core strategy.

Itiviti has developed its business activities substantially during the past five years, moving from an emphasis on futures and options trading to cash equities, then to foreign exchange. Its client base has evolved, shifting from a fairly exclusive focus on proprietary traders and market makers within banks to offering DMA and DEA services to the wider financial trading industry. It is becoming an increasingly electronic trading world, especially in cash equities, derivatives, foreign exchange and commodities. We aim to capture that growth.

The trading space is like a race track for Fintech software, but not everyone needs a race car. Some clients are, of course, less latency sensitive and we will continue to facilitate their order routing and trade execution.

More recently, the firm has also invested in the technology and skills that provide its clients with more efficient FIX messaging systems and, most significantly, connectivity. We have been expanding our focus, and that growth will be augmented by the merger.

How does the merger with Ullink enhance your strategic objectives?

Ullink is preeminent in high touch and low touch order management systems and supplies the world leading NYFIX network that provides clients with hub-and-spoke connectivity. Ullink has 1500 clients, of whom about 800 are buy-side firms largely using the company’s connectivity services. Itiviti’s 360 clients are mostly banks and brokerages, so there is huge potential for expansion for the company’s trade execution technologies among asset managers and trading platforms. The merger will be defined by its complementary synergies rather than any business duplication or overlap.

Do you see a rising trend among buy- and/or sell-side firms for outsourcing technology and systems?

Definitely – and there are four main aspects of this trend: First, tier one and tier two financial companies recognise the flexibility of outsourcing software to third parties; second, more and more institutions want to consolidate disparate trading platforms, both by functional and asset class, into fewer platforms; third, after implementation of MiFID II there will be an increasing demand to match technology capability with regulatory requirements – so called, RegTech; and fourth, the trajectory towards greater trade automation is undiminished. Underlying these four forces that are driving the move to greater outsourcing are the expectations of cost-savings.

What are the toughest challenges when working to meet a client’s technology goals?

Legacy systems, typically developed in the 1990s, are often cumbersome, sometimes expensive to maintain and usually inflexible. Financial firms increasingly need systems that are more lightweight and nimble. However, it can be a difficult process to dismantle them and transition should be gradual to prevent damaging disruption to commercial operations.

Both Ullink and Itiviti have large, well-trained customer services staff to help ease the migration of legacy systems to more efficient processes. Introducing new systems not only requires engineering expertise, it is also means consulting skills and offering the capacity to tackle difficulties as they arise.

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Analysis : Fixed income analysis : Trax

Leveraging Trax’s vast market data set, the Trax Facts quarterly review provides a detailed analysis of activity across fixed income markets, including: Corporates, Agencies, Governments, Asset Backed Securities and Emerging Markets. Here we publish a summary of the Q3, 2017 review.

European FI market by total traded volume

The third quarter of 2017 saw the characteristic drop off in trading volumes for this period, however to a greater extent in 2017 than in previous years. While volume is not a proxy for liquidity, falling volumes indicate turnover of securities is typically lower in the third quarter of a year relative to the first half of the year (see Fig 1).

The average daily traded volume for fixed income instruments in Europe for the third quarter of 2017 fell to 90 billion, from 118 billion in Q2 and 128 billion in Q1, according to Trax data. That means Q3 volume fell 10% on a year ago, when trading volume for Q3 2016 hit 100 billion. The same pattern of decline can be found in trade count annually.

European FI market by trade count (Fig 2)

The 29% drop in average daily volume from Q1 in 2017 is proportionally greater than the fall in 2016, which saw a 12% drop in volume from Q1 to Q3 2016 and the fall was a little greater than the 22% decline experienced in 2015 over that period.

European FI market corporate activity

Corporate Investment Grade in Europe saw average daily volume fall by nearly 24% quarter-on-quarter.  That was on a par with volume for Q3 2016 at just over 5 billion ADV. High yield credit saw ADV in Q3 fall 16.5% against Q2 but only saw a 3% drop on last year’s Q3 ADV (see Fig 3).

Average Daily Volume (ADV) breakdown by category

Meanwhile European government and sovereign bond ADV declined by nearly 24% in Q3 against the previous quarter and were down 10% against Q3 last year (see Fig 4).

www.traxmarkets.com

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News : Derivatives : Bitcoin

BITCOIN COMES OF REGULATORY AGE

Exchange operator CME Group threw the gauntlet down and launched the first digital currency futures a week before expected. In the first session more than $80m in bitcoin futures changed hands on the world’s biggest exchange operator by market value.

The trading value gave it a slight edge on rival Cboe Global Markets as they vie to be the main hub for the nascent bitcoin futures market.

CME executives say its contract is aimed at institutional investors who have been calling for futures. The larger size of the CME contract means investors will have to pay five times more margin money to backstop their trades.

The Commodity Futures Trading Commission (CFTF), the main US markets regulator, only gave the green light to the two competitors to list bitcoin futures, which was seen as a significant step in allowing mainstream investors to buy and sell the highly volatile cryptocurrency.

The CME and Chicago rival Cboe had agreed to operate under a self-certified regime for their contracts while Cantor Exchange, run by Cantor Fitzgerald, opted to self-certify bitcoin binary options, the CFTC added.

The moves are seen as a watershed for Wall Street professionals – including institutional investors and high-speed traders – who have been keen to bet on cryptocurrencies and their wild swings, but were worried about doing so on mostly unregulated markets.

“Bitcoin, a virtual currency, is a commodity unlike any the commission has dealt with in the past,” CFTC Chairman Chris Giancarlo said in a statement. “We expect that the futures exchanges, through information sharing agreements, will be monitoring the trading activity on the relevant cash platforms. Futures exchanges under such rules are required to monitor for potential market manipulation and market dislocations like sudden drops and trading outages.”

The price of bitcoin has been on a roller coaster ride in recent weeks, surging to an all- time high above $11,000 for the first time, only to drop more than a fifth, and then rebound. Bitcoin was trading below $2,000 as recently as May 2017.

Introduced in the wake of the 2008 financial crisis, the currency was a way of avoiding governments and central banks. However, its meteoric rise and popularity has meant that banks, brokers and mainstream investors want to get in on the action but with regulatory oversight.

“The launch of the futures will actually make the market healthier,” Cboe President Chris Concannon said in a statement. “It will create pricing equilibrium in the market. Clients who are holding bitcoin now have no way to hedge their risk. These products allow them to hedge, and to take opposing views. More importantly, it brings a wave of regulatory oversight.”

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News : Fixed income : ING’s AI

ING’S AI IS SMARTER AT PRICING BONDS.

ING  has launched Katana, a new artificially intelligent (AI) bond trading tool which uses predictive analytics to help price trades for clients. The bank claims that its new web-based ‘AI trading assistant’ allows its sales-traders to assimilate relevant trade data more efficiently, leading to faster pricing and ultimately more liquidity. The interface provides an overall view of what a trader might need to know for the trade, including current position, impact of request and the relevant price history.

Santiago Braje, global head of credit trading, at ING said, “Using historical information and real-time information, it brings forward-looking predictions. The algorithms make predictions about what the winning price will be, which the user can utilise to price a trade.”

The platform was tested in controlled conditions at specific points in the day, measuring speed, accuracy and consistency of pricing. The results showed that Katana provides faster pricing decisions for 90% of trades and contributes to a reduction in trading cost of 25%, and was four times more frequently able to offer the best price to clients.

Leveraging technology is vital to help traders join the dots in traditionally over the counter (OTC) fixed income markets. Compared to the common equities markets, fixed income is significantly less liquid with far less frequent activity in any given security. As a result, a wide data set needs to be considered in any pricing decision. Initially ING chose the Emerging Markets desk in London to test out Katana.

Braje said, “In a way, we set ourselves the more difficult challenge because it is one of the more illiquid markets, and if we find it’s effective in illiquid markets, it’s a good indication that it will be effective in liquid markets.”

The London-based bank also reported that it is constantly learning which features are the most relevant and looks for factors that can influence pricing. The tool draws on a wide range of datasets, including five years of historical trades, which provides examples on trades won and lost.

Frank Derks, head of advanced analytics and artificial intelligence at ING Wholesale Banking said, “We try to feed as much data in as possible, find out which features are the most defining ones. We have been surprised at which data source was the most relevant. We don’t try to predict; we try to understand what the machine comes up with and integrate the algorithms further.”

ING stressed that the technology is an augmentation of current human capabilities. Users are able to follow through on or deviate from the information the tool provides, depending on what information they have at their disposal.

“We are combining AI with human intentions,” said Braje. “If we look at the algorithms by themselves, there is space for improvement, but they cannot match the humans in terms of accuracy. However, we do see that the human with AI performs better than the human without.”

Roll out across other fixed income asset classes is expected in 2018, with an end game of delivering pricing to buy-side clients. While Katana enhances the bank’s ability to provide competitive trades, the tool will also tailor the quotes depending upon the client, as the client is a factor assessed by the trading algorithm, so buy-side firms should not assume they will all see the same price for a trade.


News : Equities : Euronext takes over ISE

Euronext buys ISE for €137m

Euronext has acquired the Irish Stock Exchange (ISE) for €137m in an attempt to boost its exchange-traded fund (ETFs) business and take advantage of opportunities from the UK leaving the European Union.

Lee Hodgkinson, head of markets and global sales at Euronext, said in a statement, “We are bullish on ETFs and the drive to passive. The ISE has a strong franchise with issuers such as Pimco and WisdomTree and Euronext is strong on ETF trading so the combination of talent will be fantastic.”

The acquisition gives Euronext the home venue for Irish equities, but also a market for debt securities and the largest European centre for ETFs. Ireland will be Euronext’s sixth “core European country” alongside the main exchanges in France and the Benelux nations.

Deirdre Somers, chief executive of the ISE, described the exchange as a “200 year-old start up” although the firm was established in its current form when the ISE demerged from the London Stock Exchange in 1995.

“We are the number one fund listing venue globally with 5,242 investment funds securities and 227 ETFs,” Somers added. “Asset managers from over 50 countries use Ireland to administer 13,000 funds with more €4 trillion of assets.”

Brexit was also a factor, as Somers notes, Ireland will be the only common law jurisdiction that is English speaking in the EU after Brexit and so is uniquely placed to deliver Brexit solutions.

“Brexit has implications for London depending upon on the deal that is reached and we have optionality for the business with a commitment to the EU,” added Somers. “We could think about dual listings or other offerings to solve problems.”

After completion, ISE plans to migrate its technology to Optiq, Euronext’s new proprietary trading platform. Closing is expected in the first quarter of 2018 subject to regulatory approvals from the Euronext College of Regulators and the Central Bank of Ireland.

ISE is currently owned by five Irish financial institutions, J&E Davy, Goodbody Stockbrokers, Investec Capital & Investments, Cantor Fitzgerald and Campbell O’Connor that have all committed to sell their shares.

Euronext said in July that it had as much as €2bn to invest as it sought to diversify its revenue sources. The world’s biggest exchanges are still looking to consolidate, although Deutsche Boerse’s acquisition of London Stock Exchange Group failed earlier this year.


 

Harnessing Big Data To Transform Fixed Income Trading

chris-rice-q3-17

By Chris Rice, Senior Managing Director, Global Head of Trading, State Street Global Advisors

New data mining and architecting techniques are helping to bridge the transparency gaps that once challenged fixed income traders.

Best execution in fixed income markets has always been more challenging than in equity markets in which traders have a greater line of sight into securities trading at higher volumes across automated markets. By contrast, fixed income mostly trades over the counter and is characterised by fragmented price sources and less accessible data. However, advances in data accessibility and processing through machine learning and other artificial intelligence technologies are transforming fixed income traders’ ability to build a new generation of smart order routing platforms. These new dashboards are bridging many of the price discovery and pre-trading liquidity gaps that once challenged fixed income traders.

The advent of new fixed income trading platforms has created more information than ever before about transactions and counterparties. Fixed income market participants are increasingly trying to harness the power of these expanded data sources to gain greater insights into market liquidity and enhance trading decisions.

As a result of new infrastructure improvements, dealers now provide liquidity indications of interest (IOI) to the buy-side much more frequently throughout the trading day than before. Even just a few years ago there was often just one IOI in the morning. This provides buy-side traders with a far better and timelier snapshot of actual dealer liquidity.

This improved IOI data, combined with information from other bond pricing sources and platforms, as well as liquidity cost scores, furnishes enhanced insight and the potential to negotiate a better price. Buy-side firms are leveraging this information and in varying forms have been able to consolidate much of this data within their order management systems to make access easier for traders to digest and exploit. This data is also helping fixed income portfolio managers build more resilient strategies that take liquidity conditions into account at the design rather than the execution stage.

There have also been other more formalised initiatives to improve fixed income liquidity and market transparency. For instance, Project Neptune, a collaboration of large banks and buy-side firms, has created a powerful centralised source of information around available fixed income securities. While it is not a trading platform, it nevertheless helps solve some of the opacity and liquidity challenges in the broader industry context of lower inventory and poor information transparency.

The explosion in pre-trade and post-trade data will increase even further with the implementation of the European markets in financial instruments directive (MiFID) II in January 2018. Managers with the technology and expertise to mine and architect this new data into actionable insights will enjoy a competitive advantage.

At SSGA, we are creating the next generation of data processing and visualization techniques to improve our ability to harness new data sources and incorporate those insights into dynamic dashboards that help our traders and portfolio managers achieve better execution.

Better data visualization and dashboards
New data visualization tools have improved the collaboration between trading desks and portfolio managers. The ability to dynamically filter and interpret large data sets in differing visual formats has created an important feedback loop for trader and portfolio management teams aimed at constant process improvement. The dashboards enable more precise data customisation for targeted audiences (for example, traders versus portfolio managers versus group CIOs) and allow end users to detect anomalies in trading costs, volumes or counterparty activities.

During the past year, we have rolled out dynamic dashboards to traders that enable them to hone in on their trading activity over a given time period. Counterparties can be analysed by volumes traded or associated transaction costs. Traders can review the performance of counterparty over time or narrow down performance in certain markets or trading styles. As a predictive feature, this may flag counterparty strengths or weaknesses as a guide for future trading activity. This is particularly important information for those fixed income sectors where liquidity is scarce.

March of the machines
As advances in machine learning and other artificial intelligence (AI) technologies are applied more broadly to automating and refining pre- and post-trade fixed income data, we expect that both traders and portfolio managers will benefit. We are quickly moving to the state where we will be able to automatically capture datasets from across the entire lifecycle of fixed income trading activity – from cash flows to execution. This expanded universe of data (RFQs, liquidity, market data, execution data, qualitative commentary, historic cash flows, etc.) will help to incorporate trade execution directly into the portfolio management process and improve speed to market. We envisage a not-too-distant future in which our traders will routinely be using AI technology to improve pre-trade price discovery and optimize execution.

This iterative process of improving the volume, quality and representation of pre- and post-trade fixed income data has several important benefits for investors. Most immediately it helps fixed income traders augment the inherent price discovery challenges of trading fixed income securities in fragmented and less transparent venues, thus improving their ability to provide best execution. More importantly it provides a powerful advantage to fixed income portfolio managers by equipping them with far more reliable liquidity data across fixed income sectors as they design their strategies to minimize market frictions and maximize efficient execution.

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Assembling The Best Technology Stack

By Steve Grob, Group Strategy Director, Fidessa

Steve GrobThe traditional build or buy dichotomy is being eroded by the costs incurred to keep pace with persistent regulatory changes and rapid technological advances.

Brokerages and investment managers frequently face a choice: whether to build a technology stack internally for their trading operations or purchase the full package from a vendor. Both options have distinct advantages and drawbacks.

An organically devised system can ensure that the firm gets exactly what it needs, it has an opportunity to differentiate from others and the firm is not dependent on a third party if it wants to make adjustments to the system.

figure-1-historical-pictureHowever, it is expensive and there is a risk that the project loses its discipline, becomes unfocused, and is vulnerable to staff or departments pursing their own agendas – and even to a new chief technology officer keen to make their individual mark. Although there have been some successes, there have been many disasters. The alternative, a vendor-supplied tech stack, can be scaled for individual requirements, made fit for purpose and can easily be adjusted for future needs. On the other hand, the firm is tied to a particular vendor, which can reduce flexibility and potentially creates legacy burdens later. In the past, larger firms tended to build their own stacks and smaller firms used a vendor, but there is a change underway.

The cost of building from scratch and maintaining systems is now much higher. Continual waves of regulation have become the new normal, as have constant new developments in technology sophistication. At the same time the market evolves too, creating opportunities that need to be addressed, such as the shift from active to passive investment and the resulting surge in ETF trading. But underpinning all of this is the simple fact that the economics of the industry are not what they used to be, and so everyone is faced with doing more with less.

figure-2-impact-over-timeFor instance, Fidessa supports more than 200 equity and futures markets globally. Each of these might introduce two upgrades a year prompted by regulatory or other requirements. And so 400 necessary adjustments need to be made to Fidessa’s systems before any value-added improvements are made. This overhead only makes sense if the cost can be shared over multiple clients.

A third way
To resolve these problems, a third way has become increasingly popular: firms are no longer faced with the traditional dichotomy of build or buy.

Much of the different lower level technology that is necessary to instruct, transact and settle trades in exchanges and platforms across the world can be homogenised by firms like Fidessa. As a result, these different venues can be represented as a single, normalised surface to clients and they simply need to plug their tools into this layer to access liquidity.

This creates tremendous efficiencies for both buy- and sell-side firms and not just in their equities businesses, but also for derivatives, foreign exchange and even fixed income. It allows firms to concentrate on developing and retaining high value intellectual property – those smart algorithms, enhanced liquidity connectivity and solid risk controls that distinguish them from rivals.

Indeed, increasingly, investment firms are only differentiating themselves with the top level of the technology stack, such as their algorithms, multi-asset trading capabilities and how they manage and integrate their activities with a central risk book.

The further up the technology stack, the greater amount of intellectual property. But, inevitably, today’s ultra-sophisticated, jealously-protected algorithm soon becomes humdrum and mass-produced.

figure-3So, firms are examining the best way to use third-party components in their tech stack, working out ways to glue the pieces together. A typical choice is to amalgamate static or reference data into one securities master storage centre, and Fidessa and other vendors have created systems shared by leading financial firms and implemented across different asset classes.

Post-trade operations in particular are woefully inefficient. Many of the processes are still conducted manually, so there is plenty of room for improvements in cost, speed, accuracy, risk management and compliance.

For instance, it should be straightforward to install FIX-based utilities for post-trade processes in a similar way to pre-trade order-routing.

Greater sophistication, the rapid rate of technological innovation and constant regulatory prescriptions are raising the costs while shortening the shelf-lives of home-grown systems. Hence, the trend, the direction of travel is in only one direction: towards a wider adoption of the build and buy model.

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Turquoise Plato Block Discovery

By Robert Barnes, CEO, Turquoise

robert-barnesAt a time of global passive indexation and an electronic order book environment that naturally leads to small average trade sizes, investors who wish to outperform benchmarks are calling for innovation in electronic block trading.

To answer this call and still trade in the presence of anticipated MiFID II double volume caps, one needs a respected trading mechanism that can match orders received above 100% of Large In Scale (LIS) thresholds determined per stock by ESMA, the European Securities and Markets Authority.

Designed in Europe and refined in partnership with both buy-side and sell-side, Turquoise Plato Block Discovery is a Large In Scale (LIS) electronic execution channel that works. Activity continues to grow, setting new records.

figure-1-turquoise-plato-block-discovery
Turquoise Plato Block Discovery has registered new records above the volumes of June 2016, the month of the UK Referendum.
Turquoise Plato Block Discovery set a new monthly record by value traded in July 2017 of €5.49 billion, a 3% increase over prior record of €5.33 billion set in June 2017 and more than 9x that of July 2016. Such record activity highlights strong support of the trading community and scalability of Turquoise Plato Block Discovery.
Turquoise Plato Block Discovery has more than two and a half years of empirical data evidencing quality execution featuring: high firm up rates, low reversion, higher average trade sizes in an Open Access multilateral order book mechanism where consistently more than half of value traded – 56% in July 2017 – already is above 100% Large In Scale.

Turquoise Plato Block Discovery: higher trade sizes in an open access multilateral order book mechanism
Turquoise Plato Block Discovery is a broker neutral mechanism for executing anonymous block orders above 100% of LIS thresholds. Today, orders entered are eligible to participate if above 25% LIS. ESMA sets current LIS thresholds relative to an Average Daily Turnover (ADT) metric that segments securities into one of five Bands that set a security’s respective threshold.

table-1-esma-bands-by-adt-and-respective-lis

Turquoise Plato Block Discovery key observations from Table 2 for the period since September 2016 are that:

  • Where traded activity is above LIS, the average trade size is approximately double or more times the LIS threshold across all respective ESMA Bands of liquidity: Average Trade Size Multiple of LIS ranges from 1.9x to 2.8x.
  • All of the bands have recorded a maximum successful single trade size well over €1 million, the largest to date being €13.1 million, this was a single trade in Eni, the global energy company with primary listing on Borsa Italiana.
  • Turquoise Plato Block Discovery trades for ESMA Band 5 blue chips above ESMA LIS consistently average more than €1 million per trade.

table-2-turquoise-plato-block-discovery

Turquoise Plato Block Discovery trades for ESMA Band 5 blue chips above LIS consistently average more than €1 million per trade and are more than 100x larger than the €10,000 average trade sizes for the same ESMA Band 5 blue chips matching using continuous midpoint mechanisms. This is shown clearly in Figure 2.

Why does this matter?

  • Because orders with size above ESMA Large In Scale received by a venue can continue in MiFID II to trade with LIS pre-trade transparency waiver at midpoint and save half the bid offer spread = lower implicit costs.
  • Because larger trades that match with minimal market impact and lower implicit costs contribute to long term investment returns.
  • Because it shows Turquoise Plato Block Discovery is a working LIS electronic execution channel.

Helping investors get their business done
To visualise what these larger trades look like compared to average trading activity resulting from continuous order book activity, consider the following example of UK-listed company Next plc displayed in Figure 3. The intraday price chart displays time on the x-axis and price on the y-axis with trade prints enriched by trade size. Investors are trading shares of UK company, Next plc, on multiple trading platforms, including the electronic order book of its primary listing destination, London Stock Exchange, and Turquoise. This illustration shows the prices and sizes of trades by investors on 9 March 2017. Turquoise trade prices are similar to those of the primary Stock Exchange, and Turquoise trade sizes serve both the smallest and largest orders through its single connection for straight through processing from trading in London to settlement into Euroclear UK & Ireland. In this example, Turquoise not only enables investors to access a third of the order book value traded that day, Turquoise also matched the very largest order trades of all venues during the day via its award winning electronic block trading innovation Turquoise Plato Block Discovery.

figure-2-where-esma-band-5-stocks-trade-above-lis-via-turquoise-block

How does Turquoise Plato Block Discovery work?
Members send conditional messages called Block Indications to Turquoise Plato Block Discovery. When there is a potential match between a buyer and a seller, and both are able to get their respective Minimum Execution Size filled, Turquoise Plato Block Discovery sends an automated Order Submission Request (OSR) that requests each member send a Qualifying Block Order into Turquoise Plato Uncross.

figure-3-turquoise-plato-block-discovery-offers-additional

Buyers Guide – Consolidated Regulatory Reporting Systems: An Exploration of Multi-jurisdictional, Cross-regime Buyside RegTech Solutions

Buyers Guide – Consolidated Regulatory Reporting Systems: An Exploration of Multi-jurisdictional, Cross-regime Buyside RegTech Solutions

GreySpark Partners presents a report reviewing the consolidated regulatory reporting solutions of five third-party RegTech vendors utilised by buyside markets participants. The vendor solutions surveyed for this report are:

  • Advise Technologies’ Shuttle, Consensus and Signal
  • Broadpeak Partners’ K3
  • LIST’s Lookout@MIFID and Lookout@MAR
  • Trax Report, Trax Insight and Trax SFTR
  • UnaVista’s Buyside Reporting Suite

https://research.greyspark.com/2017/buyers-guide-consolidated-regulatory-reporting-systems/

Openness: The New Word In Trading

By Michael Chin, Managing Director, Co-Head of Trading, Thomson Reuters Financial & Risk

Open platforms allow clients to leverage multiple best-of-breed components in order to enhance performance, reduce risk and cut costs.

michael-chinToday’s trader needs to be able to connect to their counterparties, find liquidity, transact and prove best execution, with fewer resources than in years past. Fortunately, the rise of open trading platforms across the industry is helping to make this ask a reality, incorporating the key functions they require across the full trade life cycle, from pre-trade through post-trade.

Top trading platforms are often constructed from multiple proprietary and best-of-breed vendor systems, integrated to provide a seamless workflow and powered by a single source of market data to ensure consistency. They strive to meet the needs of market participants who demand openness, interoperability and connectivity between clients, partners, suppliers and their own employees.

In response to these demands, and in alignment with our open platform strategy for trading, Thomson Reuters acquired REDI, an award-winning, cross-asset execution management system, in January 2017. Through the acquisition, REDI is being integrated into both Eikon, our next generation financial markets desktop, and the Elektron market data platform. This integration provides a powerful buy-side trading workflow solution with interoperability between the platforms.

Challenges and trends
The need to adopt an open platform strategy is prompted by several macro trends that affect, in one way or another, all members of the financial industry.

First, there are pressures to minimize the total cost of ownership (TCO) of the trading stack and maximize scalability and agility. Financial firms are under intense cost constraints as regulation and competition are forcing a change in business models, and prompting a shift from products to platforms and from customers to communities. Cost-containment is likely to persist, acting as catalyst for technology innovation. Meanwhile, creating, distributing and monetizing new products and services will remain a challenge for both the buy and sell side.

Second, regulatory compliance is increasingly complex, costly and global. New obligations around transparency and risk management are coming into force, but within in a market structure that is still evolving in an unclear fashion.

Third, the momentum towards automation is relentless. Algorithmic trading extends across asset classes, while straight through processing, risk aggregation and liquidity fragmentation are driving further electronification . Next generation users also have greater technology expectations, forcing the creation of digital strategies and leading to the emergence of fintech firms that are disrupting existing operating models. The new financial consumer expects the same seamless, user-friendly experience for their trading platform as they have when making an online retail purchase or downloading a new smartphone app.

Finally, financial services are increasingly data and content driven. Greater market transparency is generating valuable new sources of data, but the task of aggregating and integrating these can be extremely resource intensive.

As a result of these trends, both the buy side and sell side are considering major changes in their technology choices. According to a recent survey by Aite Group, 58% of buy-side and 79% of sell-side firms are likely” or ”very likely” to consolidate and/or rationalize their trading infrastructure. They are turning to modular technologies that will help them scale, lower their TCO, offer frictionless integration and allow them to connect to the broadest set of content and liquidity partners for trading.

What is an open platform business?
An open platform business is unique in that it acquires, connects and matches disparate systems and networks to enable providers and consumers to do business, and does so without necessarily owning all the assets in the value chain.

Perhaps just as important, it’s a business model with a go-to-market mind set, and not just a technology approach.

Many of today’s wildly successful enterprises use this model. At a basic level, these businesses link together consumers and providers. They also treat every participant across the platform as a customer, and provide environments in which those participants can create value, both for themselves and for others.

Platform foundations
A successful open trading platform, such as the one we have built at Thomson Reuters, requires three critical building blocks: the tools, “gravitational pull” and the flow.

The tools are the mechanisms that allow customers and third parties to engage with and use the platform. These include application programming interfaces (APIs), technology platform access, contracting and permission services, network distribution capabilities and various developer instruments.

The “gravitational pull” incorporates those elements that make a platform a “must have” for market participants. These are unique news and specialist content sets, data delivery and aggregation tools, standards for ease of use and integration, unique search tools, a superior desktop experience and, importantly, human expertise.

The flow is made up of the participants themselves, who offer the connectivity and communications services and usage analytics that help bring together the community and facilitate transactions. By understanding what drives the value and transaction flow across communities, a platform operator can actually help to increase and sustain that flow.

Trading in an open platform world
Participants with an open platform community include exchanges and other trading venues, content and intelligence sources, banks and brokerages, regulators and central banks. They offer platform access, developer tools and APIs, as well as contracting, billing, permissioning and network distribution services. Consumers include asset and wealth managers, banks and brokerages, hedge funds and corporate treasuries, governments, regulators and central banks. They use a platform to transact, connect and communicate, as well as leverage analytics and end user tools and services.

The key concept and differentiator for the best platforms is to be “open”. This means allowing all participants to discover, create and deliver value, build relationships and transact.

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