Data-as-a-Service in a Data-Centric World


We live in an increasingly data-driven world. In no industry is this more apparent than in financial services, in which data drives decision-making in microseconds. Decisions made on the basis of time-critical data not only affect the firm or individual executing a trade but also the wider financial markets and, in some instances, entire economies.

The introduction of regulatory requirements for the publication of pre- and post-trade pricing and execution data by a wide range of trading firms has led to a proliferation of data available for asset classes that have historically only traded over the counter. Regulation now demands this of every bank and investment firm.


Data-as-a-Service and Data Providers

Providers have evolved to drive and support our increasingly data-driven financial markets. And it is becoming increasingly apparent to all players that they are not just delivering services to their own clients. Instead, they are part of a longer value chain, in which the services that they offer enable their clients to provide better services onwards to their clients. Improving that all-important “last mile” of delivery has knock-on impacts as consumers along the chain are better able to innovate and to deliver improved services onwards.

Data-as-a-Service is a key trend in a data-centric world. A data-driven view of the world in which you have domain experts threading the needle from the data creation all the way to data consumption “is a very, very valuable way of actually realising true data value from a business perspective”, says James Tromans, a Technical Director in the Office of the CTO at Google Cloud. The data consumed and used by trading firms must be high quality and in the appropriate format for the task at hand. Data used for pricing, decision-making and execution must be relayed to the place where it is needed in the timescale appropriate for a given asset class.

For providers of data-driven services, effectively integrating their offering into their clients’ ever-evolving workflow environment remains one of the greatest challenges but also one of the biggest opportunities. The “last mile” of delivery – the integration of data into the workflows of the clients who consume it – is often the last thing on the minds of data producers while it is top-of-mind for data consumers. From a client’s perspective, it can be the key differentiator.

For companies like Morningstar, it is the ingestion and integration of data from external sources – whether exchanges or other third parties – into their own environment, so that they can produce their own data services, that matters. For them, a solution such as ipushpull opens up opportunities to deliver greater value to clients by removing the barriers to accessing more data sources.

ULTUMUS meanwhile provides Data-as-a-Service but aimed at the enterprise, and a solution such as ipushpull gives them the capability to provide the data functionality in a way that meets the needs of traders as well, but within a licensed and permissioned structure.

Clients are increasingly opting for data services which can be delivered into their existing workflow tools of choice so that they can seamlessly integrate and automate. A new breed of FinTechs sit at the forefront of this trend by offering powerful, fast-to-market solutions incorporating technologies like Artificial Intelligence and Machine Learning. These solutions integrate seamlessly into their clients (and clients of clients) existing workflow tools, removing barriers to client on-boarding and integration. ipushpull, for example, enables data service providers to automate their data-driven workflows, freeing them up from the “last mile” of delivery to focus on their core value propositions.

In the financial markets of today, availability of – and access to – data on its own is only part of the challenge. That “last mile” of data delivery – enabling data to be efficiently, effectively and quickly consumed by applications and users across an organisation precisely when they need it – now gives data service providers that all-important competitive advantage.



Data-as-a-Service: Delivered live and seamlessly into your client workflows

9th June, 16:00 BST / 11:00 EDT


For brokers, banks, and providers of data-driven services, effectively integrating your offering into your clients’ ever-evolving workflow environment remains one of the greatest challenges but also one of the biggest opportunities. We will explore the burden of the last mile of delivery and what can be done to greatly improve the client experience.

Interested to hear more from Google, Morningstar, Ultumus and Parameta Solutions on this topic? Why not register now for a webinar we’re hosting on the 9th June, 16:00 BST / 11:00 EDT.



BNP Paribas Digitises Pre-trade Client Workflows

Pre-trade Client Workflows

ipushpull’s PPQ delivers enhanced efficiency for buy and sell-side firms for non-standard, complex trades.  

London, UK – May 2021: ipushpull, the real-time data sharing and workflow platform today announced that BNP Paribas, a leading global investment bank, have implemented PPQ standardised messaging to streamline their manual workflow around non-standard, complex trades, for their global asset manager community. PPQ has been designed to deliver enhanced efficiency, reduce operational and compliance risk and support trade negotiation. 

Many buy-side firms have long highlighted the gap in the market for a way of digitising complex transactions between asset managers and sell side firms. For example, LDI trading and other complex workflows require a combination of digital and voice trading interactions in addition to tasks performed using chat, email and Excel spreadsheets. This also includes the need to streamline manual processes and operational risk associated with emails, file sharing and copy-paste, as well as providing quick and efficient responses.  

PPQ is a pre-trade syntax which standardises and facilitates the negotiation process between the buy and sell side through a set of integrated data sharing and data-driven tools. It uses financial networks like Symphony to deliver the standardised syntax within private bilateral chats to allow trading and sales to communicate detailed information.  

Chatbots can interpret key data within those messages, display them within a custom application and allow the end user to drive the workflow from a single screen. Data mapping transforms incoming and outgoing data into the required format, creating an extensible solution to interoperate between new and existing standards. The inclusion of structured data objects within messages, containing instrument definitions, event descriptions and a wealth of other metadata, can further aid automation of pre-trade workflow.  

Ben Harvey, Senior LDI & Macro Rates Sales from BNP Paribas noted “As a bank that is continuously innovating our technology and processes to enhance our client’s experiences, we are pleased to integrate data-driven automation to support our sales organisation in delivering service excellence.” Harvey added “Complex derivatives are the next area where we are focused on process automation and improvement. This also underlines our approach to the next generation dealing room and to further develop the non-price element of our customer offering.” 

Matthew Cheung, CEO from ipushpull commented “We are delighted to see the positive impact that PPQ has had on BNP Paribas’ operational workflow and risk mitigation. Our unified modular and cloud-based approach enabled us to rapidly deliver this solution into production and provide quantifiable benefits.”  

About ipushpull 
ipushpull is a leading capital market FinTech firm that connects people, data and applications in real-time. We make sharing seamless by eliminating silos of data sitting in emails, spreadsheets or file shares and integrate that data into structured workflows.  

Data drives financial markets however data sharing has hardly changed for decades. Our goal is to improve human decision making by reducing the heavy lifting around complex manual repetitive tasks, allowing people to focus on value-add activity. 

For more information visit  



Matthew Cheung 


+44 20 3808 4085 

Media contact 

The Realization Group  

Melanie Budden 

+44 7974 937970 

Enhancing chat through standardisation of data

standardisation of data

The importance of technology and data connectivity was highlighted a year ago in March 2020 when the impact of the Covid-19 pandemic resulted in the Vix, which is also known as Wall Street’s fear gauge, reaching levels that were even higher than during the financial crisis in 2008. Staff had to deal with extremely high volumes while working from home and there has since been an acceleration in the digitisation of workflow to cope with the inefficiencies and inconveniences of remote working. Firms have needed better data in order to become more efficient and continue to serve their customers. 


Standardisation of data – one syntax

However, where dealers are still carrying out pre-trade negotiations over voice and chat there are often manual processes for recording quote data. By taking the heavy lifting away –the copy and paste, the rekeying, the robotic tasks – that employees do every day you free them up to do the tasks you want your humans to do – spark conversation, cultivate relationships, generate ideas and create revenue. Standardised syntax means you can rely on a set format and build technology to use those messages. This helps automate the repetitive processes to avoid failures. This could be something as simple as recognising a pricing request and pushing notifications out to the involved parties.

Standardisation of data and syntax also drives automation and whilst we look towards global uptake of these standards an interim state can still offer more efficient, safer processes that lead towards full electronification. Where standards are not adopted across the board there exists the ability to develop a translation layer so that both sides can use their native formats but still understand their counterparts requests and responses. When you can connect data sitting in existing tools and applications you can build data-driven workflows on top of that data. You are unbundling the data that was in spreadsheets, file shares, voice and chat and giving it a structure. That workflow becomes easy to record, auditable, trackable but more importantly it’s real-time and collaborative. Everyone sees the same real-time data and can interact with it and make decisions on it at the same time. This doesn’t just mean sales and traders but across the organisation as a whole – from compliance to operations to finance, legal and beyond. In order to analyse client relationships and focus on improvements for mutual gain you need a high quality, consistent, agreed data set to work from. That will only exist when you record your interactions accurately and at all stages of the process.


Artificial Intelligence

For the buyside to fully leverage value contained in their data its essential to bring Artificial Intelligence into the workflow to present insights and opportunities based on data that AI has processed.  This means we preserve the human interaction, whilst leveraging automation and ultimately allowing the trader to make a better decision – the trader will no longer interface with the data directly but with the possibilities of the AI processing the data.

ipushpull has recently launched PPQ (Pushpull Quotes), which standardises and automates the negotiation process to help both the buy and sell side achieve these aims. PPQ fits within existing workflows so neither the client or their counterparties need to install a new system. Trading and sales can enhance chat by communicating pricing information in private bilateral conversations more quickly and efficiently using a standardised syntax. Chatbots interpret key features within the standardised data and display customised information on the desktop so the user can manage their workflow from just one screen. Standardised syntax also allows bots to take on the heavy lifting of repetitive administrative tasks so trading and sales can minimise operational risk by removing manual touchpoints. 

If you would like to know more about standardisation of data, feel free to get in touch.

Regulators Focus On Compliance as Sales and Traders’ Workflows Remain Under Scrutiny

Sales and Traders Workflows

Firms that use automation and data-as-a-service will be better able to meet regulatory requirements as regulators focus in on sales and traders’ workflows.

When the coronavirus first appeared at the beginning of 2020 few people imagined that its effects would continue to be felt nearly a year later. The pandemic caused a dramatic shift in working practices globally. Many chief executives have since predicted that a hybrid model will continue with staff having the flexibility to partly work from home, rather than being permanently in the office. This has caused, and will continue to cause, challenges for regulated financial firms who are required to monitor the conduct of front office staff in capital markets, even when they are working remotely.

Initially the Financial Industry Regulatory Authority (FINRA) temporarily waived some of its supervisory rules in the US. However, as working from home has become the norm, the UK Financial Conduct Authority (FCA) has this year stressed the need for controls as risks from misconduct may be heightened or increased.

The regulator highlighted that these risks include increased use of unmonitored and/or encrypted platforms such as WhatsApp for sharing potentially sensitive information connected with work. Even without regulatory involvement, firms themselves have been taking action when staff have broken the rules. For example, two senior commodities traders lost their jobs last year just for using WhatsApp after an internal investigation at Morgan Stanley last year.

Matthew Cheung, CEO of ipushpull explains, “Helped by the need to work remotely, we are seeing a massive acceleration of digitisation in capital markets. A convergence of live data sharing, chatbots and cloud means pre-trade workflow for non-standard complex trades can now be streamlined and conducted from anywhere.”

Automating sales and traders’ workflows 

The FCA said it has acted against individuals and firms for misconduct which involved the use of WhatsApp and other social media platforms to arrange deals, including transmitting lists of trades to copy. The regulator has sought orders preventing such individuals from carrying out these activities in the future as it views these actions as serious. The FCA highlighted that it expects this to remain an area of focus, so firms need to take notice.

One way of helping front office staff comply with the regulations is to ensure that data is easily accessible from home through providing corporate VPNs and making workflows as automated as possible via use of the cloud.

Surveillance can be particularly challenging in markets where the majority of trades are still negotiated by front office personnel by voice. Firms are concerned about how they track chat/voice and its lack of immediacy as conversations may only be monitored or transcribed once a day. The industry is looking to overcome these challenges in a variety of ways. 

For example, Morgan Stanley is investigating how to automatically convert chats into request for quotes in credit markets. The use of Data-as-a-Service (DaaS) solutions allows technology, such as bots, to identify information  such as prices from free-form chat messages or voice conversations. ipushpull can extract data  in various formats from applications that firms are already using, and deliver it to the right place so it is integrated into their existing processes. 

The data becomes structured and can be viewed by authorised personnel in real time, who could include audit and compliance, in real time. Surveillance can be performed far more efficiently as messages or conversations are automatically linked to workflows, rather than staff having to decipher recordings or transcripts of phone calls or messages. 

In addition to monitoring the negotiation of trades, regulated firms need to show that they can continue to identify unusual trading patterns, despite staff working from home. For example, if a certain client always gets a better price or if the price of a deal is suspicious. Such surveillance can also be carried out much more efficiently with increased automation.

As a result the coronavirus has led to an increased investment in technology. A recent Deloitte survey found that the pandemic has clearly accelerated digital transformation in financial services with cloud computing and storage and data analytics among the top spending priorities. 

Author: Neil Weatherall

Download “Fintech’s Next Frontier: Data-as-a-Service” our Financial Markets Insights report. In collaboration with Natwest MarketsMaystreetEuromoney TRADEDATA and Engine, part of The Investment Association, ipushpull explores the importance of Data-as-a-Service in facilitating remote working and accelerating digital initiatives within the financial markets industry.

Sales and Traders Workflows

Natwest Markets Trading Desk Adopt PPQ from ipushpull

Natwest Markets Trading

ipushpull launch PPQ workflow solution, now adopted by NatWest Markets and hire former head of GBP Inflation Trading

London, UK – 09 January 2021: ipushpull, the live data sharing and real-time workflow automation platform, are delighted to announce that Natwest Markets have implemented their newly launched PPQ (Pushpull Quotes) workflow solution that streamlines manual workflow around non-standard, complex negotiations. At the same time Neil Weatherall has been hired to lead technical sales and PPQ product development.

PPQ is a pre-trade workflow tool which standardises and automates the negotiation process between buy and sell side. Using financial networks like Symphony and standardised syntax within private bilateral chats to allow trading and sales to communicate in a better way.

Chatbots can interpret key data within those messages, display them within a custom application and allow the user to drive the workflow from a single screen. Data mapping transforms incoming and outgoing data into the required format, creating an extensible solution to interoperate between new and existing standards. The inclusion of structured data objects within messages, containing instrument definitions, event descriptions and a wealth of other metadata, can further aid automation of pre-trade workflow.

Natwest Markets plus a further three top tier banks and one of the largest UK asset managers are already using PPQ and with a strong pipeline of interest, including further customers expected to adopt PPQ early in 2021.

Matthew Cheung, CEO of ipushpull, comments:
“We are seeing a massive acceleration of digitisation in capital markets. A convergence of live data sharing, chatbots and cloud means pre-trade workflow for non-standard complex trades can now be streamlined. ipushpull allows both buy side and sell side to take advantage of this.”

Neil Weatherall has joined Pushpull Technology following a long career with Natwest Markets and RBC Capital Markets. Neil started his career at Natwest in 2002 and went on to become Head of GBP Inflation. Rapid growth in the LDI industry and hedging programmes saw trade volumes increase exponentially across a diverse client base and as a result Neil has overseen large scale changes in the technology employed to price, book and manage trades.

Neil Weatherall, Head of Technical Sales, ipushpull, adds:
“I’m excited to join ipushpull at such a time of momentous change in working practices across financial markets.  Eliminating manual processes, creating standardisation and improving efficiency are paramount.  There are a significant number of complex instruments or package trades where the Pre-trade negotiation process is ripe for digitising and enhancing through our PPQ service. I’m looking forward to helping our clients move towards frictionless and seamless workflows, providing higher quality data and intelligence around their trading activities.”

About ipushpull
ipushpull are a capital markets fintech providing a live data sharing and workflow automation platform. Solving for the complexity around data sharing – we unbundle data sitting in emails, spreadsheets or file shares and bring that data back together into a structured workflow alongside manual tasks previously spread across different applications. Data drives financial markets however data sharing has hardly changed for decades. Our goal is to improve human decision making by taking the heavy lifting and manual administrative tasks away and leave people to do the things only people can do.

For more information visit



Matthew Cheung


+44 20 3808 4085

Media contactThe Realization Group

Melanie Budden

+44 7974 937970

Digitisation of Pre-Trade Client Workflows



Streamlining workflow for sales and trading desks

Although some areas within capital markets benefit from the efficiencies of electronic trading, the more complex and less liquid instruments still involve a great deal of manual, unstructured pre-trade activity. This creates friction (summarised in this SIFMA report), which is bad for client services, increases costs for both the buy side and the sell side, hampers liquidity and creates unnecessary operational risk, which arguably feeds into systemic risk at an industry level.

Can these issues be addressed by bringing more standardisation and automation to the market, particularly around pre-trade client workflows?

This was the topic of an online panel discussion hosted by The Realization Group and ipushpull on Tuesday 17th November, 2020. The webinar was led by Clive Posselt of The Realization Group, and featured Andy Mosson, Head of Strategic Partnerships, FICC eCommerce Sales, J.P. Morgan; Ayaz Haji, Head of Enterprise Reference Data, Goldman Sachs; Richard Turner, Senior Trader, Insight Investment; Craig Butterworth, Global Head of Sales & Account Management, Symphony; Andy Ross, CEO, CurveGlobal; Chris Scott, Senior Product Manager, TP-ICAP; and Matthew Cheung, CEO, ipushpull.


Spreadsheets on the trading floor

There are many inefficiencies resulting from over-reliance on manual processes and the continued use of e-mail, spreadsheets and copy & paste in pre-trade, particularly for non-standardised instruments traded bi-laterally via voice or chat. These manual processes are not only slow and cumbersome, they are also inherently risky and do not add much value from a trading perspective.

Messaging standards such as FIX and FpML can work well for simple products traded on electronic markets. But for more complex instruments, the various parameters of the trade are often not easily expressed in a machine-readable and understandable way.

And the inefficiencies persist across the entire pre-trade lifecycle for both the buy-side and the sell-side, impacting price discovery, negotiation, execution and booking of trades.

Spreadsheets are the common standard denominator and remain ubiquitous on the trading desk, because a) they serve a useful purpose and b) they can be quickly deployed. Firms that are constrained in their development resources have to be very selective about where those resources are assigned, and it is generally much quicker and easier for someone with business subject matter expertise to solve a problem by creating an Excel spreadsheet than to wait for a solution to be developed in-house. The issue with such spreadsheets and workarounds however, is that they are not standardised and they do not scale.


Towards a standardised approach

There is no shortage of potential solutions designed to help automate pre-trade workflow, both from established vendors and newer fintechs. However, the problem with many of these is that although they provide incrementally better tooling, they are still point solutions. The wider mission is to cohesively bring together some of these tools to leverage a common secure and compliant collaboration platform, to create standardisation at an industry level, where the buy side, sell side, exchanges, clearing houses, vendors and service providers all benefit from the network effect.

FIX is a good example of a well-governed, well-accepted protocol that has been widely used across the industry for some time. More recently, bodies like FINOS are creating standards for desktop workflow, enabling standardised tools that previously might have taken years to build, to be deployed in weeks or months. There are also situations where firms just get together and create what becomes a de-facto standard.

As these standards improve and become more widely adopted, they enable greater workflow automation. Fintechs, utilising tools like data mapping, allow firms to create a data-led approach and a more efficient client-focused process, thus providing the ability for firms to interoperate between all of these different types of standards and approaches, so that they can communicate seamlessly.

Financial institutions can leverage this technology to drive efficiency with the least amount of disruption to workflow, improving their speed to market and building and deploying bespoke solutions that no one else has, thus creating competitive advantage.


Impact of COVID-19

The onset of COVID-19 and the resulting increase in remote flexible working has certainly accelerated digitalisation initiatives. Anecdotally, there has been more digital transformation in the past eight months than in the last eight years. Long held biases against working from home have been disproved by necessity and highlighted the need for firms to have a coherent omni-channel strategy.

In this current environment, end users need to be able to seamlessly switch between multiple different communication channels as it suits them, by having device and data interoperability. But with the financial services industry being so heavily regulated, the challenge is enabling that whilst still maintaining the strictest levels of compliance and security.

The goal therefore, is to be able to take communication that historically might have been siloed or non-compliant, and funnel it through a more comprehensive, standardised platform that addresses those shortcomings, and at the same time meshes them into a broader workflow digitalisation strategy.

The rapid transformation we have seen due to COVID, converging with a thriving capital markets fintech ecosystem, has led to an increased demand for solutions that can unbundle the legacy data – spreadsheets, emails, file share, voice, and chat – and rebundle it together with the tasks that were spread across different applications, into new structured workflows.


Future State of pre-trade workflow

The future state of pre-trade technology is a world where instead of having highly paid professionals doing robotic tasks, we can instead combine the human and the machine conversations, the messages and the data, eliminate manual processes and improve efficiency by creating and adopting standardisation.

The ultimate goal for most technology providers is to free up traders and sales people to do the things that only humans can do, i.e. discuss the markets, give opinion, and create value, using new, live, collaborative, interoperating tools.

The industry now needs to address its legacy silos and re-engineer its manual pre-trade processes, with a mindset of delivering an improved experience, better internal efficiency and, at the same time, a significant reduction in operational risk.


On-demand Webinar & Report: Digitisation of Pre-trade Client Workflows

Learn how J.P. Morgan, Goldman Sachs, Insight Investment and TP-ICAP are approaching the digitisation of pre-trade client workflows.

Understand how market infrastructure providers like CurveGlobal, Symphony and ipushpull are facilitating this by improving price discovery and building liquidity through standardisation, automation and live data.



New Initiatives Around Standardisation and Automation in Capital Markets

Standardisation and automation in capital markets

By Matthew Cheung, ipushpull

In my last blog, I discussed the steps that firms can take to automate some of their pre-trade, time-critical workflows, and highlighted the advantages that such automation can offer.

However, automating these data-driven workflows in isolation within your own organisation only gets you so far. It does of course bring about some genuine efficiencies, as we’ve previously discussed. But for the industry to really move forward, we need to consider the essential role of data standardisation and automation in capital markets and generally in financial markets.

Data interoperability through open source

One area where significant progress is being made around standardisation is in the open sourcing of data platforms, allowing for data interoperability across organisations.

A real-world example of this is the recently announced launch of Legend, Goldman Sachs’ flagship data management and data governance platform, now open sourced through FINOS, The Fintech Open Source Foundation.

This is an important step for the industry, because it demonstrates how a number of leading banks (including Goldman Sachs, Deutsche Bank, Morgan Stanley RBC Capital Markets, and others) are all working together within a shared environment, to prototype interbank collaborative data modelling and standardisation.

The pilot project – initially for FX options – was to build extensions to the Common Domain Model (CDM), developed by the International Swaps and Derivatives Association (ISDA). Utilising this framework, industry participants can now use and build their own models collaboratively for a range of purposes using open-source components, and feed those back into the common standard.

In the press release announcing Legend’s launch, Goldman Sachs’ chief data officer and head of data engineering said, “We believe this new data platform is so powerful and important that we are making it available to our clients and the world fully open and free of charge as an open source platform through FINOS.”

This is a big deal, because it shows that industry competitors can actually work together to solve industry challenges. And they can do it by providing a means for market participants across the industry to collaborate and share data using standardised data models, not just in the front office, but also across the middle and back office.  

A welcome development

With the current lack of common terminology and common definitions in the industry, particularly for more exotic, non-standardised instruments such as OTC derivatives, these kinds of open-source, collaborative initiatives are a very welcome development.

One of the great things about standardisation is that it makes everything easier to streamline and automate. In an ideal world, every system within every organisation would be able to read, write, and speak the same language, so that there would be no barriers; everyone would be able to seamlessly connect to everyone else, and every piece of incoming data would have the ability to automatically trigger events in connected systems.

This is in fact one of the main reasons why ipushpull exists, to give firms the means to achieve this regardless of which standards they adhere to.

But it’s great to see other examples of how the industry is moving towards this future state. And we expect to see a fairly rapid take-up of these open source standardisation initiatives, across both the buy-side and the sell-side, leading to increased automation and greater efficiencies across the board.

Find out more about Standardisation and Automation in Capital Markets, in our upcoming webinar.

On-demand Webinar & Report: Digitisation of Pre-trade Client Workflows

Learn how J.P. Morgan, Goldman Sachs, Insight Investment and TP-ICAP are approaching the digitisation of pre-trade client workflows.

Understand how market infrastructure providers like CurveGlobal, Symphony and ipushpull are facilitating this by improving price discovery and building liquidity through standardisation, automation and live data.


Automating Data-Driven Workflows in Financial Markets

Data-Driven Workflows in Financial Markets

By Matthew Cheung, CEO, ipushpull

In previous blogs, we have focused some of the benefits of Data-as-a-Service (DaaS), discussing how DaaS can be used to accelerate digital initiatives, for example. We’ve also discussed the practicalities of how firms can enable DaaS on their legacy platforms and the steps that data-rich firms can take to offer DaaS-based products to their clients.

In this blog, I’d like to clarify why it’s important for firms to progress from pure data distribution towards data-driven workflows in financial markets, examine some use cases, and explore the benefits that automated data-driven workflows can offer.


The need for financial markets workflow automation

As a starting point, what do we actually mean when we talk about data-driven workflows? It could be argued that all workflows – regardless of their simplicity or complexity – are data driven. Something happens (an event), resulting in new or updated information (data), which triggers an activity or a process (the workflow).

In the financial markets sector, workflows across the front, middle and back office have typically been established over a number of years. And while these workflows may serve their purpose, many entail manual processes that are inefficient, time-consuming, labour-intensive and not scalable.

This is a problem for the industry, and why greater automation is needed. Particularly in the front-office, where information tends to be time-critical. Firms may not realise how much these manual processes – acting on instructions received in chat windows, sending and receiving emails, transferring spreadsheets or other files back and forth, and so on – is hampering their ability to grow. A common attitude around existing workflows is, ‘that’s just the way things are’.

But things don’t have to be that way. And automating data-driven workflows can lead to greater efficiencies, cost savings, and higher growth potential.

So how do we get there?

The first step is recognising that data needs to be at the core of everything. What often happens at the moment with existing processes, is that they can result in multiple versions of the data (in multiple formats) residing in different places, with users needing specific applications, spreadsheets, chats or emails to support their version of the data.

In an automated data driven workflow, a golden source copy of the data sits centrally, and as it moves around, processes based upon that data are triggered automatically. So all of the workflow happens around the data. This approach is faster, more efficient, more scalable, easier to streamline and automate, easier to integrate, and there’s always a clear audit trail.


Use Cases: Data-Driven Workflows in Financial Markets

How does this work in practice? Let’s look at a few examples.

Real-time Pricing of basket trades

ipushpull is helping a leading institutional broker create automated workflows, for both the broker and its clients, around live pricing of basket trades. Previously, the workflow was a highly manual, labour-intensive process, where the client would send to the broker (via e-mail) a spreadsheet containing hundreds of lines of individual stocks, which would then have to be copy/pasted into the broker’s format for pricing, with the resulting data being copy/pasted back into the client’s spreadsheet format and e-mailed back to the client.

Although this a fairly standard workflow in the industry for pricing basket trades, it is time-consuming, error-prone and totally unscalable – there are only so many of these types of trades a broker can do in a day, given the manual effort involved.

Working with ipushpull, the broker is now automating a data-driven workflow whereby clients can push their basket directly from their spreadsheets, the stock data is recognised and mapped to the brokers format so the pricing can be rapidly generated. It is then automatically sent back to the client in Excel, with little or no manual intervention other than oversight of the process. This is enabling the broker to work much more efficiently, pricing more trades, in a more accurate and timely manner, and gaining new scalable business as a result, as well as eliminating keystroke risk.

Distributing Bond Axes

The fixed income division of a leading UK bank has created an automated workflow to send live prices for bond axes to its clients. In this case, the bank’s dealers are able to publish relevant axes with live prices in a Symphony chat window, which the client can execute directly from a chat. That then triggers a full STP process to automatically trade and update the bank’s internal systems.

Previously, this was a much more manual process, involving e-mails being sent back and forth, or copying information from other systems and applications into chat windows. Whereas what the client sees in the chat now is live, executable data that can be acted upon immediately either with a bot or direct with a sales person.

Streamlined pre-trade Workflow

The third use case is an investment management firm building automated data-driven workflow for FX options. The manual workflow they had – again, fairly standard in the industry – was that the trader would receive an instruction from a portfolio manager via their internal system, manually type that into a chat to its dealers and negotiate pricing across mulitple different counterparts.

Using ipushpull, this workflow has been streamlined removing any manual processes – any related operational risks – on the buyside.



The key to all of this is understanding the data, looking at the manual processes that still exist around time-critical workflows, finding the bottlenecks, and determining which processes are ripe for automation.

The good news is that the technology is now available from ipushpull to automate those processes without significant upheaval to firms’ current workflows, so users are still able to work within familiar chat and collaboration apps like Symphony and Excel Spreadsheets, but without the manual inefficiencies.

As these tools and technologies become more widely used, firms will no longer be able to remain competitive by over-reliance on manual workflows. Instead, moving to data-driven workflows will accelerate the path to a data-driven enterprise yielding significant benefits.


On-demand Webinar & Report: Digitisation of Pre-trade Client Workflows

Learn how J.P. Morgan, Goldman Sachs, Insight Investment and TP-ICAP are approaching the digitisation of pre-trade client workflows.

Understand how market infrastructure providers like CurveGlobal, Symphony and ipushpull are facilitating this by improving price discovery and building liquidity through standardisation, automation and live data.



Digitalising Financial Markets with Data-as-a-Service


How ipushpull cloud-enables firms to seamlessly share live, streaming, and on-demand data with Data-as-a-Service.

There have been many unpredicted outcomes from the current COVID-19 pandemic, but one of the more interesting ones has been the rapid acceleration of digitalisation. How rapid? Well, earlier this year, Microsoft’s CEO Satya Nadella stated that they’d seen two years’ worth of digital transformation occur within the space of two months, something that was inconceivable at the start of the year. While IBM’s CEO Arvind Krishna said “history will look back on this as the moment when the digital transformation of business and society suddenly accelerated”.

Like many other industries, the financial markets sector, with so many staff confined to working from home in 2020, has suffered severe disruption to existing workflows, forcing firms to readjust their working practices.

But with every challenge comes opportunity, and the savvier firms are looking not only at how to get through the current situation, but how they can transform their business for the better over the longer term by utilising Cloud – and specifically Data-as-a-Service (DaaS) – as an enabling technology.

What is DaaS & what can it offer?

Data-as-a-Service provides the ability to seamlessly connect your data to the right person, at the right time, in the right application. This means that you can share your data – which could be sitting in a database, in a platform, or even in a spreadsheet – with your clients, your counterparties, or your colleagues, directly into applications they’re already using. Excel spreadsheets, chat platforms, chatbots, even internal platforms via an API, for example.

ipushpull’s approach to DaaS is to integrate into both legacy and cloud-based technologies, enabling firms to access and share live, streaming, and on-demand data across the entire trade lifecycle, from the front office through to the middle and back office.

To offer a few examples, live data might be an investment bank distributing live ‘high touch’ bond axes to the buyside’s spreadsheets, OMS or chat platform. Streaming data could be where a market-maker is constantly updating quotes from an internal pricing engine, or a broker client workflow of publishing real-time prices to clients in a ‘call around market’. And on-demand means that end users can pull the most up-to-date data from any data source. Ops users may be pulling down the latest list of ISINs to match to RIC codes for example, or risk managers might need to see live P&Ls in Symphony or Slack.

All of this needs to come with the requisite enterprise security, control, and audit necessary for financial markets.

Embracing the Cloud

Historically, data sharing in capital markets has been problematic. Either it’s been done manually, through emails, file sharing, and copying/pasting data – which is then very hard to streamline, automate, and audit – or firms have had to use expensive developers to connect data together, with none of it being ‘out of the box.’

ipushpull bundles all the data and tasks that were spread across spreadsheets, email and file shares into a new structured flow into any connected application. Utilising the Cloud as an enabling technology means you can share data inter as well as intra company. You can share data to trigger workflows with external clients, customers, and teams, and do it in any application via plug and play. And using the Cloud means it’s incredibly scalable, it’s significantly cheaper than trying to build it yourself, and it has a fast time to market.

The Cloud also offers several commercial benefits for both the suppliers of data and the end-users. From the end-user perspective, only paying for what you need allows you to match and scale your operational costs more closely with your trading activity, for example.

Beneficial use cases

Where our customers already have the data and the platform, but may lack the distribution into end-user applications, they have successfully used ipushpull either for the first or the last mile of connectivity.

The first mile is where data may be unstructured or sitting in an application or system that generally does not have any external connectivity. By connecting into ipushpull, data can be securely pushed into the Cloud and then made available elsewhere.

The last mile is about getting data into the applications or tools that your clients or your teams already use, so nothing new needs to be installed. That data can be coming directly into spreadsheets, into chat, or collaborative apps such as Symphony or Slack, or straight into your internal blotters or platforms that you might be using for that last mile of distribution.

Importantly, nothing is on-premise. Everything happens via the Cloud. Rather than engage costly development teams, or rely on manual processes where someone has to copy and paste from one application to another and send it to a counterparty who is doing something similar – a process that involves lots of manual tasks, emails, spreadsheets, copy/pasting and the like – by moving to this new way of data sharing, it unlocks both technical efficiency and automation, which means your staff can spend their time on higher-value activities or things that only humans can do such as being creative, complex decision making or speaking to clients.

A growing number of firms, including panelists from our recent webinar, such as NatWest Markets and Euromoney TRADEDATA, are now utilising different flavours of the examples given above. All of them are using ipushpull to accelerate digital initiatives to widen digital distribution channels and provide better experience for their clients and workflow efficiency and automation for end-users.


The digitalisation of these types of use cases will become more commonplace as people question why they are still using manual processes or one-off development projects to share data. As Data-as-a-Service becomes more prominent and firms look for technical efficiency and automation, we’ll see this new way of sharing data becoming the norm.

We see it already in the digitisation and electronification of OTC markets, where manual processes make way for standardised delivery of prices and workflow, but why stop there? Live data sharing can be ubiquitous internally across the firm, and externally to clients and counterparts – all of this being accelerated by the Cloud and by integrations into financial networks like Symphony, Refinitiv, Bloomberg, Broadridge, DTCC, Markit, etc.

In the post-COVID landscape, there is no new norm anymore. There is only a future state. As working practices change, workflow needs to be more efficient, and data needs to be easy to access, secure and access-controlled.

As we move towards live data-driven workflows, people need to be able to seamlessly connect to data in any application in real-time, at the right time, at the right place, and from any location.

We’re seeing Data-as-a-Service being adopted across sales and trading, between sell-side and buy-side, and across technology vendors. All of them are providing a better and more efficient experience for their clients.

It’s time to move away from manual processes, emails, spreadsheets, and copy/paste and away from embarking on expensive development projects to connect data from one app to another. Instead, look to incorporate Data-as-a-Service into your digital transformation projects or as a new digital distribution channel.

On-demand Webinar & Report: Digitisation of Pre-trade Client Workflows

Learn how J.P. Morgan, Goldman Sachs, Insight Investment and TP-ICAP are approaching the digitisation of pre-trade client workflows.

Understand how market infrastructure providers like CurveGlobal, Symphony and ipushpull are facilitating this by improving price discovery and building liquidity through standardisation, automation and live data.


Moving towards future state in capital markets – The Financial Technologist

future state in capital markets

It’s a very wide spectrum in capital markets between legacy user environments at one end and the equivalent of the SpaceX Dragon 2 mission and its recent launch at the other, where automation is center stage. There is a lot that firms can be doing today to move towards the latter, especially as fast evolving consumer products set a precedent for other industries. The number of growing millennials in capital markets who are taking up senior positions expect technology in office environments to offer regular improvements and functionality updates as standard. The future state in capital markets is evolving.

Areas which before were considered a nice to have, are becoming the new norm in the dynamic that the COVID pandemic created. Standardization and aggregation of data, multi-application interoperability and reducing the overall screen real estate are becoming essential in the migration to the new environment.  

There is one component for many users across the front, middle and back office which is even more often used than Bloomberg, one that has achieved notoriety – Microsoft Excel. An integration of this component is key, whether between users, chat apps or an ecosystem of other applications which can be used to further workflow. 

How can we build a better user experience? How can traders optimize their workflow in and out of the office? What is the best way to collaborate on data between departments and locations? 

Find out more in the interview by Matthew Cheung in The Financial Technologist ‘Phoenix’ out now.  

Tune in to hear more on “Creating a Blueprint for Pandemic Recovery in Financial Technology” webinar on 19th August at 5pm BST, where Matthew Cheung and an expert panel will be discussing the topic in more detail.