financial markets – ipushpull

November 16, 2020November 26, 2020

New Initiatives Around 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.

REGISTER HERE

November 11, 2020April 9, 2021

Automating 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.

Conclusion

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.

REGISTER HERE

August 6, 2020August 6, 2020

Using Data-as-a-Service to Accelerate Digital Initiatives

Financial markets firms are increasingly capitalising on their data by taking advantage of cloud-based technologies that enable them to seamlessly connect with desktop applications. In a recent webinar, industry experts discussed how Data-as-a-Service enhances client experience, widens digital distribution channels and provides better workflow efficiency and automation for end-users.

Microsoft reported a record fiscal year in July 2020 with commercial cloud revenues surpassing $50bn for the first time, an increase of more than a third from a year ago. Satya Nadella, chief executive officer of Microsoft, said on the earnings call that the previous five months had shown that digital technology intensity is key to business resilience. Nadella said: “Organisations that build their own digital capability will recover faster and emerge from this crisis stronger. We are seeing businesses accelerate the digitisation of every part of their operations to reimagine how they meet customer needs.”

Financial services firms have needed to digitise as Covid-19 has forced working from home while maintaining the same service to their clients. The Realization Group hosted a webinar in July 2020 with a panel of experts to discuss how firms of all sizes, from the sell side to the buy side, can use Data-as-a-Service to emerge better, faster and stronger in the post-pandemic world.

Data sharing in capital markets has historically been a very manual process, involving emails, file sharing and copy and pasting. Matthew Cheung, chief executive of ipushpull, explained that Data-as-a-Service (DaaS) allows firms to automate this process and seamlessly connect their data to their clients while providing the first or last mile of connectivity to end-user applications.

The fintech ‘pulls’ the required information from a database, a platform or even a spreadsheet and ‘pushes’ it to recipients in applications they already use, such as Excel spreadsheets or a chat platform. Clients will have preferences on whether that data is live, streaming or on-demand and DaaS can also meet the capital markets regulatory requirements of security controls and audit trails.

“The cloud is an enabling technology so Data-as-a-Service allows firms to share data in any application and it is all plug-and-play,” Cheung added. “Covid-19 has accelerated cloud adoption and digital transformation projects across markets.”

This was backed up by a poll which found that the vast majority of the audience, 85%, had heard of DaaS. In addition, Covid-19 was the top factor driving their firm’s digital transformation with 30% of the vote.

Capital markets firms have traditionally built their own technology but John Macpherson, deputy chair of the Investment Association’s advisory panel for Engine, a fintech accelerator for the asset management industry, said that ship has sailed. More than half, 58%, of the audience agreed as they said they would buy, rather than build, DaaS technology.

Macpherson added: “The buy side very much looks at DaaS as a cost-efficient responsive service that allows them to focus on selling their products.”

Data-as-a-Service also creates a faster path to innovation, giving firms a more agile decision making process and a more data-driven culture which lowers risk and leads to higher revenues.

“Once these dots are connected DaaS will become more prevalent,” said Macpherson. “There are phenomenal opportunities from getting the right data at the right moment in the right format so that people can make better decisions.”

Patrick Flannery, co-founder and chief executive of data infrastructure provider MayStreet, broke down the four stages of using data effectively – collection, storage, transformation and delivery. Each stage presents a challenge, for example, storing large amounts of data can cost hundreds of thousands of dollars per month in each region. Flannery said: “Firms will have an ocean of unstructured data. They need to pull out the relevant piece and then integrate it into their downstream workflow. Giving it a go themselves may actually give them a first-hand view of the resources needed to do it right and push them into the direction of DaaS.”

Julien Dugat, fixed income client execution platforms and digital sales at NatWest Markets, explained that the main reason the bank chose to use ipushpull, rather than build, was the speed to market of using an off-the-shelf product.

“You don’t need to spend ages customising the product and integrating it with your own data feed, so you can get going really quickly”, Dugat added.

NatWest Markets uses electronic venues’ FIX API’s and ipushpull to distribute tens of thousands of daily axes to clients more efficiently than through phone calls or emails. Automating the process means the axes are always up-to-date, actionable, relevant and easy to access by clients. The bank sends a stream of live data to the ipushpull cloud and clients can pull the data in their preferred format, such as Excel or a Symphony chat. The majority of the audience, 63%, said they would prefer to use Data-as-a-Service through APIs, followed by Excel and then Symphony apps and bots.

Dugat said: “Clients don’t need to install anything on their desktop but can, for example, access our data through Symphony or the ipushpull web app or mobile app so it is a very low barrier to entry.”

The NatWest sales desks also use ipushpull to easily send highly targeted relevant axes to specific clients. A client may want auto sector bonds, and the salesperson can filter the axes and send them by clicking one button. Clients can also trade axes more efficiently as the bank has integrated ipushpull with SCOUT, an execution bot in Symphony.

Dugat said: “It is about getting the right data to the right person at the right time. Rather than just inundating everybody with lots of data, we make it relevant.”

Mark Woolfenden, managing director of futures and options reference data supplier Euromoney TRADEDATA highlighted that DaaS provides opportunities for small and medium-sized firms to access the same high-quality data as large firms, as they would be able to pay just for the data they used.

“More flexible business models could include offering data on-demand as part of the trade lifecycle from pre-trade risk validation to post-trade regulatory compliance and portfolio management,” Woolfenden added.

Cheung concluded that he expects digitisation and DaaS to become more common. He said: “Moving to this new way of data sharing unlocks efficiency and automation, so humans can spend time on higher-value tasks.”

Contact ipushpull at sales@ipushpull.com for further information or for a live demo of Data-as-a-Service in action.

May 23, 2018May 23, 2018

ipushpull win Benzinga Global Fintech Award 2018

ipushpull have been announced as winners in the Benzinga Global Fintech Awards on May 16^th 2018, setting the live data sharing and collaboration platform apart as the most innovative by what is the equivalent of the fintech Oscars. Each year the greatest advances in fintech from leaders and visionaries in the worlds of finance and technology compete for the sought after prize.

The company was recognised for its vision of real-time data interoperability by improving and unifying the data sharing landscape in financial markets, by being awarded the ‘Best Proprietary platform or API’ in the category, having competed against 16 other companies in this fintech category. With 200 finalists contending for prestigious awards, winners were determined by a panel of judges made up of industry experts from firms such as Citi, JP Morgan, Alliance Bernstein, Nasdaq, D.E. Shaw, Fidelity, DRW and Worldquant.

Benzinga is a leading financial media publication and data provider that was founded in 2010 by Jason Raznick. We are very proud to have been chosen by Benzinga and to receive this award at the New York show.

Benzinga CEO Jason Raznick says:

“The Benzinga Global Fintech Awards has consistently highlighted the work of the most innovative companies in fintech for four years. We’re proud to celebrate the trailblazing work of companies like ipushpull.”

CEO Matthew Cheung on receiving the award:

“Thanks to the early adopters of ipushpull, 2018 has been a tipping point for the company with banks, brokers and funds using our platform for live, secure, access controlled data distribution and collaboration across a variety of applications and cloud services.”

About ipushpull

ipushpull is a secure, audited and access-controlled live data sharing and collaboration platform providing live data interoperability between applications over the cloud or over an intranet, meaning that ranges of live data can be shared and collaborated on between connected applications.

BZ Awards are hosted annually and provide the opportunity to meet and network with executives, developers and innovators from the worlds of finance and technology. For more information about Benzinga visit www.benzinga.com

To learn more about ipushpull please visit https://www.ipushpull.com or contact the business development team on sales@ipushpull.com

January 24, 2017February 9, 2017

iPushPull – Giving you Big Data, Fast

Big Data describes the increasingly large volumes of data that companies collect every day, through social media, clickstreams, data sensors and point-of-sales. If they’re able to analyse these massive sets of structured and unstructured data and unearth the patterns and trends hidden inside, companies can discover a great deal about their customers, employees and even their business’ operational efficiency. Big Data is becoming the key basis of competition, increasing productivity and aiding innovation, as found by MGI and McKinsey’s Business Technology Office. But if we can’t get to big data, fast, is there any point?

For companies completing operations such as fraud detection and compliance reporting, for example, data needs to be analysed on demand and acted on quickly or it loses value. To get around this issue many industries, including financial services, have started to integrate outside API technology.

The Problem with Big Data

As a recent article from DataInformed stated, data has a shelf life. It’s all very well if your analytics framework can tell you how you should have kept your customers satisfied yesterday. However, you’re likely to lose out to a competitor who has worked out how to keep them satisfied today and tomorrow.

The era of big data seems to be fostering the false notion that we are obliged to retain any data that we come across as it could potentially be useful. Companies need to employ a ‘use it or lose it’ attitude in order to combat this data hoarding. Data needs to become transparent and usable at a higher frequency, making big data fast and flexible. This can lead not only to better consumer insights, but also expose variability and boost performance through the collection of accurate and detailed information on everything from product inventories and purchase behaviour to employee performance.

This is particularly relevant in the financial markets, where in banking and insurance, enterprises need immediate access to the most relevant data. They need big data, fast. It is far more valuable than the petabytes of historical data that has sat in warehouses for years. Having rapid access to relevant information can be used for low frequency forecasting, high frequency nowcasting and help management make more precise business decisions.

The Solution

At iPushPull, we’re experts in delivering real-time data to the desktop for our financial markets customers, from trading services to Fortune 100 banks. Not only do we help you get access to your big data in less than a second, but we also deliver it to the applications you and your team already use, like Microsoft Excel. And we let you do more with that information by letting you share it instantly and continuously between Microsoft Excel, Slack, Symphony, the web and mobile on our encrypted, audited and monitored platform.

Next we’re partnering with big data platforms like Cloudera and SAS. Just another way we give our customers real-time access to their analytics wherever they are, whenever they need it.

Please get in touch to find out more, or sign up for a free trial.