Algomi is a software company that provides technology to bond market participants to improve their workflow and liquidity through data aggregation, pre-trade information analysis, and execution facilitation. (Algomi) Founded in 2012 by UBS credit e-commerce alumni Robert Howes, Usman Khan, Michael Schmidt, and Stu Taylor, Algomi originally offered a product called Honeycomb - an information matching system that directed buyers to sellers in the fixed income market. (MarketsWiki) However, in 2017 it was sold the ownership of a fixed income data aggregation and market surveillance tool called ALFA (Automated Liquidity Filtering & Analytics) that had been developed as a proprietary tool by Alliance Bernstein. ALFA has since become Algomi’s strategic focus at the core of their mission to become an indispensable part of the fixed income capital markets. (Algomi)
Alliance Bernstein started developing the ALFA platform in 2015 to bring greater clarity into the state of the bond market at any given time. As electronic execution facilities had continued to cement their place in the trading world, the investment professionals at Alliance Bernstein, like all institutional fixed income investors, had begun to lose sight of the bond market. So many trading platforms had emerged, each with their own sets of coverage and market participants, that getting a holistic view of the market had become very difficult work. The fixed income team had noticed that with the changes in market structure that had resulted from a drift towards electronic execution, and from the impacts of post-crisis regulations, those who could effectively address issues such as price transparency, liquidity, and efficiency would have a competitive advantage. Thus, ALFA was born. (Turner, 2017)
ALFA brings together liquidity data from all available major electronic venues, messaging platforms, and dealer inventory feeds, and combines them into a single consolidated landscape. As an all-to-all trading platform – one that allows buyside-to-buyside as well as sellside-to-buyside transactions – ALFA begun to take away the bargaining power from dealers when it came to pricing and profit margins per trade (reportedly, it had shaven an average of 4.5 basis points off the bid-ask spread). Despite any competitive advantage that ALFA may have offered Alliance Bernstein as a proprietary tool, the institutional investor realized that for it to reach its full potential, it would require greater dedicated attention to onboarding market participants and sources of liquidity. As such, as a result of their focus on fixed income data technology solutions, Algomi was chosen to be the buyer within a competitive bidding process. Once sold, the product was officially renamed to Algomi ALFA. (Algomi)
When Alliance Bernstein sold ALFA to Algomi, it took an undisclosed minority stake in the company, and a seat on its board. Outside of this investment, Algomi has raised $14 million in outside funding over the course of seven rounds. Its initial 2012 Series A came from Lakestar, a European venture capital firm focused on digital and technology entrepreneurs. In 2013, Lakestar doubled down for a Series B in partnership with Hoxton Ventures, another European venture capital firm. Since these initial investments, Algomi has continued to raise funding over five further rounds from both VC/PE funds, and its market data/exchange partners: Euronext, S&P Global, and Euroclear. (Crunchbase)
The problem that Algomi ALFA is trying to solve is twofold: (a) inconsistent liquidity in fixed income markets following post-crisis regulation, and (b) fragmentation in fixed income execution workflows.
The first of these issues is something that all institutional fixed income investors have been grappling with in the post-crisis world: liquidity just isn’t the same as it used to be. There are arguments both for and against this. On one hand, there are many observable signs that liquidity has improved. Primarily as a result of a rise in the e-trading facilities that have connected buyers and sellers in a more efficient way than was possible in the past, it is much easier to find someone to take the other end of a trade most of the time. With the buyside being able to easily trade with each other in addition to through a dealer, bid-ask spreads have thinned, making prices more consistent. Additionally, an overall increase in trading volume means that trades generally have less impact on the market, which creates an environment of lower volatility. However, on the other hand, there is also observable evidence that liquidity now appears to completely dry up in times of stress. Large institutional investors seeking to offload large positions in a very short period of time in response to a market event have historically been able to turn to a dealer, who would be willing to take on the risk of the position in return for a higher price, to execute such a transaction. However, due to post-crisis regulations, dealers aren’t given as much freedom to take on such positions, meaning that sellers can be often left stranded without a buyer. (Turner, 2016)
The second of these issues is a manifestation both of post-crisis regulations and of the rapidly evolving electronification of the trading domain; not only are there many more steps that need to take place during a trade, but there are now many more ways to execute, and different tools for every step of the process. Following MiFID II, trades involving at least one European counterpart must now digitally evidence their entire trade process, from outreach to a client through to settlement, and demonstrate best execution to showcase that all participants received a fair price. To make matters more complicated, electronic trading systems have given rise to complex trading algorithms that can execute a single order across multiple venues and counterparties based on a set of rules. The lower barriers to entry when creating trading software resulting from advancements in cloud computing has led to a multitude of different platforms attempting to service these various needs in the trade lifecycle, which has formed a crowded landscape with very little connectivity.
By connecting more of the marketplace together, Algomi ALFA provides better insight into available liquidity and offers algorithms that can help place trades more efficiently across all venues. ALFA aggregates the entire bond landscape into one screen, alerts buyers and sellers of liquidity opportunities, helps traders determine the best mode of execution, offers tools for optimizing bond selection, hooks into execution platforms, and provides evidence for best execution and TCA to meet regulatory obligations. Not only does this amalgamation bring together the disparate components of the trading workflow; it also increases overall liquidity, improving the chance that a position can be liquidated efficiently in times of stress. (Algomi)
What’s interesting about Algomi ALFA is that the company’s CEO, Scott Eaton, has opted for a strategy of “co-opetition”, or partnering with potential competitors rather than trying to displace them, in order to create a true end-to-end trading service for fixed income. He has not sought for Algomi ALFA to be a new trading platform in the domain, but the glue that stitches all of it together. Recent partnerships have been made with fixed income trading platforms Trumid and Liquidnet to allow for execution capabilities in addition to the original data aggregation offering, and with companies such as Euroclear for increasing the amount of data available on the platform. (Business Wire, 2019) As such, there is no apples-to-apples competitor to Algomi ALFA as a purely fixed income-focused EMS offering an end-to-end solution for searching, communicating interest, and initiating execution. (Markets Media, 2019) Since Algomi took on the ALFA platform, they have been targeting PMs, traders, and quants at large institutional investors with at least $500 million in assets under management as their users, forging partnerships with industry giants such as PIMCO, T. Rowe Price, and Brown Brothers Harriman. However, they also have several sellside institutions opting to trade via their platform as well. As of this year, they claim to have 20-21% of the $102.8 trillion global bond market going through their platform. (Kolcha and Podziemska, 2019)
When Algomi took on ALFA in 2017, they made two notable technological changes. First, they rewrote the program in HTML to align with the industry trend towards web technologies, and second, they opted to partner with OpenFin for its cloud-distribution and interoperability capabilities. OpenFin is an Electron and Chromium-based platform that is striving to become something of an app store for the financial services industry. OpenFin offers a launcher with a lightweight onboarding process that allows developers to onboard applications into its environment by providing a JSON configuration file. OpenFin can then launch either web or native components into a Chrome container injected with a number of APIs to provide services such as layout management capabilities, or interoperability with other applications over its proprietary messaging bus. For fintech companies such as Algomi, OpenFin offers direct download and update services via the cloud. All that a client of Algomi ALFA has to do to get access from a technical perspective is provide their own hardware via an approved cloud provider, and download an appropriate OpenFin runtime. (OpenFin)
Algomi has built ALFA in such a way that it is extremely easy to integrate with other applications that its clients may use. Firstly, it is interoperable over OpenFin’s messaging bus, and leverages the industry standards for interoperability currently being established by Finos’s Financial Desktop Connectivity and Collaboration Consortium (FDC3) so that it is able to pass context and share data with any other application doing the same. A few lines of code are all that is needed in order to open up an application to be able to interoperate with Algomi ALFA. Secondly, it has built an API that allows for users to access their aggregated real-time market data. Algomi ALFA converts data that exists in disparate formats into a JSON format using a highly performant normalizer. This normalized information is then pushed into a websocket server that can easily be consumed by a variety of programming languages, such as Python, Java, and Javascript, using an API. Similarly to the interop capability, this only requires a few lines of code to implement into other applications. (Algomi) (Finos)
Algomi ALFA sits within the electronic trading domain, which has long been subject to technological innovation. Over the past decade, electronic trading in fixed income has been growing at a steady pace, and has supplanted voice trading as the preferred method for execution in certain sub-asset classes, such as sovereign bonds. While the broad-brush categories of electronic trading and regulatory changes have driven the aforementioned changes in fixed income liquidity and market structure, there are several technologies and trends that have contributed to the rise of electronic trading itself; namely, cloud computing, advanced analytics, artificial intelligence, and process/service externalization. (Nagel, 2016) (Williams et al, 2016)
For the tech industry in general, cloud technology has massively lowered the barriers to entry for startups by lowering computing costs, reducing capital expenditures, and setup speeds, and increasing scalability and flexibility. Companies no longer have to build and maintain their own infrastructure to get off the ground, which reduces the amount that early stage investors have to contribute to each of their portfolio companies, and increases the number of companies these investors can deploy capital into. It’s for this reason that one of the primary issues Alliance Bernstein initially set out to solve with ALFA – the overabundance of trading applications in the market – exists. Algomi, like other startups, leverages cloud computing services from AWS, and leverages their partnership with OpenFin to reduce the time it takes to get set up with a client. (Williams et al, 2016)
As barriers to entry have lowered and more electronic trading platforms have entered the marketplace, increases in trading volume have upped the amount of trading data available, and opened the door for additional technologies to come into existence that are capable of leveraging massive amounts of data to inform better trading decisions. Advanced analytics based on the capture of human interaction with applications, such as behavioral analytics, predictive analytics, and sentiment analysis, have become standard in trading applications. Additionally, the ability to leverage these data and analytics using machine learning has led to the development of trading algorithms that have optimized trade execution both in terms of selection and placement. Algomi ALFA has been heavily involved with incorporating advancements in data analytics and machine learning functionality by offering better pre-trade insight into liquidity and sentiment, access to trading algorithms, and post-trade insight into best execution to meet regulatory requirements. (Williams et al, 2016)
As the number of services and solutions has increased, process and externalization has become a major trend in the electronic trading domain. As mentioned previously, there are now simply too many niche areas available for fintech companies to capitalize on - whether it is meeting a certain regulatory requirement, or specializing in a certain asset class - for traditional financial services firms, no matter how large their tech budget, to offer everything to everyone as they may have been able to in the past. Alliance Bernstein was aware of this when they sold ALFA to Algomi, and Algomi has been very shrewd in the development of ALFA to ensure that it is compatible with other technologies through interoperability and APIs, choosing to partner with other organizations rather than attempt to outcompete them. Algomi has also been smart in keeping its focus specifically on fixed income. Its top competitors are seen as large cross-asset OEMS providers such as Inforeach, FlexTrade, and Portware, but these companies’ lack of focus on a specific asset class mean that it is unlikely that they will be able to provide a solution as proficienct at Algomi ALFA in its slice of the market. (Williams et al, 2016)
Algomi ALFA has been highly successful in its rise as a one-stop-shop execution management system for fixed income trading. Although it has only been around for four years, and only under the ownership of Algomi, who truly started efforts to bring it to the center of the bond trading world, for two years, it has managed to capture 20-21% of the market, with hundreds of clients signed on, including high-profile accounts such as PIMCO. (Markets Media, 2019) Additionally, Algomi has been very smart in its approach of partnering with potential competitors to create a unique product that connects the services of several applications in the fixed income electronic trading domain together into a single user interface and API. It’s strategic partnership with OpenFin has also eased its distribution, and opened up channels for other applications to interoperate with it, increasing its stickiness as a platform.
Personally, I feel that Algomi ALFA is in quite an aspirational position, and that they are doing mostly everything right. I truly believe that their focus as an intermediary between multiple different trading services is what makes them such an indispensable tool. However, looking at the offerings of some of their potential “competitors”, one thing Algomi may want to consider is building out an order management system to create a complete fixed income OEMS package, as opposed to strictly just an execution management platform. Appending an OMS would allow portfolio managers to communicate their strategies to their traders with more fluidity, and tie into their portfolio management systems, without leaving the Algomi ecosystem. Algomi ALFA is built in such a way that it should be easily interoperable with third party OMS systems, but building one in-house that Algomi can include as part of its offering would likely create a smoother experience for the end-user.
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• “Algomi Eyes Next Round of Growth.” Markets Media, January 14, 2019. https://www.marketsmedia.com/algomi-eyes-next-round-of-growth/.
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“Alliance Bernstein Selects Algomi for ALFA.” Algomi. Accessed December 21, 2019. https://www.algomi.com/company-news/alliance-bernstein-selects-algomi-for-alfa.
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Kolchin, Katie, and Justyna Podziemska. “SIFMA Capital Markets Factbook 2019.” sifma.org. Accessed December 21, 2019. https://www.sifma.org/wp-content/uploads/2019/09/2019-Capital-Markets-Fact-Book-SIFMA.pdf.
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Nagel, Joachim. “Electronic Trading in Fixed Income Markets.” bis.org. Deutsche Bundesbank, January 2016. https://www.bis.org/publ/mktc07.pdf.
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Turner, Matt. “A $500 Billion Investor Developed 'Cutting Edge' Technology, and Now It's Sharing It with Rivals.” Business Insider. Business Insider, May 16, 2017. https://www.businessinsider.com/alliance-bernstein-alfa-system-algomi2017-5.
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