Algomi

Matchmaking Model






Algomi

Algomi represents an exemplar “matchmaking” business model in the financial services sector, specifically catering to buyers and sellers in bond markets, and the exchanges on which they trade. Algomi’s algorithms provide bond matching technology that enables secure and discreet dealer-to-dealer transactions, and provide access to information to buyers and sellers that improves liquidity in the bond market. By linking the exchange, banks and investors, Algomi’s technology transforms exchanges into centralized marketplaces for bond trading.

HISTORY

Algomi – which comes from Algorithms for Market Intelligence – was launched in June 2012 by Stu Taylor (Former Global Head of Matched Principal Trading and creator of PIN-FI at UBS), Usman Khan and Robert Howes (Founders of CAPXD), and Michael Schmidt (Former Head of European Credit Trading and IB Board Member at UBS). Algomi is backed by investment from Lakestar, and a panel of Strategic Advisors, and has grown to over 140 employees at the end of 2015. It currently has offices in London, New York and Hong Kong, with client support and sales in Chicago, San Francisco, and Boston. As of October 2015, the company had more than 120 buy-side firms and 11 banks – including HSBC, Deutsche Bank and Credit Suisse – using its technology, which it launched in 2014.

CUSTOMERS – WHO THEY ARE:

Algomi serves the buy-side and sell-side of bond markets, as well as the exchanges on which bond trading occurs. Algomi’s clients – hedge funds, asset management firms, pension fund managers, sovereign wealth funds, and endowments, among others – hail from New York, London, and Hong Kong.

ENGAGEMENT – VALUE CREATION PROPOSITION:

In a nutshell, Algomi has developed a suite of technology products that facilitate trading in bond markets, where a lack of liquidity has become a serious problem for buyers, sellers, and the exchanges themselves. Behind its technology are three main algorithms that serve buyers and sellers of bonds, and bond trading exchanges. For buyers, a matching algorithm called Synchronicity will find suitable bonds based on the buyers’ inquiries, similar to how Amazon shows similar products in search results. The buyers’ inquiries are made securely and discreetly within Algomi’s network. In addition, Algomi has developed a calibration algorithm that helps connect the group of people needed to complete the trade, within what Algomi calls its Honeycomb network. As Usman Khan, co-founder and CTO of Algomi said in a recent interview with FusionWire, “If a salesperson in another part of the bank previously missed a trade, or entered an enquiry on a similar bond, they’re pulled into that group.” In this way, Algomi’s calibration algorithm helps traders connect with the right people – buyers to potential sellers, and sellers to potential buyers – to facilitate the trade. Finally, Algomi has developed a prioritising algorithm that helps sales people sift through large amounts of data on different bonds, helping them make decisions about which bonds to trade – by locating liquidity – by prioritizing the data for them. Khan, in his interview with FusionWire, explains: “So what is it that helps traders identify opportunities across the myriad of systems they have access to? Information. Who holds the bond? Where is it priced? When was it last traded? We realised this information can help people understand where liquidity resides.” As a recent article in Bloomberg explains, “Algomi harnesses data from banks so it can be searched by its buy-side clients using its Honeycomb network. Once given permission, an investor can click on debt he wants to buy or sell, and a heat map will appear on the screen. It may show, for example, that HSBC traded that bond a week ago or that Deutsche Bank currently has interest in the bond. Banks may share pre-trade data with their own customers to show them what’s available.”

This access to information is a key element of Algomi’s value proposition. Whereas previously bond traders would gather information about the market, or particular bonds, by speaking to each other on the phone – which kept the information invisible to the rest of the market – Algomi centralizes, makes accessible, and helps traders prioritize this information. In addition, by seeking information about a particular bond over the phone, other traders would know who was interested in which bonds, and the market could begin to move against individual traders seeking to buy or sell the bond about which they were inquiring. Algomi’s technology keeps traders’ inquiries secure, and centralizes all of them so that portfolio managers, for example, can get an overview of what’s potentially moving in the market or not.

The discreetness with which Algomi’s technology allows traders to inquire and access information about bonds is another key element to the company’s value proposition. The Honeycomb technology displays the investor’s portfolio and planned transactions visually, showing the investors any information shared with them from multiple sell side firms, without revealing their intentions until they are ready to open a communication channel. This reduces “information leakage” so that traders can place calls about sensitive trades in confidence. As a knock-on effect, this also reduces market noise associated with multi-dealer enquiries. Once the investor has revealed their inquiry to the chosen bank, the sales contact is notified internally as to exactly which other salespeople have clients who are most likely to be the other side of the trade, again reducing the number of potential leakage points surrounding a trade.

For compliance teams, Algomi’s Honeycomb technology offers full Order Management Systems integration and provides a detailed audit report recording price and liquidity discovery from the moment an enquiry is loaded. Every button click on the Honeycomb Network is tracked and pulled into a report that demonstrates the process undertaken by the buy-side trader, and the information they received that led them to their final decision around execution. This means a dealer is able to prove that a best execution process has been followed even on trades where this would normally be difficult to demonstrate.

Finally, for bond trading exchanges, Algomi’s technology has been shown to greatly increase liquidity, by identifying execution opportunities that existing markets cannot see, across all fixed income platforms. This adds valuable additional revenue flow for the Exchange.

DELIVERY – THE VALUE CHAIN:

To actually complete a trade, buyers and sellers connect either manually on electronic platforms or, for larger or more illiquid trades, on the telephone. The algorithms are developed in-house, and can be configured for each client to best represent the client’s strategies and business model in the bond market. Users of Algomi’s technology interface with it through their existing terminals, and the software runs on Java. The technology is integrated into clients’ existing IT infrastructure, including messaging, application servers, and databases.

MONETIZATION – VALUE CAPTURE:

Algomi charges its clients a fee to use the technology and join the Honeycomb network – it does not charge a trade-related fee or commission. The company does not disclose the fees that it charges for the use of its technology.

Sources:

Company Website: www.algomi.com

MarketsMedia Website: http://marketsmedia.com/buy-side-joins-algomis-honeycomb/

Business Insider: http://uk.businessinsider.com/algomi-cuts-10-of-global-workforce-2015-11

FusionWire: http://www.fusionwire.net/featured/algomi-from-startup-to-bond-market-standard/

Bloomberg: http://www.bloomberg.com/news/articles/2015-10-19/hsbc-joins-banks-sharing-bond-inventories-with-matchmaker-algomi

Disclaimer:

Written by Kandhasamy Muthu and edited by James Knuckles under the direction of Prof Charles Baden-Fuller, Cass Business School. This case is designed to illustrate a business model category. It leverages public sources and is written to further management understanding, and it is not meant to suggest individuals made either correct or incorrect decisions. © 2016

Published 20 April 2016



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