Case Study: How Interoperability Brings Automation to Bond Trading
FIX/API Interoperability: Bringing Automated Trading To Complex Dealer Desk Technology
Source: Overbond
Why is trading technology interoperability so important?
Overbond COBI-Pricing LIVE gives desks the ability to fully automate 30 percent of their RFQs and execute an additional 20 percent with trader supervision. This is possible because of three factors: AI models such as COBI-Pricing LIVE that can price fixed income securities and score their liquidity; speed from cloud computing; and protocols that allow for data aggregation and increased interoperability of the systems used in trading workflows.
Interoperability is the ability of different systems or programs to communicate with each other, exchange information, and use that information. It is particularly important for bringing automated trading to the sell-side and buy-side desks because these desks traditionally have five to 10 pre-existing systems necessary to conduct trading. Automating trading workflow is possible because COBI-Pricing Live is fully interoperable with the existing technologies on the desk.
COBI-Pricing LIVE interoperability
COBI-Pricing LIVE now offers protocol and system agnostic integration with venues and e-trading systems used by sell-side and buy-side trading desks through RA Platform 3.0, an open API enterprise software platform from Rapid Addition, a provider of electronic trading middleware.
Rapid Addition’s expertise in FIX protocol, counterparty, and market-place connectivity via its open API enterprise software platform will allow global fixed income trading desks to seamlessly integrate AI-driven bond pricing and liquidity scoring analytics into their workflow, regardless of which internal OMS, e-trading system, direct venue connectivity, cloud or on-premise solution they currently use. These API connections allow for internal system integration, pre-and post-trade external data vendor ingestion, and liquidity venue connectivity — ultimately creating a streamlined system capable of automating RFQ flow using Overbond’s AI engine.
Overview of the Current Process
Technology has been enabling automation in equities for two decades. It’s now poised to enhance the bond market. Increases in fixed income electronic trading volumes have driven enhancements in trading desk operations over the previous five years, making the lives of traders easier in today’s natively digital world. This is now possible because of three factors: AI models such as COBI-Pricing LIVE that can price fixed income securities and score their liquidity; speed from cloud computing; and protocols that allow for data aggregation and increased interoperability of the systems used in trading workflows.
Challenges With Legacy Systems And Processes
When the RFQ is received by the trader via the Bloomberg (or other) terminal or a phone call, there could be several different methods of pricing the bond, below is an example of some of these options:
1. CBBT price taken from Bloomberg covering most of the cases
2. Fixed Yield quoted – for the special type of the security
3. Price Range quoted – a certain range is added
4. A certain spread range set – this might be quite wide
The decision on which of these methods should be used, or whether the CBBT (Bloomberg composite feed) price is good would have to be taken by the trader on a case-by-case basis. A loss of RFQ (as a sell-side market maker) may occur due to the manual and time-consuming nature of checking fixed yields and certain spread ranges. Comparing the bond that is mentioned in the RFQ, with a similar bond from a peer, would provide good insight into the likely price of the bond, however, this would also take time.
Drivers of the problem
The primary problem that the trader faces is due to the low confidence in prices suggested by Bloomberg CBBT and third-party applications that are currently used:
These factors lead to low confidence in the suggested prices and traders must constantly spend a great deal of time and effort in manually adjusting prices based on prior knowledge and intuition. The major trade-off is thus accuracy versus time, leading to missed deals and direct downward pressure on desk P&L. Clients value speed of execution. Interoperability between data feeds, internal systems, and trading venues speeds the RFQ process by facilitating automated trading in near real-time.
Challenges With Data Aggregation
One of the first hurdles facing fixed income pricing AI is the lack of a centralized source of trade data. Data feeds from any single electronic provider don’t provide enough information for calculating prices and liquidity scores for illiquid securities. This problem is solved by aggregating data from multiple sources including vendor feeds, internal historical records and settlement-layer volume information for OTC trades from providers such as Euroclear. This data aggregation layer requires interoperability between multiple data feeds and real-time AI data mapping.
COBI-Pricing Data Intake
Successful data pre-processing is the key stage and pre-requisite for the COBI-Pricing algorithm operation. The precision of the algorithm output is critically dependent on the accuracy, timeliness, and relevance of the pre-processed input data. Overbond sources raw data from major data suppliers in the financial sector, including Refinitiv, Ice, The Six Group, EDI, MarketAxess, Tradeweb, Euroclear, Clearstream, DTCC, CDS, S&P Global Market Intelligence, major credit rating agencies, as well as other sources. The data COBI-Pricing algorithms use includes the following:
Case A - EUR sell-side credit trading desk
The diagram below and the following paragraphs provide a description of how the Overbond and RapidAddition(RA) venue connectivity works with desk using Valantic’s iQbonds bond trading platform:
Case B - GBP Dealing sell-side credit trading desk
The diagram below and the following paragraphs provide a description of how GBP sell-side credit trading desks use internally built OMS systems and can connect with Overbond & RA interoperability layer to achieve best execution:
Case C – USD Buy-side credit trading execution desk
The diagram below and the following paragraphs provide a description of the desk technology interoperability with client-side built data lake (client aggregated data lake) along side custom built OMS system.
Business Impact
Interoperability with electronic trading venues not only allows for the ability to trade on multiple platforms but also opens the door for smart order routing, allowing desks to optimize execution. Using Overbond’s COBI-Pricing LIVE gives desks the ability to fully automate 30 percent of their RFQs and execute an additional 20 percent with trader supervision. The precision of AI, the speed of cloud computing and the interoperability with trading desk systems are making automated trading a reality.
Specific use cases for the COBI-Pricing algorithm application are examined to identify business objectives and key benefits below. Overbond client organizations include sell-side institutions with significant trading volumes (200-2000 RFQs+ a day per trader). Their innovation groups actively explore new technologies that can serve as the catalyst for trading automation and improved risk management, trade flow, pre-trade and post-trade analytics.
Implementation Considerations
Institutions considering AI predictive analytics implementation and big-data transformation projects can employ acceleration utilizing externally calibrated models and market signals. Below are several key considerations and questions for executives in charge of AI roadmap:
Custom AI Services
Overbond works with clients to identify and recommend practical AI analytics use cases that are aligned with the strategic goals of the financial institution. We help assess current-state AI capabilities and define the roadmap to help clients realize value from AI applications. We manage cross-channel data flows across multiple systems and enable custom font-end visualizations.
Proven Methodology
With our targeted approach and implementation methodology, we quickly demonstrate value of AI analytics to test use cases, enabling client-side change management approach and stakeholder buy-in.
Operational Acceleration
We help clients build and deploy custom AI solutions to deliver proprietary analytics and tangible business outcomes. Our experience combines calibrated models, design patterns, engineering, and data science best practices, that accelerate value and reduce implementation risk.
AI Analytics As-a-Service
Overbond helps customers design and oversee mechanisms to optimize and improve existing fixed income credit valuation, issuance and pricing prediction and pre-trade opportunity monitoring using AI. Our team of world-class data scientists and engineers manage an iterative implementation approach from current state assessment to operational handover.
About Overbond
Overbond specializes in custom AI analytics development for clients implementing trade automation workflows, risk management, portfolio modeling and quantitative finance applications. Overbond supports financial institutions in the AI model development, implementation and validation stages as well as ongoing maintenance.
Contact:
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Chief Executive Officer
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