Implementation issues and solutions

Chapter two

In the past decade, sell-side institutions have been under great pressure to reduce costs and produce more with less in order to remain competitive.

As many firms play catch-up with agile and digital-focused fintech competitors, they must address skill gaps and the fears of their employees over the future of their roles after implementation of new technologies such as machine learning, artificial intelligence and cloud-based data management. In some cases, sell-side firms have had to rush through the implementation process, which has created additional operational challenges, with potential negative impacts on trading for their clients.

The fixed income market is catching up with the equities market as new technologies become available and implementation of them increases. Increasingly, it is important for sell-side firms to identify which areas of the trading process should be prioritized when implementing these technologies.

The human question is an important one, however. As the fixed income market continues to develop its use of automation technology, how will humans and machines co-exist on the trading floor?

This is particularly pertinent in the wake of the COVID-19 economic crisis, which has seen a number of banks reduce headcounts due to reduced profitability caused by the virus. Some have started to look at doing this in the near-to-medium term.

Much of this concern is warranted, but it may also be misplaced. Automation technology is designed to free up time for trader’s to focus more of their attention on high-value tasks. Once the sell side translates that to their workforce, there is likely to be less of a concern around threats to jobs and more of a focus on using automation to make headcounts more productive.

31% of survey respondents indicated dealer selection criteria and price contribution as the most important criteria and rules to consider when implementing a new automation strategy

What are the most important criteria and rules to apply when implementing a new automation strategy?

 

How can automation technology help with dealer selection criteria?

“A lot of the challenge here is trying to make sense out of dealer performance using historical and real time data. Clients are trying to understand which dealers have actually done a good job by them in a particular asset class over time. There’s a lot of data crunching and this is something computers are particularly good at.”

Ravi Sawhney, Head of Trading Automation & Analytics, Bloomberg

“There is a strong push from buy-side organizations to use data science to improve dealer selection by reducing human error. If the inquiry is sent to the wrong dealer, at best you’re not going to get the trade done, and at worst you’re leaking information about what you’re doing, which could affect your price.”

Dan Tsou, Head of ETOMS, Bloomberg

Our respondents answered that they thought RFQ Response/Auto Quote, IB/Voice RFQ Response/Auto Quote were some the market making workflows that are better suited for automation today

Which market-making workflow do you think is better suited for automation today?

 

Why do you think RFQs ranked so highly with respondents here?

“RFQ is either the first or the second step in the price discovery or trading process, so automation there benefits everyone. The IB (IB is Bloomberg Terminal’s Instant Messaging Tool) voice automation interest is a global trend and has been a technical challenge. But using AI to detect an inquiry and recognizing financial instruments with Bloomberg’s financial vocabulary is a game changer. That and the fact that we have the dominant financial trading chat platform puts us in a unique position to do something powerful for our clients.”

Dan Tsou, Head of ETOMS, Bloomberg

“RFQ is the most commonly used workflow for OTC trading electronically. It’s also the most prescriptive, so lends itself to being automated. Many buy-side firms have their best execution policies written down and these can effectively be ‘codified’ into a rule and automated.”

Ravi Sawhney, Head of Trading Automation & Analytics, Bloomberg

29% of our respondents said that managing the human angle was the biggest challenge faced by their organizations when implementing new automation technology

What is the biggest challenge your organization has faced during the implementation stage of new automated trading technology?

 

How can fixed income sell-side firms overcome this and other challenges when implementing new automation trading technology?

“There’s merit to the perceived threat, but it’s more smoke than fire. When automation infringes on human tasks it can certainly be intimidating, but a machine’s not going to help you choose products, or make better use of your balance sheet, or enhance your ability to serve clients. Firms can overcome negative perceptions by making sure they have the right messaging and vision on how automation will be used to help traders, not replace them.”

Dan Tsou, Head of ETOMS, Bloomberg