At some point in the future, one person will do the job of our entire desk...”

Most sell-side traders and salespeople agree: In the future a lone zen-like super trader will sit in a calm space as they monitor and optimize the algo machine which in turn furiously prices, hedges and axes with flawless efficiency. Only occasionally will they have to intervene on a fiendishly complex transaction.

And maybe that same person will also watch over the sales robot as it simultaneously spouts charming small talk with 600 clients on chat while fielding 5,000 inbound requests a day.

However, today's trader desktop experience couldn't be further away from this.

“Right now we're still in a world of angry popups competing for attention on top of wall-to-wall data grids. My traders are trading in the dark"

Six screens filled with endless spreadsheets and legacy applications. Data is everywhere, but most of the intelligence still occurs in the trader's brain rather than the systems they use.

75% of traders we interviewed said they are forced to make uninformed pricing and hedging decisions.

So how do we bring salespeople and traders out of the dark? How will their systems evolve over the next 5 years?

Based on research with more than 200 salespeople, traders and business heads in Tier-1 sell side banks, here's our top ten features of the future.

Traders and Salespeople will no longer have to spend a few seconds working out (or worse; guessing ) whether an RFQ is a good fit for the bank - something which the existing algos are able to identify easily.

Adding a flag to each RFQ and auto-adjusting the start price allows traders to jump straight to 'how should i price this?' rather than 'do i want it?'.

This flag can also be used to segregate hit rate analysis into 'good fit' RFQs vs 'bad fit' RFQs.

Using historical RFQ analysis to identify the likelihood of winning an RFQ for a given price will allow traders to nudge the win % up / down, rather than tweaking the price itself.

The starting price will be a factor of the win %, and estimated P&L, based on whether the RFQ is a good fit or not - cutting out the need for trial and error pricing from the trader.

The current divide between 'normal' traders and 'algo traders' will disappear. Traders will be responsible both for manual intervention on voice trades and optimising the parameters of the algos in their area.

Their systems will help by prompting them to adjust the weighting of algo parameters based on analysing the its impact and the outcome of the RFQ at a sector by sector, product by product level.

"We won’t need to go looking for the risk issues - they’ll be brought to us"

Instead of presenting appendixes of risk data, risk systems will identify emerging hot topics, which could be sector, issuer or specific trade.

They will present news-style stories to traders, including pinned datapoints and a concise assessment of the situation.

Traders can then address the emerging risk by hedging or axing, and then enhance the story with their insight and publish for wider consumption.

In this way, traders spend less time scouring the data universe for issues and more time thinking about how to resolve them.

Traders won't have to guess whether to hedge a large transaction - or what the most cost effective heading strategy is. Instead, they will be in charge of defining the business rules and risk thresholds which govern the automatic hedging logic.

Sophisticated product correlation matrices and ongoing assessment of prices will minimise hedging costs while staying within the defined risk tolerances.

Market makers will be assisted by smart systems that automatically add instruments to their axe lists based on live risk positions of the desk (or wider organisation) and current price trends in the market.

Traders will define the strategies to determine when to hedge and when to axe.

Communication between different desks will be aided by automatically generated daily reviews covering the highlights across P&L, hit rates, risk hot topics and market insight.

Drafted by AI and then curated by desk heads, the concise summaries will ensure different desks work better together.

For example if the Emerging Markets desk flags a market trend concerning Egypt bonds, this flag could appear on Egypt-related RFQs for all traders on the floor.

Sales teams will be able to maintain dialogue with their vast client base by sparking micro-interactions with clients through automated chat messages sent at regular intervals.

Conversations will be based on the personal, trade and market information held in CRM and designed to generate engagement and more business.

Salespeople and traders will be able to perform any task in a few keystrokes using a smart command line prompt.

Open a Vol chart, execute a trade, open a risk grid displaying CS01 by tenor and industry sector for EMEA.

The prompt will recognise natural language and shorthand, and will learn as it goes ensuring that users can navigate their systems as fast as they can think.

Sales and traders will be able to instantly see news and analytics data for the context they are currently investigating (be it the instrument they're pricing right now, or a new risk crisis in the energy sector).

Most banks have now managed to hook up their internal applications to share context, but by extending this to third party providers like Bloomberg, they will be in total control over their whole desktop.


So what have we missed?

Or is your organisation already doing all of these things?

We'd love to know your views.


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