Derivatives sales 2.0: banks explore big data
Pressured banks hope new tools and technical nous will give their sales teams an edge
Need to know
- With staff costs under the microscope, banks want their derivatives sales teams to run more cheaply and effectively – Citi, Goldman, HSBC and others are exploring new technology.
- Dealers are looking not only to make better use of public and private data for performance measurement, but to get a better picture of client interests.
- Some are also looking to apply artificial intelligence to predict a client’s needs and marry them up with internal axes.
- “Sales in the past was capable of managing a relationship. Tomorrow it will be a technological war,” says Societe Generale’s Albert Loo.
- Some are looking to focus senior sales resources on the largest and most profitable clients, with smaller firms getting a lower-touch, electronic-focused service.
- Salespeople will also need more technical skills. “It is now the salesperson’s responsibility to be proactive and engaged,” says Nomura’s Wissam Farah.
It’s not hard to guess how clients will be affected as bank market-making businesses continue cutting costs – reduced access to sales staff, coupled with greater reliance on trading platforms and other electronic tools. What’s less easy to predict is the impact next-generation technology could have on the way banks serve their customers.
“If you look at how technology has transformed other service industries in the past five years, the capital markets industry in general has been very behind. Banks are just waking up to this opportunity, and realising it can deliver an improvement in profitability in the long term,” says Craig Butterworth, global head of the client ecosystems project at Nomura in London.
It is still early days, but banks have begun exploring this territory. Over the past 18 months, projects at Citi, Goldman Sachs, HSBC, Nomura, Societe Generale Corporate & Investment Banking (SG CIB) and others have focused on giving salespeople more complete, up-to-the-minute information on what clients have been doing; more ambitiously, some dealers believe machine-learning software will soon be able to anticipate client needs.
Other technology attempts to give the sales team a better handle on the banks’ own positions – or even to make this visible to the client, essentially allowing customers to browse through a dealer’s inventory.
The aim – of course – is to run sales more cheaply, but also to make it more effective. That has implications for the way a sales team works, and also for the kind of skills it needs.
“Sales in the past was capable of managing a relationship. Tomorrow it will be a technological war in terms of digital,” says Albert Loo, global head of fixed income, currencies and cross-asset sales at SG CIB in Paris. “The difference will be the environment you have around you, the engineering capabilities, the IT, quants and so on. The battlefield will be completely different tomorrow compared to in the past.”
The foundation for all of this is a better understanding of the resources clients currently use, and more rigour in the way those resources are deployed.
At one US dealer, analysis of sales time allocated to clients via Bloomberg chat, phone calls, meetings and written emails found roughly half the bank’s derivatives sales resources were being spent on the top 200 of around 5,000 clients. That might be roughly the right split, says one of the bank’s top fixed-income salespeople, but he adds these clients are not always given the right amount of attention. This has led some dealers to look at restructuring flow teams along wallet lines.
In general, this means a platinum client, or a medium-sized client with high margins, would have experienced, asset class-specific salespeople at their beck and call. They would be free to trade via phone or screen, and have access to traders for pricing enquiries on larger risk transfers or to discuss detailed trade ideas or research.
The bigger tranche of smaller clients would be pushed toward electronic execution. This would see them served by younger, tech-savvy, cross-asset salespeople concentrating on ensuring the bank is being asked to quote by client groups where it aims to be competitive. Other banks see this low-touch sales role including some general market comment and trade ideas, and some cross-selling of the bank’s own post-trade services.
“When you go to the smaller clients, and look at how you service them properly, ultimately they’re going to have to have less touch with a salesperson as we just can’t afford to run that model for much longer,” says a senior salesperson at one US bank.
Big data analytics
Both of these sales teams should end up having better tools at their disposal through a more thorough use of big data analytics. Banks have access to reams of data that traditionally has not been put to use – for instance, data on trade enquiries is often discarded, while voice and electronically executed inquiries are also rarely married up.
Some banks – such as Goldman – have already started making use of this data, allowing salespeople to check their client performance analytics in a form that is accessible, instead of having to request the data via specialised IT staff.
Speaking to Risk.net in January, Goldman’s head of interest rates product sales, Paula Madoff, explained the benefits: “Every time you wanted to run your hit ratios or evaluate how you’re doing with a client, we’d have to call someone else, who would download the data, and it was cumbersome. Now salespeople have QlikView dashboards where it’s very easy to pivot the data themselves in real-time.”
Many are looking to dig further, mining public data sources as well as private ones to get a better sense of a client’s behaviour and anticipate its needs.
“It’s not a luxury, it is vital. If we don’t do that, we risk being marginalised,” says Marwan Dagher, head of institutional sales for Europe, the Middle East and Africa (Emea) at HSBC in London. “The old-school style of memory as a salesman’s most important attribute is so outdated. You can’t compete if you don’t have at the very least a very good client relationship management system, and are using all the data in your possession to see how you are doing and to understand the client’s behaviour.”
The potential data pool is large. Banks are taking different approaches, but most are broadly looking to tap public data like trade repositories, news reports and regulatory filings, while also taking into account the research a client has read – and how much time they spent reading it. Advocates of the technology claim putting this information alongside performance metrics, balance sheet usage, the client’s current live portfolio and their peers’ trades – subject to data-protection controls – can help salespeople understand clients at a granular level in real-time, at scale, at near-zero marginal cost.
So, for example, instead of covering all hedge funds in the same way, this would allow a salesperson to cover hedge fund risk-takers idiosyncratically, even within the same firm. And when the salesperson receives a call, new technologies can read the phone number and put personalised information up on screen instantly.
If you’re a salesperson, it allows you to strip out the noise, and for technology to deliver personalised insights so you have clear calls to action and can make the right call at the right time
Craig Butterworth, Nomura
“If you’re a salesperson, it allows you to strip out the noise, and for technology to deliver personalised insights so you have clear calls to action and can make the right call at the right time,” says Nomura’s Butterworth.
While some clients have concerns about data protection, Conor Davis, Emea head of investor sales for markets and securities services at Citi in London says tight controls can be put in place to limit who can access a buy-side firm’s trade history internally. “Trust between the bank and its clients is key, so you need to carefully manage the information flow to ensure it is used for the client’s benefit,” he says.
Some banks are also looking to take the data approach further, linking the sales system up with axe-monitoring fintech services like Neptune. The latter, an open-source industry collaboration involving multiple dealers, allows banks to access their current inventories in real time. This means a salesperson can see what instruments they’re axed on at any one time, and can even show them to selected buy-side traders, along with prices.
Its focus so far has been on cash bonds, like Algomi’s Honeycomb product, but according to Neptune’s interim chief executive officer, Grant Wilson, it can just as easily handle derivatives inventories. He says three banks are currently coding towards the platform to start showing credit default swap inventories.
Predicting behaviour
The end game is to marry this up with machine learning and artificial intelligence (AI), so a sales system can predict the trades a client may need given their portfolio, the bank’s axes and behavioural characteristics. Banks already have systems in place to suggest when a client might want to take profit from a position, for instance, but are taking it a step further.
“To give you an example, a particular individual might read lots of research on Trump and oil prices, and the impact on breakevens. The system could identify this, and that they went short breakeven inflation six months ago and are now 50bp underwater, and that we’re axed to offer those same bonds that the client is short. The system would then pop up to the salesperson for that client and say ‘You might want to pick up a phone to have a conversation’,” says Nomura’s Butterworth.
Clients broadly support these initiatives, though some still doubt AI can be sophisticated enough to take into account restrictions such as hedge accounting. A trader at one European pension fund says his email inbox is often flooded with mostly useless research and trade ideas from the fund’s 50 derivatives counterparties, and welcomes anything to cut that back.
“You talk to three or four people that know the company – people who might say: ‘Did you see this trade, I think that will fit for you, we’ve done this analysis and know you will be interested in knowing more about it’,” he says.
Derivatives valuation adjustments (XVAs), credit support annexes (CSAs), execution and clearing preferences have also emerged as strong influences on pricing in recent years, and the onset of the market’s new margining rules for non-cleared trades will require funding costs to be taken into account when pricing new trades.
While the best salespeople are already up to speed with the latest developments, banks say that, particularly for interest rate swaps, staff will need to be fully up to speed not only with the way these effects are priced into trades, but how trades affect credit lines, balance sheet capacity, interdealer and clearing house initial margin requirements, as well as capital requirements.
Wissam Farah, head of Emea sales for global markets at Nomura in London, says the salesperson is effectively becoming a risk manager. They will need to be in discussions with clients about collateral posting rights in CSAs, proactively manage existing portfolios to make sure leverage and XVA exposures are limited where possible, or attend internal discussions about how to price wrong-way risk in emerging markets, as all these things affect the price the bank can offer.
“It is now the salesperson’s responsibility to be proactive and engaged. In fact, the salespeople who are proactive in terms of helping trading manage risk and manage costs and helping the credit valuation adjustment teams are the most successful, because they end up resolving the issues faster, getting the best prices to the clients sooner and getting the market share,” he says.
Some also note the most successful salespeople are usually the ones with the quickest and most technical understanding of pricing dynamics and who are able to price their own plain-vanilla derivatives, whether on their own systems or via the bank’s externally available pricing tool.
“There’s really not much room on a trading floor for someone who can’t utilise an Excel-based pricing tool, or play with variations and adjust a bespoke price for a specific client requirement, whether a swap or a simple option,” says Nomura’s Farah.
“In addition to the salesperson’s ability to understand the client requirements, their technical, financial mathematical understanding of pricing dynamics of a swap or any type of derivative is becoming a relevant benchmark for assessing the skills of a salesperson,” he adds.
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