Skip to main content

Part 1 of 3

Since the installation of the first transatlantic undersea cable, trading technology providers were tasked with simple mandates:
  • Deliver information faster, from as many sources as possible and help investors and market operators to make better decisions and implement them quickly.
Fast forward to 2020 and the imperative for financial services firms of all ilk has moved away from just raw speed and toward the systematisation of trading decisions and the industrialisation of their implementation. Moreover, banks are still engaged in a struggle to regain competitiveness and bring down the cost / income ratios of their trading businesses. Therefore, the drive for automation and for the optimal allocation of human capital to the most value-added tasks now extends to all phases of the trading and client lifecycles.
This imperative – borne out of mounting regulatory constraints in the wake of the financial crisis – created an opportunity for technology vendors to alter their approach to systems architecture such that expenditure on both trading desk personnel and corresponding technology resources can be constrained or unleashed at will. Herein, the belief is that trading systems must be designed to preserve the ability of human traders to manually intervene in the operations of complex, automated execution programs when they deem it necessary to do so on either a pre-trade or at-trade basis, and that there is no other more optimal arrangement of functional capability – but, there is.
In this series of articles – produced in partnership with Itiviti Group – capital markets consultancy GreySpark Partners explores the current dynamics of the long-running debate over the dominance of high-touch versus low-touch trading systems design, arguing that the distinction between the two types is no longer necessarily relevant from an end-user perspective.

The Need for Differentiation & Efficiency: Remaining Relevant in a Competitive and Capital-constrained Environment

The first challenge that trading businesses face when designing, for example, a cash equities order and execution management solution (OEMS) fit-for-purpose within a client-facing business environment is the need to industrialise trading processes to achieve better cost-income ratios. Approaching the challenge from this perspective allows both systems designers and end-users to directly focus on the three levers that can be adjusted in relation to one another to lower the cost of production associated with a single executed order ticket or transaction.

Trading systems providing advanced analytics as well as optimal access to liquidity enable trading firms to significantly improve their performance through the management of three levers:

  1. Personnel – Sophisticated, client-facing trading solutions aid in the management of trading desk explicit costs by providing sales-trading personnel with the tools required to provide end-investor clients with the means to self-direct the ways in which they access the markets liquidity needed to execute axes or fill more complex orders.
  2. Systems – Sophisticated, client-facing trading solutions allow for the maximisation of the on-going, implicit costs associated with complex in-house systems maintenance by creating a layer through which the complexity disappears in the eyes of the end-investor client, who is then no longer required to navigate through it on their own or with the aid of support personnel.
  3. Automation – Sophisticated, client-facing trading solutions adapt to the changing needs over time of both the trading business and its end-investor clients through the use of progressively-updated automation toolkits that minimise manual interventions and that can be easily adjusted to meet the challenges associated with adding or subtracting access to markets liquidity and corresponding securities products and services.

Weighing the advantages and disadvantages associated with spooling one or more of the three cost control levers up or down can result in findings that can be used to lower the cost of trade production inputs on a per executed ticket basis. However, in doing so, financial services firms and their technology provider partners do not naturally succeed in producing an optimised end-investor experience as there is no direct connection between lower trade execution costs and higher-quality execution outcomes for the end-investor. Instead, firms are left able to mechanically produce higher traded volumes more efficiently, but not necessarily in a manner that is optimised for the specific needs of individual clients or for the needs of the trading business and its client base.

Herein, an opportunity to promote business efficiency emerges – specifically, the optimisation not just of the business’ production and execution costs per traded ticket, but also the optimisation of the outcomes on a per order / transaction basis for the firm and its clients equally. Once the fixed or variable costs associated with any one of the three levers are lowered or raised in concert with the other two, trading franchises can begin to examine their slate of customer-servicing activities in a more transparent light.

Specifically, trading businesses can then organically understand:

  • what roles their personnel actively perform for each segment of their assigned clientele, or for the client base, and the value-add or lack thereof that they bring;
  • what the objective or subjective outputs are that systems consistently generate for both the firm and its clients; and
  • how those two segments of the business, combined with their production inputs, can be further streamlined such that the same or better end-result output is produced for each client on each trade generated, and for the same fixed or variable cost.

Thus, a trading business’ base of total capital – that is, trading capital and allocated Capex investment – is stretched farther across a business environment in which its scarcity is a constant within a complex equation. In said equation, one side of the formula shows that a firm can support the same amount of traded volumes with less total capital – that is, revenue/capital or retail on trading capital – if:

  • the business takes less risk in the marketplace; or if
  • the business hedges its existing book of risk more efficiently, resulting in lower residual risk and less capital consumption.

Meanwhile, the other side of the formula shows that better outcomes can be produced with less budget if:

  • a firm invests a high proportion of its total capital in either financial engineering or in technology (see Figure 1).

For example, firms can build better trading systems that are both more efficient – that is, more productive – and that produce better outcomes that reduce frictions that naturally emerge between the point-of-sale of a product or service and the delivery of the product or service’s end-result.

Figure 1: The Four Varietals of Trading Business Front-office E-commerce Business & Trading Models

Source: GreySpark analysis

The Need for Agility: Reconfiguring the Business at Will

The second challenge that trading businesses face when designing client-facing OEMS is the need to maintain a flexible approach to either increasing or shrinking the depth and breadth of their operations at will by flexing up or down the number of trading desks active across multiple geographies and by rolling in or out of different types of products markets at will. Herein, reconfiguring the business at will is about focusing not on the quality of service provided to the clients, but rather on the quantity of business that can be done with them at any given time.

Taking, for example, two products manufacturing models – namely, the Craftsman’s Workshop and the Factory – and superimposing them over a trading business model:

  • In the Craftsman’s Workshop Model – If the initial fixed costs for the trading business are low, then the marginal costs are high; whereas
  • In the Factory Model – The initial capital outlay to build the trading business is high, but once it is expended, then producing yet another traded ticket or unit of production is an incremental expense.

However, neither model is ultimately desirable for trading businesses seeking to remain both efficient and agile when it comes to total capital outlay because the initial set-up of the technology systems underlying the client-facing OEMS must be done as cheaply as possible, but with a fixed cost nonetheless. As such, what trading businesses are ultimately seeking is elasticity. Specifically, for a trading business this means the ability to scale-up production capacity for as long as is needed relative to the initial cost, and – when high production capacity levels are no longer required – the ability to cut or reduce them incrementally (see Figure 2).

Figure 2: The Three Manufacturing Models

Source: GreySpark analysis

Leveraging elastic infrastructure through expenditure on cloud computing resources, for example, allows a trading business to achieve scalability in terms of its ability to increase the number of end-investor clients its serves while simultaneously growing traded volumes without the burden of linear cost increases or the degradation that comes from reductions in the overall quality of client service. In effect, marginal cost increases the minute that the business scales up, and it then decreases the minute that the business decides to scale down.

Ultimately, trading businesses must prioritise the ability to remain agile from a total capital utilisation perspective because the future is always uncertain. For example:

  • new waves of regulation or re-regulation in the wake of a financial crisis can result in the structural reform of a financial market for a specific asset class that then cascades into markets for other instruments or products on either a regional or global basis; likewise
  • if regulatory agencies increase their external scrutiny two-fold of the trading practices of asset managers or investment banks, then those firms or institutions must implement four- or five-fold higher standards internally in the enforcement of compliance and risk management best practices.

And if a trading business expands out the scope of its reach into new markets for instruments or products, thus garnering new end-investor clients along the way, then the demands of the client base in total become more complex.

The Need for Velocity: Unshackling Change

The final challenge that trading businesses face when designing client-facing OEMS is the need to unshackle a firm’s operations from the tedium of the bureaucracy associated with the implementation of incremental change. Dramatic step changes in technology innovation are historically few and far between and, more commonly, change is drip-fed such that innovation is an evolutionary process. However, since 2008, dramatic shifts rooted in the adoption of cross-enterprise DevOps approaches to IT management in the cloud allow application development teams to take advantage of elastic approaches to infrastructure management to facilitate the continuous testing, delivery and integration of new systems and, thus, quicker adoption of innovation where it is accessible and financially achievable.

Nimbler business process re-engineering can result in benefits that fundamentally transform a trading firm’s ability to streamline their scope of operations. The automation and flexibility that DevOps provides is invaluable in helping financial services firms position themselves competitively, but trading businesses must also continuously and actively assess how DevOps processes can be integrated into their scope of operations, and how different yet complementary technological processes can work together to deliver more business value. Cloud technology, open source software and microservices provide far-reaching benefits within a DevOps framework, and when used in conjunction with the DevOps toolchain, can transform operations holistically.

Therein, achieving a high degree of systems functional capability through careful selection processes – that is: buy; build; or buy and build – and acquiring a complementary level of in-house technical expertise in enterprise cloud management or in platform design ultimately speeds the time-to-market associated with the elastic scaling up of the business’ reach into new markets and the prospective clients that they contain. Getting from Point A (initial cost outlay) to Point B (higher volumes), however, can be a gargantuan effort because it requires capital markets trading businesses to interweave teams, processes and technology to create a culture that will allow enterprise DevOps in the cloud to bed-in.

The long-term benefit, though, is the creation of a mechanical capability within the whole of the trading business to either pay down or write-off completely the burden of so-called technical debt – that is, the inferior aspects of enterprise architecture, systems architecture, data and software environments that originate as part of the natural course of a product’s evolution. In 2020, the build-up of technology debt within a business’ systems and automation capital outlays still frequently emerges when a series of tactical bolt-ons, or hacks, are made to existing software platforms, the failings of which are then exacerbated by the inability of regulators to articulate complete, unambiguous, quantitative, verifiable requirements with sufficient advancement. Repayment of technical debt is always seen as being done in lieu of more important business functionality – something that is generally anathema to stakeholders who are unaware that it exists in the first place.

Figure 3: The Accelerated Creation of Technology Debt

Source: GreySpark analysis