How Do Systematic Internalisers Retain a Competitive Edge after the Tick Size Harmonization?

Concept

The harmonization of tick sizes under the Markets in Financial Instruments Directive II (MiFID II) was a deliberate architectural intervention designed to recalibrate the European equity market structure. Its core purpose was to establish a level playing field between incumbent public exchanges and the ascendant class of Systematic Internalisers (SIs). For an extended period, the operational model of an SI was predicated on a simple yet powerful structural advantage ▴ the ability to quote prices at increments finer than those permitted on lit venues. This capacity for sub-tick price improvement allowed SIs to become a default destination for retail and institutional order flow, capturing volume by offering a mathematically marginal, yet consistently better, price.

When regulation mandated that SIs adhere to the same minimum tick size as exchanges, it appeared to neutralize their primary weapon. The system was, in effect, re-architected to remove a key variable.

Understanding how Systematic Internalisers retain a competitive edge in this post-harmonization environment requires a shift in perspective. One must look beyond the dimension of price alone and analyze the multi-faceted nature of execution quality. The competitive landscape transformed from a simple contest on price to a complex interplay of risk management, technological sophistication, and the mitigation of information leakage. An SI’s value proposition was compelled to evolve.

It now centers on its function as a private liquidity mechanism, a bilateral risk counterparty that offers certainty of execution and minimizes the market impact costs associated with transacting on a transparent central limit order book. The harmonization did not eliminate the SI model; it forced it to mature, compelling these entities to compete on the more sophisticated metrics that define institutional execution quality.

The Pre-Harmonization SI Architecture

Before the mandate, the SI operating model was a clear example of regulatory arbitrage creating a distinct competitive niche. An SI, which is an investment firm dealing on its own account by executing client orders outside a regulated market or multilateral trading facility (MTF), could internalize order flow efficiently. Their ability to quote in sub-tick increments meant they could systematically offer a price that was, for instance, one-tenth of a cent better than the European Best Bid or Offer (EBBO). For a smart order router (SOR) governed by best execution obligations, the choice was algorithmically simple.

The SI was the logical and most efficient destination for a vast amount of marketable order flow. This created a significant flow of trades away from public exchanges.

This structure raised concerns among regulators and exchange operators about the health of public price discovery. If the most informed and aggressive orders are routed to lit markets while a large volume of less-informed flow is internalized by SIs, the quality and reliability of the public quote can degrade. The bid-ask spread on public venues might widen to compensate for the increased adverse selection, creating a feedback loop that makes SI internalization even more attractive. The tick size harmonization was the regulatory response to this dynamic, intended to redirect more order flow back to the lit markets where price formation occurs transparently.

The competitive focus for Systematic Internalisers shifted from marginal price improvement to a holistic offering of execution quality and risk mitigation.

What Is the Core Function of Tick Size Harmonization?

The primary function of the MiFID II tick size regime is to ensure the orderly functioning of markets. By standardizing the minimum price increment for a given security across all trading venues, it prevents a “race to the bottom” where venues compete by offering ever-finer pricing increments. While this might seem beneficial to investors, excessively small ticks can lead to “order book noise,” where market participants make negligible and frequent price improvements.

This increases the computational burden on market participants and can obscure the true state of supply and demand, thereby degrading the price formation process. Harmonization establishes a common quoting language, ensuring that a price step on one venue is meaningful and equivalent to a price step on another.

For Systematic Internalisers, the application of this regime meant their quotes had to align with the price ticks on the primary exchanges. They could no longer automatically step inside the spread by a fractional amount. Any price improvement they offered would have to be at a full tick increment, a much higher bar that requires taking on more risk.

This change fundamentally altered the economic calculation for SIs and forced a strategic re-evaluation of their business model. They could no longer rely on a simple, structural pricing advantage; they had to build a more resilient and multifaceted value proposition.

Strategy

In the wake of tick size harmonization, the strategic playbook for Systematic Internalisers underwent a necessary and profound transformation. The neutralization of sub-tick price improvement forced SIs to pivot from a volume-centric strategy based on a simple structural advantage to a more sophisticated, value-centric model. The new competitive arena is defined by factors that have always been important to institutional clients but are now paramount ▴ minimizing market impact, ensuring execution certainty for large orders, and controlling information leakage. SIs now compete by functioning as highly specialized risk absorption engines, leveraging technology, data, and curated liquidity pools to deliver superior execution outcomes that are measured in basis points saved on impact costs, rather than fractions of a penny on price.

Leveraging the Large-In-Scale Execution Niche

A primary strategic adaptation for SIs has been to focus on a segment of the market where the tick size constraint is less relevant ▴ Large-In-Scale (LIS) block trades. MiFID II provides exemptions for LIS transactions, recognizing that executing large orders on a lit order book presents unique challenges. Attempting to execute a block trade directly on an exchange can signal the trader’s intent to the entire market, leading to adverse price movements (market impact) as other participants trade ahead of the order. The value of an SI in this context is its ability to take the other side of the entire block trade, providing the client with a single execution price and absorbing the risk of holding that large position.

The client achieves certainty of execution and avoids the signaling risk of the public market. This service is of immense value, far outweighing any potential for marginal price improvement.

SIs engineer their systems to be specialist block trading counterparties. This involves sophisticated risk management systems to price and hedge large positions, as well as strong client relationships to source this type of flow. The competitive advantage is built on trust and the demonstrated ability to handle large, sensitive orders discreetly.

Table 1 ▴ LIS Execution Venue Comparison

Pivoting to Execution Quality and Data Analytics

The second pillar of the modern SI strategy is an intense focus on provable execution quality. With price improvement less of a differentiator, SIs must now compete by demonstrating that their execution method results in a better all-in cost for the client. This is achieved through a combination of superior technology and sophisticated data analysis, specifically Transaction Cost Analysis (TCA). An SI can provide detailed TCA reports to clients showing how an execution with them compared favorably to benchmarks like the Volume-Weighted Average Price (VWAP) or the arrival price.

The key metric they emphasize is implementation shortfall ▴ the difference between the price at which the decision to trade was made and the final execution price. By minimizing market impact, SIs can often deliver a better implementation shortfall, even if the nominal execution price is on the tick.

This requires significant investment in technology. SIs employ advanced quoting engines that ingest vast amounts of real-time market data, analyze their own risk positions, and model the potential impact of a trade. They use this intelligence to provide firm quotes that are competitive while managing their own risk. This data-driven approach allows them to price aggressively when their internal inventory or risk profile allows, creating opportunities for price improvement even within the harmonized tick regime.

By absorbing large blocks of risk privately, SIs provide a critical service in mitigating the market impact costs inherent to transparent, lit venues.

How Does Curated Liquidity Create an Advantage?

A core, yet often overlooked, strategy is the cultivation of a specific liquidity ecosystem. An SI is not a public utility; it is a private trading environment. This allows the SI to be selective about the clients it interacts with and the type of order flow it internalizes. By focusing on, for example, institutional asset managers and avoiding certain types of high-frequency trading flow, an SI can create a less “toxic” trading environment.

Toxicity, in this context, refers to the probability that the counterparty to a trade has superior short-term information, leading to losses for the liquidity provider (adverse selection). By curating its flow, an SI can reduce its adverse selection risk. This lower risk profile translates directly into a competitive advantage ▴ the SI can offer tighter, more consistent pricing to its desired client base because its expected losses from informed trading are lower. This creates a virtuous cycle, attracting more of the desired flow and further strengthening the ecosystem.

The Power of Bundled Services

Finally, it is crucial to recognize that many SIs are not standalone entities. They are typically part of large investment banks that offer a wide array of services to institutional clients. This provides a powerful competitive moat. A client’s decision to route order flow to a particular SI may be influenced by the broader relationship with the bank, which could include access to equity research, capital markets advisory, prime brokerage services, and bespoke financial products.

The execution service becomes one component of a bundled offering. In this model, the SI’s competitiveness is a function of the entire firm’s value proposition. An independent trading venue cannot compete on this dimension, allowing the bank-led SI to retain sticky, valuable order flow even in the absence of a structural pricing advantage.

Execution

The execution framework for a post-harmonization Systematic Internaliser is a masterclass in technological precision and quantitative risk management. The abstract strategies of focusing on execution quality and LIS trades are brought to life through a highly engineered operational and technological architecture. Success is a function of integrating disparate systems ▴ from client-facing order management systems to internal risk and quoting engines ▴ into a single, coherent machine designed to price and absorb risk with maximum efficiency. The execution layer is where the theoretical competitive advantages are forged into tangible, measurable outcomes for clients and the firm.

The Operational Playbook

Adapting an SI’s operational model to the harmonized tick environment requires a deliberate, multi-stage process. It involves recalibrating every system that touches an order, from intake to post-trade analysis, to reflect the new competitive reality.

1. Smart Order Router (SOR) Re-Engineering Objective ▴ The SOR’s logic must be updated to de-prioritize sub-tick price improvement as the sole factor for routing.
   Execution Steps ▴
   – The SOR must incorporate a more sophisticated best execution model that weighs factors like the probability of fill, potential market impact, and venue toxicity alongside the quoted price.
   – It needs to be able to dynamically identify LIS-eligible orders and route them to a dedicated internal workflow instead of slicing them up for execution on lit markets.
   – Latency to market data feeds and the speed of the decision-making engine become critical to ensure the SI’s own quotes are based on the most current state of the market.
2. Developing a Specialized LIS Execution Desk Objective ▴ To build a dedicated pathway for handling large block trades that leverages the SI’s ability to commit capital.
   Execution Steps ▴
   – This involves both technology and human expertise. The desk needs traders skilled in pricing large, illiquid positions and managing the subsequent inventory risk.
   – The desk must be equipped with pre-trade analytics tools to estimate the market impact of executing the block on a lit venue, providing a quantitative justification for the price offered to the client.
   – A robust risk management system is required to provide the desk with real-time views of the firm’s overall exposure and inventory, allowing them to price blocks aggressively when the trade reduces the firm’s overall risk.
3. Implementing Advanced Transaction Cost Analysis (TCA) Objective ▴ To create a data-driven feedback loop that proves the value of the SI’s execution quality to clients.
   Execution Steps ▴
   – The SI must capture high-precision timestamps for every stage of an order’s lifecycle, from receipt to execution.
   – Post-trade TCA reports must be generated that go beyond simple VWAP comparisons. They should include metrics like implementation shortfall, price reversion (a measure of market impact), and spread capture.
   – This data should be presented to clients to demonstrate the “hidden savings” of executing with the SI, such as the avoidance of adverse selection and market impact.

Quantitative Modeling and Data Analysis

The core of an SI’s execution capability lies in its ability to model risk and cost. TCA is the primary tool for demonstrating this value. The following table presents a hypothetical TCA comparison for the execution of a 200,000 share order in a stock, comparing an execution via an SI to an algorithmic execution (e.g. a VWAP schedule) on lit markets.

Table 2 ▴ Hypothetical Transaction Cost Analysis

Effective TCA reporting transforms the conversation from the nominal execution price to the total economic cost of a trade.

Predictive Scenario Analysis

Consider a portfolio manager at an asset management firm who needs to sell a 500,000 share position in a mid-cap European stock. This position represents 75% of the stock’s average daily volume. The manager’s primary objective is to exit the position with minimal price disruption. The arrival price is €50.25.

The manager considers two execution pathways. The first is to use their firm’s VWAP algorithm on the lit markets. The pre-trade analytics predict that executing this size over the course of a day will push the price down by an estimated 30 basis points, resulting in a significant implementation shortfall. The signaling risk is high, and there is a chance the full order will not be completed if liquidity dries up.

The second pathway is to contact the LIS desk at a trusted SI. The SI’s trader, using their firm’s quoting engine and risk system, analyzes the request. The engine notes that the firm is currently short 100,000 shares of the same stock for another client, meaning this trade would help them flatten their book. Factoring in the stock’s volatility, the cost of hedging the remaining position, and the benefit of internalizing the risk, the trader offers to buy the entire 500,000 share block at €50.21.

This price is four cents, or two ticks, below the arrival price, representing an immediate cost of 8 basis points. However, it is a firm price for the entire block. The portfolio manager accepts. The total cost is a known 8 basis points, compared to a projected and uncertain 30 basis points of market impact on the lit market. The SI, by absorbing the risk and providing certainty, delivered a superior, more predictable outcome, retaining its competitive edge through risk management rather than sub-tick pricing.

What Does the SI Technological Architecture Look Like?

The modern SI runs on a sophisticated, low-latency technology stack designed for real-time decision making. The key components include:

• Connectivity and FIX Protocol ▴ The SI must have robust FIX (Financial Information eXchange) protocol gateways to receive client orders from their Order Management Systems (OMS) or Execution Management Systems (EMS). Specific FIX tags are used to identify orders intended for SI handling and to communicate execution reports back to the client with the necessary transparency data.
• Market Data Infrastructure ▴ This system consumes direct data feeds from all relevant trading venues. It must normalize this data and present a coherent view of the European best bid and offer (EBBO) and market depth in real-time. The latency of this infrastructure is a critical competitive factor.
• The Quoting Engine ▴ This is the brain of the SI. It is a complex event processing engine that takes in market data, client order details, the SI’s current inventory and risk limits, and quantitative models of market behavior. Its output is a firm quote, compliant with the tick size regime, at which the SI is willing to commit capital.
• Risk Management System ▴ This system runs in parallel to the quoting engine, providing real-time monitoring of the firm’s aggregate risk exposure across all positions. It sets the operational boundaries for the quoting engine, ensuring that no single trade or series of trades can breach the firm’s pre-defined risk tolerance.
• Post-Trade Reporting and Analytics ▴ After an execution, this system takes over. It is responsible for reporting the trade to the market via an Approved Publication Arrangement (APA) within the timeframes mandated by MiFID II. It also feeds the execution data into the TCA system to generate the client-facing reports that justify the SI’s value proposition.

Reflection

The evolution of the Systematic Internaliser reveals a fundamental principle of market structure dynamics ▴ when one axis of competition is constrained, capital and innovation flow to others. The harmonization of tick sizes closed a door on simple price competition but opened a window onto a more complex and, arguably, more sophisticated landscape defined by risk absorption, technological prowess, and the quantifiable metrics of execution quality. This prompts a critical examination of one’s own execution framework.

How does your system define and measure a ‘good’ execution? Is it based solely on the explicit cost captured by the execution price, or does it incorporate the implicit, and often larger, costs of market impact and information leakage?

Viewing the SI’s adaptation not as a defensive maneuver but as an offensive strategic pivot provides a powerful lens. It suggests that the most resilient operational frameworks are those that are not dependent on a single structural advantage. Instead, they build a multi-layered value proposition. The knowledge of how SIs have re-architected their model is more than an academic insight; it is a component in a larger system of intelligence.

It informs how to better route orders, how to select counterparties, and how to build a more robust and adaptive execution strategy. The ultimate edge is found in understanding the complete architecture of the market and positioning your own operations to navigate its evolving pathways with precision and purpose.