There’s a classic line from The Simpsons: “The Springfield Police have told me that 91% of all traffic accidents are caused by you six guys,” followed by celebration at Moe’s.  

While there is no centralized data source attributing the causes of pricing errors across investment operations, derivatives are often a significant contributor. At times, it can feel like derivatives operations teams shoulder a similar majority of the blame. Beyond internal reputational damage, these errors pose serious financial risks and may lead to external scrutiny or negative press. 

Many firms are actively working to identify process gaps and remediate root causes. Still, questions persist:  

• What exactly should be transformed?  

• What does a mature future state look like?  

• How can firms make meaningful improvements without a full system overhaul? 

A well-defined maturity model can help firms assess their current state and move toward a target framework to build toward a future state across systems infrastructure, process design, and operational readiness for derivatives.

What Defines a Mature Derivatives Operating Model? 

The foundation of a mature derivatives operating model is process design. Processes should verify that all relevant systems maintain accurate trade details, account allocations, and position valuations. Robust operational controls and automation are the keys to ensuring accuracy, validity, and efficiency across these categories.  

While systems can constrain firms’ ability to scale, process design should seek to introduce automation, with exception-based processing, wherever possible. For example, if a firm uses a modern order management system (OMS) but has a weaker Investment Book of Record (IBOR) or Accounting Book of Record (ABOR), issues may include misrepresented trade legs or dummy securities for mark-to-market (MTM) entries. In such cases, data from the OMS can be compared to the counterparty trade record. This can serve as a proxy reconciliation at a higher level of detail, then validate the core attributes from the deficient system against the system with the best representation. This introduces strong control and improves accuracy in the end-to-end flow, where downstream systems may not have been capable otherwise. 

Even in environments with limited tools, firms can use their strongest data sources to validate and strengthen weaker points in the process chain. 

To improve automation with less modern systems, consider how exception-based processing and reconciling the most basic components between two systems can more efficiently highlight the root cause of breaks. Firms with legacy or less modern systems can still achieve automation by introducing basic exception-based controls. For example, a margin reconciliation can be built to include inputs from each source, flag any discrepancies, and compare the contracts, pricing, and FX rates. Operations teams then evaluate margin breaks to identify whether the issue is isolated or systemic, reprocess margins, and investigate only the exceptions. 

These improvements are achievable regardless of the current technology stack. Whether the firm has one underperforming system or is still reliant on spreadsheets, process design can bridge many of the gaps.

Systems Infrastructure as a Maturity Enabler

From a systems standpoint, adaptability is essential, as there are many ways to represent the same derivatives instrument, both in terms of how the traded amounts are structured and the representation of the security master. Deals can be structured with traded amounts represented in terms of notional or in terms of units. 

While some representations have clear advantages in terms of data quality and accuracy, system limitations can force firms into less ideal data models until they are able to upgrade their systems. 

In a scenario where several systems have differing limitations for multilegged instruments, consider how a data warehouse can store and transform data to meet the differing system requirements. An appropriate data warehouse allows all systems to tie back to the central record and use controls to validate that the various representations are equal. A transformational layer between each system can enrich the limited representation from any system in the chain with details from the data warehouse to meet each requirement. 

In a more modern operational environment, similar strategies can be used to ensure accuracy across multiple IBORs or even across an asset manager and service provider. 

A strong data architecture does more than store information. It serves as connective tissue that ensures systems remain aligned and scalable as complexity increases.

Operational Readiness Plays a Major Role in Maturity

In today’s environment, the front office may identify a fleeting opportunity to generate alpha using a new derivative product or identify a more efficient way to hedge. Operations’ inability to support these requests generates opportunity costs and introduces unnecessary risks. 

Operations groups must have the capacity to identify gaps in their processing capabilities and to share their limitations with the front office to prioritize improvements. Ideally, firms should have a prioritized roadmap for new products and strive for continuous growth. Operational processes should be as modular as possible to ensure support for new products implements quickly, minimizing rework. 

Mature operations teams do not block innovation. They enable it, with the controls and structure needed to move fast without sacrificing accuracy.

By identifying and remediating gaps, operations are a strong partner to the front office, ensuring firms can fully implement their investment strategies.

Why Meradia? 

Regardless of your firm’s operational maturity, Meradia can help. Whether you need to make the most of what you have or are ready to implement a new end-to-end platform, our consultants have the expertise and experience to help you improve your operations, maximize your system’s capabilities, and expand your product coverage to enable front-office strategies. 

Our expertise bridges system limitations through strategic architecture, data transformation, and workflow design. We ensure accuracy, scalability, and readiness to support even the most complex trading strategies. Partner with us to future-proof your derivatives infrastructure and unlock operational alpha. 

Download Thought Leadership ArticleServices: Process Design and Change, System RationalizationExpertises: Derivatives and CollateralClients: Asset ManagersAuthors: Jake Daly-Leonard