Cross-Asset Archives - Page 2 of 6

Novation and backloading of 70,000 trades for G15 bank restructure

Client type: G15 Bank

Challenge:

Following internal restructuring, a G15 bank approached Custom Processing to facilitate the novation and backloading of bilateral trades across OSTTRA MarkitWire.

OSTTRA Solution:

Following a review of the scope of work, the G15 bank leveraged the Custom Processing team to handle all activities pertaining to the novation and backloading of trades across OSTTRA MarkitWire

OSTTRA Delivered:

Novation of circa 30,000 bilateral trades across OSTTRA MarkitWire
Backloading of circa 40,000 bilateral trades across OSTTRA MarkitWire
Scope definition, planning and delivery with cross-functional team involving OSTTRA and the G15 bank colleagues
Testing, issue resolution and authorisation for successful delivery in production environment
Script development to accommodate project requirements
Handling of all client communications, from inception to go-live
Fully documented project plan and runbook
Project constituted repeat business from the customer due to previous successfully completed projects

Customer Benefits

Streamlined, flexible bespoke project management
Defined project structure
Defined roles and responsibilities with single point of contact
Dedicated project manager and execution resources
Automated execution solution
Substantial cost savings

Focused, Tried and Tested

A repeatable and systematic service from OSTTRA, subject to continuous enhancement and evolution
Relationship management with internal and external project resources dedicated to meeting customer expectations
Full testing and issue resolution via pre-production and UAT Testing
Migration Day execution and communications

For more information or to arrange a call with a member of the Team please email info@osttra.com.

TriOptima named Best Compression and Optimization Service

As the transition to the new capital regime on counterparty risk and uncleared financial instruments gathers pace, an increasing number of firms with substantial exposure to over-the-counter (OTC) FX derivatives are looking for ways to reduce their gross notional and counterparty exposure in the most efficient manner.

In 2021, their toil is proving particularly laborious. Hundreds of firms will have been caught by phase five of the uncleared margin rules (UMR), which took effect on September 1, and many more will have to adapt the manner in which they calculate their exposure to derivatives contracts when the last remaining – and some of the largest – jurisdictions shift from the current exposure model to the standardized approach to counterparty credit risk (SA-CCR) by the end of 2021.

To fulfil their obligations, many financial firms have sought out TriOptima’s compression and optimization solutions over the past year, with noteworthy effects on the risk exposure of those in the network.
In January alone, $541 billion of gross notional was eliminated by TriOptima’s clients through its triReduce compression service, more than double the amount achieved the previous year. And, similarly, the triBalance service executed its largest ever optimization FX cycle at the beginning of 2021.

“Looking at the past 12 months, I’m most proud of the fact that we are live optimizing capital exposures in an ever-growing network,” says Erik Petri, head of triBalance solutions at TriOptima. “I can say with confidence that we offer the market’s largest optimization network for bilateral counterparty credit risk for the FX market.”

While reducing gross exposure to meet UMR rules and rebalancing counterparty risk to satisfy SA-CCR requirements can be met separately, Petri strongly encourages firms to accomplish both of these within the same cycle, rather than running separate compression and optimization cycles.

“It is extremely important for firms to consider optimizing both UMR and SA-CCR in one go,” he says. “Otherwise they risk suppressing one exposure while increasing the other, and that’s not ideal. In the FX market there is the opportunity to optimise the two in an extremely efficient way.”

The way TriOptima enables firms to achieve both goals simultaneously is that, during the compression side of the cycle, a set of forward and swap trades are replaced with new transactions with a combined gross notional that is worth less than the original notional. During the optimization portion of the cycle, short-term risk-reducing FX non-deliverable forwards and forward hedge trades are introduced across all relationships so each participant remains market-risk neutral. In this way, both initial margin and counterparty credit exposures can be reduced simultaneously, while at the same time reducing the gross notional outstanding.

Until recently, running this type of scenario was largely the remit of global systemically important banks – known as G-Sibs. In the past 12 months, however, an increasing number of smaller sell-side players have joined TriOptima’s network, with the buy-side also showing interest in the benefits that compression and optimization can offer.

“We are now seeing that interest filtering beyond the top-tier banks with regional banks and second-tier banks more focused on net optimization, not only because of the introduction of SA-CCR but also more generically,” says Mattias Palm, head of triReduce FX at TriOptima.

“While SA-CCR is only applicable to banks, we also see increasing interest on the buy-side, even though they’re not directly driven from a capital cost perspective,” says Palm. “Bilateral exposure comes with a cost to everyone, and a lot can be done across all kinds of institutions to minimize it.” While making the necessary technological investments to centralise their portfolios can be considerable for many firms, the benefits for TriOptima’s network of participants, that come from reducing risk through compressing and rebalancing a derivatives portfolio, can run into the millions, not only in the funding cost of initial margin but also the cost of capital.

“It’s impossible to put an exact number at the moment, but we know there are significant savings to be achieved,” says Petri.

“The transition to SA-CCR is a big deal for the industry,” he says. “And it’s something that we expect will drive growth over the coming years. There will be an increased need in the FX industry to keep counterparty credit risk down through rebalancing and compression. FX is one of the asset classes where bilateral liquidity – in terms of outstanding trades – is significant.”

Also worth noting is that OSTTRA’s triCalculate has developed an SA-CCR engine that calculates SA-CCR figures for portfolios containing a wide variety of derivatives transactions – margined and unmargined, as well as bilateral and cleared – across all asset classes, according to the latest guidelines.

OSTTRA’s TriOptima was voted Best compression and optimization service for FX at the 2021 FX Markets e-FX Awards.

OSTTRA triCalculate: Initial Margin Analytics

Case Study 1

Client type: European Pension Fund
IM analytics challenge: IM exposure calculations and Pre-deal check simulations
End User: Derivatives trading and structuring desk

Challenges

Our client who manages the derivatives trading desk at a large European insurance company needed a fast and efficient way of running ‘what-if’ initial margin scenarios in order to optimise exposures before derivatives trade execution.

The client is using OSTTRA triCalculate to calculate their daily IM exposures for derivatives subject to uncleared margin rules. They also benefit from the pre-deal check capabilities of the service which allows them to make informed trading decisions when pricing new deals to find the optimal counterparty in terms of IM. They have been using the service since coming into scope as part of phase 5 of the uncleared margin rules and value having the ability to run fast and efficient pre-deal check simulations. Additionally, they use the pre-deal check module to help mitigate the risk of breaching regulatory UMR or internal thresholds.

Case Study 2

Client type: Leading US Regional Bank
IM analytics challenge: IM exposure calculations, stress testing and forecasting
End User: Collateral management team

Challenges

Our client who is part of the regional bank’s collateral management team, needed daily IM exposure calculations.

The client needed to simulate changes to trade populations and to assess their impact on their IM exposures as their auditor required the bank to monitor how trade expirations were leading to changes in IM.

Additionally the client had an internal requirement to occasionally benchmark how their IM exposures would change if they switched calculation model by using the schedule/grid approach instead of the more risk sensitive SIMM™ model. The client’s risk team also required the collateral team to stress their IM exposures by using stressed and/or alternative sources of market data.

Case Study 3

Client type: European Regional Bank
IM analytics challenge: IM exposure calculations and regulatory model backtesting
End User: Credit Risk Manager

Challenges

Our client manages the credit risk management team of a large regional bank that was in scope for the uncleared margin rules for derivatives transactions.

They needed a solution for calculating their daily IM exposures and also a tool to help them cope with the regulatory requirement of backtesting the SIMM™ model on a quarterly basis. The bank required a backtesting solution to compare the 10 day SIMM™ IM to 10 day actual P&L moves.

Our Solution

These firms took the decision to use OSTTRA for their regulatory IM calculations. The service provides an easy-to-use, web-based solution that streamlines the daily IM process. Our clients benefit from transparency into their IM exposures and the ability to gain a more detailed understanding of their overall IM exposures through pre-deal check simulations, backtesting reports and IM analytics via an intuitive and flexible interface. The interactive interface further allows clients to decompose their total IM exposures into its different components and to run detailed P&L explain reports to understand day-to-day changes in margin amounts.

All clients also benefit from being able to run simulations on trade population changes through the interactive interface by uploading amended input files or performing simulations using alternative market data.

For more information about the our Initial Margin analytics service, please email info@osttra.com.

Why Do We Disagree? How AI Solves One of Post-Trade’s Most Persistent Challenges

In post-trade operations, most problems are not caused by outright errors, they are caused by ambiguity. Trades that look different but are not wrong. Valuations that diverge for valid reasons. Numbers that do not line up, even though nothing has actually gone awry. At scale, that ambiguity is more than a nuisance – it becomes very expensive.

Across global markets, banks reconcile vast portfolios of trades every day. In most cases, counterparties broadly agree. But a small proportion of differences persist, feeding into portfolio reconciliation breaks, valuation discrepancy and, ultimately, collateral disputes. Each instance requires manual intervention, devouring time, human attention and in many cases, regulatory capital.

This is where artificial intelligence (AI) is beginning to matter in a tangible, impactful way.

A dispute problem, not a broken system

It is important to be clear about what this problem is and what it is not. Post-trade infrastructure is not failing. On the contrary, trades are confirmed, processed, and settled at extraordinary scale with remarkable reliability.

The challenge emerges much later. Over time, trades that once matched perfectly can appear differently in each counterparties’ internal systems. Present values move as markets move. Models diverge, volatility assumptions vary and FX rates are captured at different times of day. Time zones, calendars, and internal conventions all play a role. While most of these differences are often valid, proving that is difficult.

Over time, trades that once matched perfectly can appear differently in each counterparties’ internal systems.

As a result, banks often devote large teams to dispute management. Dozens of people may spend their days drilling down from portfolio-level differences to individual trades, trying to answer one deceptively simple question: ‘why do we disagree?’

The real risk is not that differences exist. It is that genuinely dangerous booking errors can be hidden among a much larger volume of explainable noise.

Signal versus noise

This is the distinction that really matters. In dispute management, the signal represents the handful of true errors that can pose genuine financial risk. The noise is everything else: timing effects, model differences, data conventions and benign inconsistencies that look alarming until properly explained.

In dispute management, the signal represents the handful of true errors that can pose genuine financial risk.

Historically, separating the two has been slow and manual. Teams work through disputes one by one, often without the full context needed to resolve them quickly. The result is operational drag, capital buffers held “just in case”, and less time spent on the issues that genuinely deserve attention.

AI changes this dynamic, not by replacing expertise, but by accelerating understanding.

What AI actually does in this context

The value of AI in post-trade is not abstract. It lies in pattern recognition across scale. Post-trade platforms occupy a unique vantage point maintaining a view of both sides of a trade. This means that not only do they witness how valuations evolve over time, but crucially – how similar disputes have been resolved in the past. Individual institutions simply cannot replicate this view on their own.

By applying advanced analytics and AI to this dataset, it becomes possible to explain a far greater proportion of differences automatically. Not by guessing, but by learning from history.

For instance, valuation differences driven by FX timing can look like serious breaks when viewed in isolation. But when analysed across time series data, exchange rate movements and historical behaviour, they can often be identified and explained with high confidence. What once required hours of manual investigation can be resolved far more quickly, and with clear supporting evidence.

From investigation to prioritisation

When explainable differences are resolved faster, two things happen. Firstly, operational teams spend less time proving that nothing is wrong. That reduces cost and friction across reconciliation and collateral processes.

Secondly, and more importantly, with the noise filtered out, the remaining pool of unexplained differences stands out more clearly. This is where genuine booking errors, model failures, or contractual misunderstandings hide.

In other words, AI helps teams prioritise risk, not obscure it. Adding to the toolbox, not replacing it. None of this suggests a radical break from existing post-trade practices. Human judgement remains essential – but what AI adds is leverage. It enhances the existing toolkit by removing friction and ambiguity at scale. It also allows experienced professionals to spend more time on high-value work and less time navigating false positives. This is particularly important as volumes continue to grow and markets become more interconnected. Complexity is not going away. The only sustainable response is better insight.

AI helps teams prioritise risk, not obscure it.

A pragmatic path forward

AI in post-trade does not need to be futuristic to be transformative. Its impact is already visible in dispute explanation, reconciliation efficiency and collateral workflows. The next phase is about extending that capability responsibly – applying intelligence where data is rich, outcomes are measurable, and human decision-making is enhanced, rather than displaced.

The goal is clarity, less noise, and sharper signals. By ensuring risk is no longer drowned out by ambient friction, AI facilitates a post-trade environment where material exposure is easier to identify and manage. While AI adoption is in its infancy, momentum will build as firms realise tangible, measurable gains in operational efficiency

EMIR Post Trade Risk Reduction Service Exemptions from ESMA and the FCA Come into Effect for OSTTRA

LONDON, 8 July 2025 – OSTTRA services have been granted exemptions from mandatory clearing obligations under EMIR by the European Securities and Markets Authority (ESMA) and from the public reporting requirements under MiFIR by the UK’s Financial Conduct Authority (FCA).

OSTTRA triBalance is currently the only provider in the EU approved to carry out post-trade risk reduction services under a clearing exemption, confirmed by ESMA on 16 June 2025. Additionally, the FCA’s exemption from the Derivatives Trading Obligation (DTO), post trade transparency reporting and best execution requirement took effect on 30 June 2025, removing a further obligation from UK based users of OSTTRA’s Post Trade Risk Reduction (PTRR) services. EU based users already benefitted from the equivalent exemptions that came into force with EU MiFIR 3 in 2024.

The clearing obligation was designed to reduce systemic risk by mandating central clearing for certain derivatives, however, the EMIR clearing obligation prevented the use of vanilla swaps for portfolio rebalancing. With the exemption now in place, the OSTTRA service can better optimise risk reduction through a more liquid and widely traded contract, marking a significant milestone in OSTTRA’s efforts to expand the use of post trade risk reduction services.

Previously, swaptions were used as a proxy, but these more complex and costly instruments limited the wider adoption of portfolio rebalancing. This reduced the broader benefits of multilateral participation, preventing widespread reduction of counterparty risk in the financial system. The exemptions from ESMA will better enable OSTTRA to support a wider set of market participants.

A similar decision from the Bank of England’s Prudential Regulation Authority (PRA) is under consideration; another key step towards enabling broader market participation. Work is also underway to facilitate similar exemptions from the CFTC and SEC for equivalent rules in the US under the Dodd-Frank Act, which will complete the regulatory alignment needed to fully support multilateral risk reduction and enhanced liquidity.

“This is an important development for our clients, who rely on our services to reduce risk in their portfolios,” commented Kirston Winters, Head of Legal, Risk, Compliance and Government and Regulatory Affairs at OSTTRA. “These exemptions allow us to deliver more efficient and accessible optimisation services, reducing operational complexity and enabling broader participation in multilateral risk reduction – ultimately strengthening the resilience of the financial system. We’re working closely with other regulators to provide additional exemptions, which will further enable firms to use post trade risk reduction services.”

To find out more, talk to a member of our team at at info@osttra.com.

The Power of Post Trade: How OSTTRA is leveraging AI to deliver value and confidence

Introduction

by John Smith, CTO of OSTTRA

Change is the only constant at OSTTRA. Over the past two decades, we have built the essential post-trade infrastructure that underpins global financial markets. But we have never stood still. Our systems evolve alongside shifting regulations, market structures, and emerging technologies.

Today, we are leveraging this foundation — a deep network of shared connectivity, data, and industry standards — to unlock the transformative power of AI. By applying the lessons of the last twenty years, we are uniquely positioned to deliver AI’s benefits while minimising the friction of implementation.

We’ve started this journey from within, equipping all staff with Gemini, empowering our developers with code assist and integrating agents into workflows that drive efficiency across the firm.

In this series of articles, we will explore the specific use cases we are rolling out to our customers, starting with the core principles that guide our approach to innovation for the post-trade community.

The OSTTRA Vision: The New Era of AI in Post Trade – From Reaction to Anticipation

Artificial Intelligence is now a crucial, transformative force in the post-trade ecosystem. At OSTTRA, our clear vision involves leveraging this technology to optimise processes, mitigate operational risks, and deliver unparalleled value and confidence to the global market. We are not simply integrating AI; we are strategically embedding it throughout our technology stack to solve high-stakes, real-world problems and fundamentally enhance the efficiency, accuracy, and security of client operations.

A Philosophy of “Purpose over Hype”

Our approach is Cautiously Ambitious. We believe AI is a powerful solution only when applied to the right challenge, prioritising real-world utility and security over mere novelty. To accelerate innovation without getting caught in the “reinvention trap,” we have forged a deep strategic partnership with Google.

By leveraging Google’s cutting-edge AI infrastructure, pre-trained models, and generative AI capabilities—specifically tools like Vertex AI—we focus on two key areas:

Accelerated Innovation: Securely fast-tracking our Machine Learning (ML) and AI projects, allowing our central AI team to focus on the most impactful post-trade challenges.
Focus on Client Value: As expert users of AI, rather than frontier researchers, our efforts are directed entirely toward applying this technology to deliver measurable benefits to our clients

Data Security: Our Unwavering Commitment

The security and safeguarding of client data is paramount. We adopt a conservative, security-first approach, applying the same rigorous data protection framework to our AI applications as to all other mission-critical systems.

Our AI framework is built on three non-negotiables:

No Client Data Exposure: Client data and information are never exposed to vendors or external parties for AI training.
No Internal LLM Training: We do not tune or train Large Language Models (LLMs) on client data, eliminating the risk of internal data leaks.
Strict Governance: We maintain ironclad AI policies and are actively working toward ISO 42001 certification during 2026, ensuring adherence to the highest international standards for AI management.

Transforming Post Trade: An Engine for Client Value

While generative AI is used internally to boost our efficiency, our primary focus is transforming the client experience. We are committed to using AI to help clients resolve disputes, breaks, reconciliation, and processing failures, while providing the advanced insights necessary to prevent them altogether. This directly addresses the significant time and effort firms spend daily on trade processing and reconciliation.

AI’s Role: Resolution, Prevention, and Advanced Insights

AI is fundamentally changing the resolution landscape, which is often a significant drain on operational resources. By analysing vast streams of historical data, powerful AI applications can identify errors and understand their root causes.

Accelerate Dispute & Break Resolution: Intelligent analysis can pinpoint discrepancies and determine the most likely path to a matched trade, drastically speeding up confirmation. In many cases, AI will identify errors pre-matching or automatically resolve issues through dedicated agents.
Proactive Prevention: By analysing the reasons failures occur, AI provides clients with deep insights into potential systemic issues. This allows firms to correct problems at the source, transitioning from a reactive “firefighting” mode to a truly preventative operating model.

“We are creating intuitive, intelligent resources that automate tasks currently handled manually.”

Enhanced Self-Service and Future Automation

Beyond resolution and prevention, we are creating intuitive, intelligent resources that automate tasks currently handled manually. Tools like the OSTTRA Digital Assistant are already being rolled out, allowing users to employ natural language queries to receive concise, verified information, replacing traditional manual searches of documentation and support interactions.

Looking ahead, we envision intelligent agents delivering:

Highly Contextualised Responses: Tailored support that integrates client-specific data.
Workflow Guidance: Real-time support relevant to a user’s specific platform utilisation.
Proactive Recommendations: Suggestions to maximise the efficiency of the overall OSTTRA experience.

At OSTTRA, AI is the engine driving a future of reduced operational costs, improved risk management, and a superior client experience. Our strategic adoption and partnership with Google continue to bring unparalleled efficiency and trust to the world of post trade.

Proactive IM Management in the Face of SIMM 2.8+2506

The semi-annual recalibration of the ISDA SIMM model, version 2.8+2506 (reflecting data up to 30 June 2025), has been released and becomes effective on 6 December 2025¹.

This update introduces relatively modest changes overall. We see some of the biggest delta risk weight decreases in energy-sector commodities. Conversely, the most notable increases are in the credit qualifying space, specifically for high-yield and non-rated subsections within the financial and technology sectors. Most other risk weights and correlations across interest rate, commodity, and equity risk classes see only minor adjustments, and all concentration thresholds remain unchanged.

While these specific parameter changes may be small and likely have a minor impact on SIMM calculations, in the contemporary regulation-driven environment, we see a trend where the costs and complexities of managing initial margin are becoming a critical focus for liquidity and funding.

In this landscape, simply calculating the IM number is not optimal for managing margin costs, maintaining control over liquidity buffers and making funding projections. There is significant value in understanding its drivers and anticipating how it changes with time, alterations of the portfolio and under stressed market scenarios. The OSTTRA triCalculate service has a sophisticated suite of tools designed to address these exact challenges.

Stay ahead of SIMM version updates

Clients can anticipate IM impact from a SIMM recalibration. Well before SIMM 2.8+2506 becomes effective, OSTTRA triCalculate enables users to compare their current portfolio’s IM against the new model version.

Understanding daily IM movements

A common challenge we see is understanding why IM moves from one day to another, especially for portfolios dependent on many market factors. We have developed a dedicated attribution view to make this transparent. It allows for a drill down analysis from the top-level product class (e.g., Equity, Rates) to the individual risk factors and trades, as well as quantifying how much of the IM change can be attributed to market data moves versus new and expired trades.

Make informed strategic decisions

Effective IM management is forward-looking. To that end, we provide powerful tools for strategic planning:

Pre-Deal Checks: How will a new set of trades affect your margin? Our pre-deal check tool quantifies the marginal IM impact before execution. This insight can be crucial in deciding not just whether to trade, but how to trade, potentially aiding in the selection of a counterparty or the structuring of the transaction to be more margin-efficient.
IM Stress Testing: You can also project your margin exposure into the future. The service supports sophisticated IM stress testing, allowing you to bump market data or apply a theta shift (time decay) to predict future IM requirements under various scenarios.

Calculate the cost of funding

Funding initial margin over time can be a big financial burden and source of uncertainty. As part of our extensive XVA suite, we support MVA (Margin Valuation Adjustment) calculations. MVA quantifies the expected cost of funding initial margin over the lifetime of a portfolio. Clients are interested in MVA because it provides a measure of a major cost component associated with uncollateralised or partially collateralised trades, ensuring that pricing fully reflects the true economic cost of the trade’s full lifecycle.

Don’t wait for 6 December

The ISDA SIMM 2.8+2506 update is just the latest challenge in a complex and evolving margin landscape. With OSTTRA triCalculate, you can move from a reactive to a proactive IM strategy.

Contact us at info@osttra.com to schedule a demo or, if you are an existing client, to run a free impact analysis on your portfolio against the new SIMM 2.8+2506 model.

¹ https://www.isda.org/2025/10/31/isda-publishes-isda-simm-methodology-version-2-8-2506/

Navigating the Complexities of CVA Risk Capital Calculations: A Global Perspective

Basel III capital rules now require banks globally to choose between the Basic Approach (BA-CVA) and the more risk-sensitive Standardised Approach (SA-CVA) for calculating Credit Valuation Adjustment (CVA) risk. Many institutions, particularly in the EU, have initially favoured BA-CVA due to lower implementation costs.

In the EU, a significant factor influencing CVA risk capital strategy is the current exemption for corporate and sovereign trades, which reduces the capital cost considerably. However, the long-term stability of this exemption is uncertain. Its potential removal would significantly increase the required CVA capital, possibly shifting the balance in favour of SA-CVA for many institutions. This kind of regulatory uncertainty requires banks worldwide to carefully consider their CVA risk capital strategy and prepare for regulatory shifts.

The choice between BA-CVA and SA-CVA also has important implications for hedging strategies. While SA-CVA allows banks to incorporate market risk hedges into their CVA calculations, BA-CVA does not. Consequently, hedging to reduce P&L volatility might inadvertently increase capital requirements under BA-CVA. Banks, therefore, need to carefully weigh the trade-offs between simplicity, capital efficiency, and hedging effectiveness, a consideration relevant across all jurisdictions.

OSTTRA triCalculate XVA helps banks apply the most appropriate approach to different counterparties. This granular control is crucial for optimising capital and adapting to evolving regulations, both within specific jurisdictions and globally. Furthermore, OSTTRA triCalculate XVA leverages GPU technology to overcome the computational complexity of CVA sensitivity calculations. This enables efficient and timely generation of necessary risk sensitivities, even for large and complex portfolios.

With the Basel III capital rules already implemented in some jurisdictions, the UK set to adopt them in January 2027, and US regulations expected to follow, banks must take a proactive approach to CVA risk capital management. This involves not only considering the current regulatory landscape but also anticipating potential changes and understanding the interplay between CVA risk capital calculations and hedging practices.

A flexible and robust calculation solution, capable of handling the computational demands of CVA, is vital for navigating this complex and globally diverse environment, ensuring long-term compliance and capital efficiency.

OSTTRA triCalculate provides XVA risk calculations across credit, debt, funding, margin, capital and collateral for bilateral OTC derivatives. Our web-based service provides efficient XVA calculations using transparent and consistent models. To learn more, contact us or visit osttra.com/xva

Cash Flow Management: Moving Away from Manual Workflows

Efficient cash flow management is critical for market participants navigating ever-evolving post trade requirements. But existing workflows rely on manual processes, leading to errors and excessive operational demands. Watch the video below to hear from Tom Woolfenden, Product Design Director at OSTTRA, to hear how OSTTRA Cash Flow Management is automating and streamlining operations for firms facing tight deadlines and complex processes.

Our configurable, centralised platform already processes thousands of cash flows, across multiple asset classes and currencies. To find out more, visit osttra.com/cashflow or contact us.

From Rusty Bikes to Formula One: Upgrading Cash Flow Management in Derivatives Trading

Traditionally, the back office has lagged behind the front office in technological advancements, hindering efficiency and accuracy in cash flow management. It’s time to shift gears and unleash the full potential of automation, regardless of asset class or payment type.

In December 2024, Philippe Lintern, the head of the Bank of England’s FX division, compared front office staff using the most advanced technology to Formula One teams, while noting that peers in the back office were left struggling to match the pace on their “rusty old bicycles.” An area where this rings particularly true is the $667 trillion global derivatives space, where cash flow management remains heavily manual, relying on humans, emails and even fax machines, despite the fast-paced world of trading pushing ever increasing volumes through this strained back office infrastructure.

It doesn’t have to be like this. As the dust settles from the all-consuming rush to T+1 settlement, resources can be re-focused on tackling some of the stubborn pockets of manual process that persist in the back office – and with the twin goals of improving both operational and capital efficiency, cash flow management is emerging as a priority.

“Last year we started to see a lot more focus on transparency and automation in post-trade interactions between counterparties, including those processes where custodians are involved, such as cash flow payments,” said Tom Woolfenden, Director, Product Design, OSTTRA. “However, so much manual coordination remains to agree and settle these cash flows.” This has been highlighted recently by the Financial Markets Standards Board in their final standard for sharing of Settlement Instructions, and updated guidance also issued in the Global Foreign Exchange Committee’s revised FX Global Code, such as Principle 44, which states that “Market Participants are encouraged to implement straight-through automatic transmission of trade data from their front office systems to their operations systems”, by means of secure interfaces where the transmitted trade data cannot be changed or deleted during transmission.

Cash flow management itself isn’t a complicated concept: At its core, it’s about making regular payments to the other parties involved in your trades, based on the underlying contract terms and up-to-date valuations.

However, things get incredibly complex when you consider the scale of the market. A large financial institution might handle hundreds of thousands of these trades and their associated cash flows every month. This volume alone makes it difficult to track who owes what to whom. The problem is compounded by the fact that different participants use different data standards, calculation methods, market data sources, and messaging formats. This lack of standardisation can make it extremely challenging to even figure out which specific trade back-office staff are discussing in their emails, or which trade is causing a discrepancy.

“An absolute worst-case scenario is that you’re expecting to receive a cash flow from an open trade, and you have your designs on how to use that money, but your counterparty doesn’t even have an idea that there is an obligation to you”, Woolfenden adds.

Interest rate swaps, equity swaps and portfolio swaps are prime examples of the products where manual cash flow management leads to errors and operational inefficiencies. Take equity swaps for example: Cash flow management for these contracts involves the ongoing payments of the swap for the duration of the trade, as well as the underlying dividends and accruals, all of which need to be calculated, agreed on and then settled, which is where the uncertainty and misalignment comes in.

“We often see market participants taking agreed cash flow information offline, emailing, or even faxing it to their custodian, creating an inefficient communications chain to complete the payment and settlement process,” Woolfenden said.

As settlement times are expected to continue to shorten globally, untangling the confusion will quickly become even more important. Cash flow inefficiencies also prevent liquidity optimisation, or the ability of the front office to deploy cash to generate profits – because the money is stuck in a back-office limbo until the disagreement is resolved.

The most efficient way to resolve this conundrum is bringing transparency into the process for all sides and linking agreed trades with subsequent cash flows so that calculations can be made using consistent economics. OSTTRA Cash Flow Management is an established platform that helps streamline the cash-flow-processing challenge with a standard workflow and matching engine. With legal confirmations for many bilateral OTC trades readily available on OSTTRA MarkitWire and connected to the OSTTRA triResolve reconciliation engine, participants can have complete confidence that they share a common view of a transaction with their counterparties. An automated system that matches cash flows, as well as linking the underlying trades associated with them, removes the need to spend time figuring out who owes what and why: OSTTRA Cash Flow Management also notifies participants if they’re misaligned. It can also bilaterally net matched cash flows into an agreed, reduced number of payments whilst respecting settlement instructions.

“At OSTTRA, we are uniquely positioned to eliminate friction and inaccuracies in derivatives cash flows, thanks to our position at the centre of post-trade, from trade confirmation and processing through to portfolio reconciliation and collateral management, and all the opportunities for improving data standardisation that this brings. The end result is that we can seamlessly automate the entire process, including sending SWIFT settlement messages on behalf of our clients. The settling bank, typically the custodian, can receive an instruction to do the settlement just one minute after the cash flow is matched, removing the all too common merry-go-round of email, phone and fax communication and bringing greater transparency on a real-time basis,” Woolfenden said.

Once the whole lifecycle is automated, conducted in real-time and in a way that’s transparent to parties, calculations can be done on the same basis, payments can be netted and settlement becomes a matter of a simple instruction to the custodian – as easy as riding a bike! To learn more about OSTTRA for Cash Flow Management, please visit osttra.com/cashflow