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State Street


Nichols and Paige Pratt


08 December 2020

State Street’s Owen Nichols and Paige Pratt discuss their perspectives on how the approach to collateral optimisation has evolved in recent years and what the road ahead is looking like for the investment industry

Image: stock.adobe.com/Photocreo Bednarek
Collateral optimisation is an area of increased attention for the investment industry, due in large part to the Uncleared Margin Rules (UMR) that regulators ushered in after the 2008 financial crisis. This new regulation has spurred buy-side institutions globally to examine their collateral programmes and manage them more strategically. Organisations coming into scope for UMR compliance in phases five and six (2021 and 2022) are now looking at their collateral needs and capabilities in a new light. This is a welcome development, as increased complexity in collateral markets is changing the very nature of optimisation.

How are buy-side institutions thinking about collateral optimisation in light of UMR?

Owen Nichols: Based on what we’ve observed, only a small subset of institutions, primarily the alternative asset managers, demonstrate that collateral optimisation is truly embedded into their processes today. Many asset owners and traditional asset managers haven’t yet needed to be compliant because they’re in scope for phase five or six of the UMR – so accordingly, their level of readiness will vary.

Our discussions with clients have ranged from assisting them in understanding the regulation basics when calculating their aggregate average notional amount (AANA), as they may have paused readiness efforts when UMR implementation was delayed in 2020, to in-depth reviews of optimisation analytics and focused conversations on how they can transform collateral. A consistent theme we hear in these conversations is that technology budgets are limited. Teams are charged with preparing for the regulations, but they’re stretched thin and their situation is further complicated by the challenge of working remotely.

Given the scale of this challenge, we’re seeing institutions search for new ideas and they welcome external perspectives to help chart the best path. While each organisation is unique and outcomes vary, we’ve observed that investment teams appreciate a choice of modular components to address their gaps, especially when they know their service partner can help them simplify the contracting and technology integration with the key vendors. Often, these measures will enable timely adherence with the upcoming deadlines for UMR phases five and six, while the organisation works toward a more long-term, end-to-end solution. The overarching goals are to create operational efficiencies, achieve better transparency and minimise portfolio drag as much as possible.

How has the approach to collateral optimisation evolved in recent years?

Paige Pratt: The UMR have become a powerful catalyst for asset owners and traditional asset managers to take a deeper look at their collateral requirements. This is particularly true as the requirements expand in size and complexity.

Historically, collateral optimisation has meant some form of a ‘cheapest-to-deliver’ strategy. This means the trade is put on and it generates a collateral requirement, which in turn kicks-off a process to optimally meet that requirement. So, the measurement of ‘cheapest’ in this scenario can mean selecting operationally efficient collateral, which is often cash. It can also mean the implementation of a liquidity waterfall logic — for example, corporate debt, before government debt, before cash — with the aim of preserving the most liquid holdings.

The problem with the traditional ‘cheapest-to-deliver’ approach has been that is by nature reactive to the obligation created from trading, without being priced into the front-office decision-making process. It’s executed in the middle and back office, without a clear sight-line into the front office, which means it is effectively disconnected from the broader trading strategy.

Prior to the implementation of the latter stages of UMR, buy-side market participants have been required to post variation margin or repo margin, but this is viewed as a cost of trading. It’s the cost of doing business. The variation margin in these requirements is simply a result of the mark-to-market on the trade and is inherently aligned with the trading strategy.

The UMR requirements introduce a couple of layers of complexity. Margin requirements are set increase for buy-side participants, driven by the UMR’s focus on bilateral trades. Bilateral initial margin under UMR, as well as cleared initial margin for central clearers, is founded on risk and portfolio-based calculations that are more complex but can be managed with the right tools.

What types of tools or approaches are needed to effectively optimise collateral management and manage these headwinds?

Pratt: We look at this issue from a couple different angles. The first is integrating the collateral impacts into the front-office decision strategy, ahead of those trades being placed.

Initial margin calculations performed by central clearing parties, as well as the standard initial margin model (SIMM) for bilateral derivatives, take into account whether the incremental trade either adds to or offsets the directional risks in an existing portfolio. So, if you place a trade with one broker, your margin could increase while placing the exact same trade with another broker could result in a margin reduction.

The key factor is how the addition of that trade affects the risk in the existing portfolio. One trade with the wrong counterparty might not have a large impact, but hundreds of misaligned trades certainly will. Therefore, it’s key to give the execution desk transparency so they can reduce the overall size of the initial margin, but also account for the knock-on drag of that additional margin.

The second objective is getting a clear view into the portfolio collateral inventory optimisation. This means moving beyond basic cheapest-to-deliver strategies and implementing a more sophisticated algorithmic method, which accounts for eligibility and haircut placement impacts, as well as the associated funding cost and opportunity cost of the collateral types. Opportunity costs are critical drivers of a sophisticated inventory optimisation tool. Whether through the investment of cash or through securities lending, holdings can often be put to work to enhance portfolio returns if they’re not going to be encumbered as collateral.

Not all assets are created equal here. Cash opportunity costs can depend on currency and investment guidelines, while lending value of securities can differ based on asset class and market demand for those securities. So, the best tools will integrate both of these facets of optimisation and define the clearest path for the front office.

What themes are surfacing in your conversations with buy-side institutions as they progress on their optimisation journey? What is your outlook for the industry?

Nichols: We are seeing encouraging signs of progress across the industry, with increasing focus devoted to collateral optimisation and a commitment to identifying more sophisticated solutions. There is a growing awareness and understanding of the complexities of initial margin, which often translates into a heightened urgency to put new analytical capabilities into place. Buy-side institutions naturally want to see a clear vision of the potential operating efficiencies and funding cost savings they can achieve, to help them justify new spend on these analytics.

At State Street, we believe that these analytic capabilities and improved connectivity with the front office are important risk mitigants, because they support the preservation of cash and high-quality liquid assets in an uncertain investment environment. Looking to the future, we think collateral optimisation will be an important differentiator for investment businesses in an intensely challenging and competitive industry.
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