Aussie asset managers struggle to meet ‘bank-like’ collateral, margin obligations

Australian asset managers are facing increasing regulatory pressure to perform, and since 2021, have been required to undergo a yearly assessment of their superannuation products by the Australian Prudential Regulation Authority (Apra).

Super funds, which hold A$3.9 trillion ($2.6 trillion) in assets as of March 2024, are held accountable for any underperformance. If a superannuation product fails the test two years in a row, it will not be allowed to accept any new contributions until it passes a future performance test.

One potential hindrance to passing this performance test is compliance with initial margin requirements and collateral management.

Australia, along with several other jurisdictions in Asia-Pacific, the US, the UK, and the EU, implemented the final phase of the Uncleared Margin Rules (UMR) on September 1, 2022, as stipulated by the Basel Committee on Banking Supervision (BCBS) and the International Organization of Securities Commissions (Iosco).

The International Swaps and Derivatives Association (Isda) has prescribed two methodologies to calculate initial margin: the standard initial margin model (Simm) and standardized grid (Grid). While Grid is a simpler and less-risk sensitive approach to initial margin calculations, Isda has observed that the initial margin determined using Grid is more conservative than that calculated using Simm.

The issue that buy-side firms in Australia face is that Apra is strict in giving out approvals to firms wanting to implement the Simm methodology, which is often referred to as the cheaper way of margining. As a result, most firms use the standardized Grid model.

“The reason more firms are with Grid is because the effort required to get Simm approval is just far too costly from a resource perspective and the engagement required with Apra,” says a source who recently worked at a buy-side firm with more than A$150 billion ($99 billion) in assets under management.

They say the regulator is treating buy-side participants as though they are banks. “They want all risk models rebuilt. They want them ratified. They want them confirmed. You need to have your own quants team, you need to have an independent review of your quant team, internal audit, external audit—very much the framework of a bank,” the source says.

Those teams are required to put together the 40-point Apra checklist for Simm approval, which can take six to nine months to do. The rationale of Apra’s “strict” approval process is that it wants to ensure superannuation companies understand their exposure—something the regulator isn’t confident of, the source says.

Marc Knaap, managing director for strategic partnerships at Cassini Systems, a provider of analytics and optimization tools for the derivatives industry, says that unlike other regions, Apra tends to be more actively involved in this process and wants to ensure that the model is correctly implemented with the appropriate data sources used.

“The supers feel that they are treated like banks. But banks are more liquid, and it’s easy for banks, for example, to lend money for repo and derive cash. In our experience, it’s much more difficult for supers. So, the supers argue that the return on their investment is lower because much of their money is tied to margin and collateral obligations,” he says.

He adds that many buy-side firms have typically outsourced margin calculations and collateral management. If so, Cassini has observed that Apra will insist that the supers have an independent methodology for calculating margin to validate the work their outsourced providers have done. 

I think that’s where the power lies: having your data, knowing your data

Buy-side source

“We have not seen that in any other region,” Knaap says. And particularly due to the time difference between Australia and the US, Australian firms tend to maintain larger collateral buffers for potential margin requirements. Knaap adds that these buffers can often be twice the size of those held by their European and North American counterparts, as it is challenging to incorporate the US market close and data from external fund managers in a timely manner for margin calculations.

This is pushing firms to adopt tools to calculate variation margin and initial margin before T+1 and to forecast and stress test their margin requirements in the short- to mid-term, which helps them avoid over-collateralization while ensuring collateral resilience.

Apra declined to comment for this story, but sources close to the regulator say that Apra’s CPS 226—which looks at margining and risk mitigation for non-centrally cleared derivatives—is aligned with international margin rules. “These rules are proportional in that only material financial users of over-the-counter derivatives are required to exchange initial margin. In Australia, this threshold is set at A$12 billion ($8 billion) of these derivatives, meaning only about five superannuation funds require Apra approval to implement an internal model rather than using the standardized approach,” they say.

False expectations

The Simm methodology is broken down into various risk buckets, and Apra wants firms to understand their risks in each of those buckets.

Unless you’re a quant, and have built the Simm calculator, you may not really understand the “why” of the various risk buckets, the buy-side source says.

“And the regulators are saying that the buy side needs to hire those people and bring those skill sets into the organization. There’s a false expectation that these types of resources are readily available and are on hand to assist,” they say.

In Australia, the initial margin requirements apply to entities with an aggregate average notional amount (AANA) exceeding A$12 billion. To comply with CPS 226, the first step is to calculate the AANA to see if they’re in scope to exchange initial margin.

This is challenging as data is fragmented, the source says. “We have multiple order management systems [and] we have a custodian with an overlay, so what is our golden source of truth?” they say.

This led the source’s firm to look for providers that could assist with the AANA calculation as well as pre-trade, trade, and post-trade exposures.

“It came to a point of, who can help take data from an order management system and translate that into the requirements for the AANA calculations to see if we’re in scope and bridge the gaps?” they say. 

Cassini was the only one of three providers the firm engaged with that could take the firm’s data as is, enrich it, calculate the AANA, and do initial margin calculations “on the fly.”

This is important as many superannuation firms have external fund managers, and to do the AANA calculation, the data needs to be aggregated at the asset owner level. “As an asset owner, you might have 10 or 15 external fund managers that may have their own order management system, their own way of reporting. They would report to the custodian and—get this—they would send a fax to the custodian three or four days after the trade has been executed to say, ‘These are the transactions that we’ve executed,’” the buy-side source says.

Knaap explains that Cassini integrates datafeeds directly from external fund managers upon a client’s request and then incorporates that data into its margin calculation processes based on the firm’s needs. It can do this easily because it is integrated into order management systems and execution management systems.

“Our analytics live in [BlackRock] Aladdin, State Street Alpha, Charles River Development, SimCorp Dimension, and on the hedge fund and risk side, Enfusion and TS Imagine. … With one click of a button, in a pre-trade scenario, firms can clearly see how margin and collateral costs impact their fund performance while operating within the regulatory constraints of the asset manager, owner, or hedge fund,” he says.

He adds that since Cassini is designed for intraday, real-time margin calculations, it can accommodate data from external fund managers even at later stages of the margin and collateral management workflow.

Cassini allows users to calculate margin on any asset and provides the ability to analyze and attribute the cost impacts of trading strategies while operating within regulatory and market constraints.

Execution transparency

This process was helpful to the buy-side source’s firm in determining what to do if it exceeded the A$12 million AANA threshold.

“If you’re over, how much are you over? What products are you over, and what is the expected margin that you’d need to pay on the back of it? By having the Cassini tool, it broke it down per asset class, per counterparty. So, I can see that with Goldman Sachs, for example, we put 90% of our interest rate swaps with them. And if we continue to do that, we’re going to be in scope, and we’re going to have to post margin,” says the source.

Having that information and breakdown by asset class and counterparty helped the firm understand its exposure. That allowed it to strategize around who it trades with and how it trades. “Not only do you want to try and stay below the threshold, but you don’t want to be exchanging margin—that’s what everybody wants to avoid. This is where you do the pre-deal trade check,” they say.

Using Cassini, the source says the firm’s portfolio managers had the insight to say, “If I put this transaction on, this is the impact it will have, and this is how much margin I would need to set aside or allocate to that transaction. Do I really want to do that transaction with Goldman Sachs? Or is it better to do it with BNP, or Deutsche Bank? Because if I have to pay margin, that comes out of the fund, which means I’ve automatically got cash drag.”

They add that implementing Cassini’s tool was straightforward, and the solution was up and running within four weeks. Other vendors it engaged with would require data to be in a particular format or wouldn’t engage with the external fund managers. “We would need to engage with them, collect that information, aggregate it, and send the vendor one file. That was a challenge from a resource perspective because we’re not an IT company—we’re not a data mining company that can sanitize all of this [data],” they say.

Cassini’s Knaap says the integration is quick and straightforward, particularly when clients use its partner solutions, referring to its analytics integration with major order and portfolio management systems and collateral and risk management providers’ tools.

But those not using Cassini’s analytics via any of those integrations will need to provide their data to Cassini, he says. From that point, it will typically take six to eight weeks to get the firm fully operational, depending on the specific Cassini modules required.

While complying with regulation is not typically seen as a competitive advantage—everyone has to do it—there may be opportunities for firms to save more money or make more basis points by managing margin requirements and collateral more efficiently.

“I think that’s where the power lies: having your data, knowing your data, and then slicing and dicing it, putting it through scenario analysis and then looking at questions like, ‘Do I send it for clearing? Do I send it for bilateral? Do I send it for securities lending?’” the buy-side source says. “Once you’ve got your core dataset ready, you can start to look at how you can start optimizing your return and what works better for your organization.”