The prospect of the U.S. Federal Reserve raising interest rates in 2022 will mean a new focus on putting cash to work. Furthermore, the Archegos hedge fund collapse earlier this year showed once again the importance of collateral management and optimizing the calculation of initial and variation margins. So an integrated approach to collateral optimization is very much on the minds of bankers and hedge fund managers. There are big opportunities to boost revenues and reduce costs but all this can prove difficult to achieve if you are faced with an array of existing systems and the limitations of packaged solutions. David Cassonnet, Global Head of Business Development at ActiveViam, explores the problems posed by collateral optimization and how to resolve them.

The combination of rising inflation and a recovering economy is generating expectations of rising interest rates. The ECB seems determined to resist and the BoE has yet to make up its mind, but the growing consensus is that the US Federal Reserve will raise interest rates next year, probably by 25 basis points to 0.25-0.50% in Q4 2022.

So after a decade of vanishingly low base rates, buy- and sell-siders are facing the prospect of no more “cash on the side-lines”. That means banks, and the hedge funds they service, will need to rediscover the “lost art” of managing collateral so they can free up cash to invest and trade. The ability to optimize existing collateral will again become a highly-valued and sought-after service, and bankers will see the optimization of client assets as a differentiator when competing for business. But they also need to integrate the technology developments of the previous 15 years. It makes no sense to simply go back to the old methods.

This renewed focus on collateral optimization comes at a time when the dangers of poor collateral management are all too clear.

The Archegos fiasco in June 2021 illustrated the flaws in the current way that initial margin (the minimum balance required to open a position) is calculated. The hedge fund had been making big bets on certain stocks using derivatives known as total return equity swaps. But according to the Financial Times, approximately US$10bn of losses resulted from inadequate collateral management and the affected banks’ subsequent rush to liquidate their positions. 

Archegos was a headline-grabbing example, but the management  of both initial and variation margin is challenging during periods of high volatility. The problem is compounded when the banks that act as brokers to hedge funds lower collateral levels in a bid to generate more business.

All of which makes the management and optimization of collateral an important concern for bankers and buy-side alike. The problem is that, as so often, senior managers are faced with an array of existing underlying systems when what they need is an analytics platform that operates across siloed departments through the back, middle and front offices.

Optimizing across silos

ActiveViam’s proposal to meet this challenge is to deploy an agnostic, firm-wide, cross-asset aggregation platform that ensures users have a real-time, consolidated view of collateral exposure, collateral types and inventory levels. Information should be updated incrementally as soon as the underlying data changes (new trades, FX rate change etc.) and is available to multiple users who can access the data simultaneously.

Sudden, large market moves require the front office to assess on an intraday basis different data sets in order to evaluate whether additional variation margin is needed to cover a trade. This requires of-the-minute access to collateral inventories as well as a microscopic view of counterparty risk. ActiveViam wants to allow users to interrogate collateral data at any level and perform instant ‘what-if’ analysis to evaluate alternative optimization scenarios. These might include cherry-picking assets, excluding portfolios, or strategic asset withdrawal.

Overall, the right software solution will enable the easy aggregation, optimization and analysis of large volumes of complex, dynamic data enabling firms to perform deep-dive and scenario-based analytics and really understand their margin exposure and cost-of-trading. Once bankers have a clear view of their collateral positions they can free up cash to trade. The approach we are advocating also potentially saves traders hours every week as they no longer need to work out the best collateral for every trade, and can instead concentrate on making profits. 

There are clear practical advantages to such an approach. ActiveViam is a completely flexible solution that adheres to a firm’s technology architecture and sits atop its existing systems while drawing the necessary data out. It comes with pre-built optimization algorithms (such as “CTD”, Cheapest to Deliver) to help ensure the deployment of collateral optimization applications in a matter of months. But over time, in-house business and IT teams can enhance it with their own algorithms as their collateral strategies evolve.

Banks can actively monitor and forecast margin levels to ensure limits and thresholds are managed effectively in real-time. ActiveViam goes well beyond traditional CEP (Complex Event Processing) software, ensuring better-informed decisions through more advanced business logic. It also manages rules that trigger specific actions, for example to exclude certain assets when clearing cut-off times are reached, ensuring maximum optimization efficiency.

As we go into 2022, ActiveViam is keen to start a conversation within the market about the best approach to achieve these significant benefits in terms of both cost control and revenue generation.

In terms of cost, simple allocation methodologies like preference ranking or haircut ranking are static and do not consider all the variables associated. Calculating – and therefore understanding – the cost of collateral depends on a clear view of transaction/settlement costs, transformation costs, haircut, lending rates, interest rates (etc.). With the right approach, strategies for collateral optimization can be based on dynamic models which consider all the costs and ranking variables that can vary on a daily basis.  

On the revenue side, repo and securities-lending desks can generate alpha by using eligible collateral inventory to lend to others and collect a return. But this requires a front-to-back platform that allows an enterprise-wide view of the available inventory, and the implementation of multiple collateral optimization algorithms that are collateral-focused and/or lending-focused..

Such a deployment also offers major benefits for the buy-side. Only a small subset of asset managers currently have collateral optimization and inventory management embedded into their daily processing. Instead they generally rely on cash to cover margin requirements. But proper workflow automation and asset allocation tools can ensure collateral availability and forecast potential margin calls based on current market conditions.

2022 looks like being the year when collateral optimization is right back in fashion. This will rightly lead to a new emphasis on how it can both boost revenues and minimize costs. And 15 years on, there are now better, more efficient and more flexible ways to achieve it.