Case study: Global tier-1 bank uses OpenGamma Analytics to save $8mm

Top global bank reduces its OTC cleared margin costs by 5.5% using a handful of trade recommendations from the OpenGamma platform


Since 2008 banks have been exposed to more and more regulation leading to higher margin and capital requirements. With growing liquidity in the CCP switching market,  opportunities are being created to move exposure between CCPs and reduce those costs, but this requires reliable and consistent data to identify opportunities.

Consequently, our client  a global tier-1 bank that clears trades across LCH, CME, Eurex and JSCC, was posting $2.5 to $3bn initial margin. This cost the bank over $25mm per year in financing costs. Over the last few years, the bank has been been accumulating structural risk across more CCPs, as post-crisis regulation has been pushing clients towards clearing and liquidity has become more fragmented (with Eurex and JSCC gain traction for EUR and JPY trades respectively).

The challenge

As a result, the bank could no longer reduce margin as effectively. Before post-2008 regulation hit, the bank ran an ad-hoc manual process to spot opportunities to reduce margin for LCH and CME by running specific scenarios through the CCP tools and internal spreadsheets once a week. In the current regulatory climate, the bank could no longer reduce margin as effectively this way. New, new regulation means the bank needed to identify opportunities faster and more accurately using more reliable data processed daily not weekly. This would normally require a lengthy and costly internal IT build to bring together the required data and display it clearly to support decision making.

This is why the bank contacted OpenGamma. Our cloud-based service which consumes the bank’s positions, running millions of simulations to improve desk-level decision-making, calculating implied CCP switching spreads across the 4 main Rates CCPs (LCH, CME, Eurex and JSCC) based on full firm-wide structural positions, highlighting opportunities to reduce overall CCP initial margin requirements.

Our Analytics allowed the bank to price MVA into its client trades and reduce margin costs by rebalancing risk across CCPs. Here’s how:

1. Pricing MVA into client trades

The lifetime cost of posting initial margin for cleared products will vary based on:

  • The individual CCP methodologies.
  • The directionality, duration and composition of the dealer’s portfolio.

On a standalone basis, the difference in MVA for identical 30y EUR 1mm DV01 trades across different CCPs can be as high as 2bps. The lifetime cost of financing the margin for that trade ranges from 5.7bps to 8.4bps running (including SIMM):

bank case study – graph 1

* Assuming 1% funding cost at each CCP.

In this standalone example, the difference is driven by differences in margin methodology.

This cost difference can become much greater when considering the bank’s underlying portfolios at each CCP.

Let’s look at the cost of this 30y swap for our client across 2 CCPs where they have existing positions:

Bank case study – graph 2

As the bank has directional portfolios at each of the CCPs, the cost of financing the incremental margin will vary depending on the CCP and the terms of the trade. In this instance, the difference is 5.1bps.

Being able to accurately price the cost of financing margin across CCPs is critical to winning client business as it can have a significant impact on the swap price quoted.

2. CCP switches

In addition, by using the platform, the client was able to find structural positions where paying in one CCP and receiving in the other reduced margin costs while keeping the net risk across CCPs the same.

On top of the existing structural positions, the different margin costs for trades at two exchanges were:   

Bank case study – graph 3

The above numbers are for one tenor with 5mm size at a time, i.e. if the client does 30y in 5mm size, the numbers for 25y and 20y would be different. But, if the client did different amounts of 20y, 25y and 30y adding up to 5mm, the net impact would be similar to doing one 5mm trade in one tenor as the basis are similar for all of them.

Taking advantage of the liquidity of the LCH-CME basis and with LCH trading at discount to CME, the client reduced the lifetime margin costs by USD 8mm by doing a set of 5 trades over a 1-week period not to hamper liquidity and execution.

Fragmentation of liquidity across CCPs means that it is incredibly easy to build up structural risk and margin inefficiencies that end up costing banks tens of millions of dollars every year. Accurately reflecting these costs in swap prices and identifying opportunities to reduce these costs is critical to the bank’s capital efficiency. OpenGamma allowed them to do this in a fast and cost-effective way.