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Feature

Techniques for post-trade collateral optimisation


05 January 2016

Ted Allen of FIS and Thomas Schiebe of Sapient Global Markets discuss the techniques that firms are employing to optimise the allocation of collateral


Image: Shutterstock
Collateral optimisation is a buzzword used to describe a variety of techniques that aim to reduce the cost of collateral supporting trading activity. This is important for all sell-side and buy-side market participants given the various regulatory changes that increase the amount of collateral required to support trading activity, the increasing number of collateral movements to be processed and the additional strain on liquidity from regulatory capital changes. The goals of collateral optimisation differ by firm, geography and sector but at their core translate into a number of common problems.

In a previous paper written jointly by FIS and Sapient Global Markets, we discussed the collateral optimisation value chain and the tools that can help firms minimise the impact of increased collateral requirements. The collateral optimisation lifecycle consists of three distinct phases:
Pre-trade optimisation to minimise the margin requirement of a given new deal by identifying the optimal broker, central counterparty or bilateral counterparty;
Ongoing optimisation that seeks to minimise the amount of collateral required to support a given portfolio through cross-margining, trade compression and back loading of trades to clearing; and
Optimised post-trade collateral allocation to minimise the funding or opportunity cost of the collateral deployed.

In a new whitepaper due to be released this month, we provide an in-depth analysis of the techniques for optimised post-trade collateral allocation. Here is a taster of some of the key highlights.

Purpose of optimised collateral allocation

The optimisation of each step of any financial institution’s processes is more important than ever. Collateralisation of business activities has increased post-crisis due to regulation, market standards and a wider adoption of credit risk mitigation techniques. The available collateral within every typical financial institution is limited and there are conflicting demands for the use of high quality assets, hence a mechanism is needed to ensure these are optimally allocated.

By optimising the allocation of collateral, firms are essentially minimising the cost of use of collateral assets. In addition to minimising cost of use, another goal of collateral optimisation can be to maximise the value of the assets that are retained. This two-step approach of minimised cost and maximised retained value requires active management of collateral allocation as part of a front-office trading or treasury management function. The growth in the number and complexity of collateral agreements and the amount of collateral required make the optimisation problem both large and complex. The paper discusses why a waterfall approach to allocating assets against requirements based on preference ranking cannot lead to optimal results, highlights other techniques that may be employed and provides examples of savings that are achievable in a typical collateral programme.

Requirements

Collateral inventory optimisation can identify how to rebalance the collateral inventory by posting the overall cheapest-to-deliver collateral while considering funding capacity and liquidity ratios. The most advanced algorithms identify what collateral should be substituted, what assets should be posted against new requirements and what assets should be retained in order to minimise overall costs and maximise potential liquidity from a given inventory. Both of these goals can be achieved in a single process.

Recent studies performed by both Sapient Global Markets and FIS demonstrate that significant, quantifiable savings can be achieved by the optimal allocation of available collateral. They have also shown that improved performance in the range of three to 12 basis points can be attained on a typical portfolio of a bank’s collateral requirements and inventory by implementing a collateral optimisation programme.

The benefits of collateral optimisation techniques go beyond simply minimising the cost of posted collateral. They can also maximise the liquidity potential of the available inventory. This is important for banks that will be subject to the liquidity coverage ratio and the net-stable funding ratio. These are binding constraints on short-term and medium- to long-term liquidity that force banks to set aside more assets. Collateral optimisation can mobilise more liquidity and enable more business.

The four key goals of optimised collateral allocation are:
Minimise the cost of collateral;
Maximise liquidity or funding capacity of the retained inventory;
Minimise funding costs by identifying the optimal funding venue for the inventory; and
Automate the allocation process.

Common strategies

Two strategies for post-trade collateral optimisation are typically considered: collateral rebalancing and inventory optimisation. In practice, both can be performed continuously, but for illustration purposes, it is meaningful to assume a two-step approach. Both strategies are applied in the post-trade world where collateral has already been exchanged. The core principle of post-trade optimisation techniques is to restructure the collateral portfolio by analysing current collateral requirements, collateral that has already been posted, and the assets available to the firm, and then proposing substitutions and new allocations in order to achieve an economic benefit.

Although the target function of post-trade optimisation methods may vary by firm or market situation, collateral rebalancing and inventory optimisation target the goal of minimising the cost of funding. Other goals of collateral optimisation are to minimise the balance sheet impact of collateral, maximise liquidity through haircut optimisation or simply to automate the recall of posted collateral that has gone special. The optimisation procedure is independent of the target function and always follows the same pattern, regardless of the function to be maximised.

The whitepaper provides a detailed commentary on the approach and realisable benefits of these optimisation techniques, including:
Techniques for measuring the cost of use of inventory positions;
Constraints to be considered in the optimisation process;
Allocation methodologies;
Inventory optimisation objectives and methodology; and
How to measure and quantify the benefits.

Outlook

Collateral optimisation techniques are relevant now and will evolve as the market and regulations change. Various collateral approaches can have different impacts on the leverage ratio, so impacts on the leverage ratio will equate to impacts on the optimisation problem.

The inclusion of mandatory bilateral margining of non-centrally cleared derivatives can be easily mapped into the approach that we have outlined in the whitepaper. Indeed, the broader eligibility buckets under the regulatory proposals compared to the often narrow eligibility sets in legacy credit support annexes will enhance the potential savings from optimisation.

However, it is important to note that theoretical funding costs and realised funding costs differ. This also implies that ‘xVA’, and funding valuation adjustment (FVA) costs in particular, differ when calculated pre-deal based on optimal availabilities of assets and ex-post.

The solution to this emerging field is the establishment of collateral transfer pricing. The development of this pricing mechanism is best owned by a collateral trading desk and best realised in an enterprise collateral management IT solution.
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