Toning up in the collateral gym
21 February 2023
In the first of two articles on collateral management strategy, Bob Currie examines advances in collateral optimisation and electronic negotiation of collateral schedules
Image: stock.adobe.com/studiostoks
The prominent challenges in collateral management have changed relatively little over several decades. Firms labour to reduce collateral fragmentation across product silos and geographical locations. They invest to improve optimisation, to unlock underutilised collateral pools and to enhance collateral mobility. They work to eliminate STP breaks and settlement fails, while minimising the risk of post-trade disputes. And, more generally, they work to deliver an integrated front-to-back process from trade initiation across the contract lifecycle.
While the song remains broadly the same, the tempo has become distinctly more lively. Regulatory drivers, macroeconomic conditions and geopolitical uncertainties have each played a role in forcing firms to upgrade their collateral ecosystems and take an enterprise-level view of their collateral inventory and financing requirements.
Regulatory changes are forcing a new community of firms into the collateral world and requiring established players to minimise balance sheet cost and remove operational drag. With an expanding range of firms required to manage initial margin (IM) and variation margin (VM), as they have fallen into scope of Uncleared Margin Rules (UMR), these firms are looking for automation, better inventory management, as well as innovative new ways of managing these priorities.This is bringing new utilities to the market and presenting exciting opportunities for triparty and for other specialist vendors in the collateral gymnasium.
Comprehensive rethink
Sophie Marnhier-Foy, global head of product marketing at Adenza, indicates that the conjunction of higher volumes of UMR compliant trades, rising interest rates and increased standardised initial margin methodology (SIMM) weights and correlation has created a perfect storm for companies that are impacted.
In many cases, firms did not initially gauge the full impact of the UMR 鈥� partly as a consequence of the progressive compliance rule, where only new trades are in scope of the new regulation, and partly the result of UMR thresholds, where firms only came into scope when their aggregate average notional amount passed a specified level (for example, US$50 billion under Phase 5, US$8 billion under Phase 6). By the time that they recognised the full impact of this regulation, suggests Marnhier-Foy, it was often too late to quickly adapt their approach.
Eric Badger, BNY Mellon鈥檚 global head of sales and relationship management for clearance and collateral management, notes that, in the not-too-distant past, collateral mobility was limited and optimisation was principally a back-office function, essentially encompassing only a cheapest-to-deliver methodology. In contrast, optimisation is now more front-office focused, entailing complex decisions across a wide range of variables that extend beyond just security type, eligibility and counterparty.
In making this point, Badger reminds us that optimisation tends to be interpreted differently depending on where a firm sits in the trade lifecycle. 鈥淭raditionally, our focus has been on post-settlement optimisation,鈥� he says. 鈥淗owever we are well beyond the days of a one size fits all approach. Clients utilise a combination of our data driven and automated services in combination with vendor solutions and their own technology capabilities.鈥�
For J.P. Morgan鈥檚 head of collateral services for EMEA Graham Gooden, there is no doubt that optimisation as a discipline has advanced a long way over the past five to 10 years. 鈥淲hen we first ran our collateralisation optimisation engine in the early 2000s, it took up to a day to run the algorithm to completion,鈥� he says. 鈥淲e are now on our fourth or fifth generation optimisation engine and this is embedded in the triparty platform, providing optimisation of a client鈥檚 collateral inventory in close to real time.鈥�
Client requirements may differ substantially across buy- and sell-side firms regarding how they use this optimisation capability. 鈥淪ome users send details of their collateral inventory and collateral eligibility schedules directly to J.P. Morgan 鈥� via API or as a data file using secure FTP (SFTP) 鈥� using our optimisation services to provide analysis, often to a highly granular level, of how best to allocate these collateral holdings against their risk exposures and trading objectives,鈥� says Gooden.
Other clients may use a hybrid approach, where they source collateral and valuation services from one or multiple vendors, as well as using J.P. Morgan as a collateral agent. 鈥淚n this situation, we may receive the data file directly from the vendor,鈥� says Gooden. 鈥淲e have done a lot of configuration work with the leading collateral management vendors 鈥� in terms of managing eligibility schedules, data reconciliation etc 鈥� and this ensures good STP rates and high levels of operational efficiency in supporting these hybrid arrangements.鈥�
Looking across the industry, BNY Mellon鈥檚 Badger notes that clients are at substantially different stages of their optimisation journey. Some firms are already well advanced with central funding and optimisation teams and have the requisite technology in place to support it. Others are earlier in their journey, bringing different trading desks together and investing in modernising their systems.
This challenge is typically more complex when optimisation needs to be applied across multiple legal entities and products. Clients also differ significantly in terms of the constraints that they face, with some firms having more difficulties than others in bringing internal data and systems together.
For Adenza鈥檚 Marnhier-Foy, UMR has not just been a compliance exercise. 鈥淚t changes the collateral ecosystem and requires proactive optimisation,鈥� she explains. However, this again raises the question of what we mean by optimisation. There are many factors contributing to a final increase in funding costs. Some, she suggests, are exogeneous and cannot be controlled 鈥� for example, market volatility affecting the SIMM backtesting and resulting in higher margin numbers, or regulatory scrutiny of procyclical factors which may have a domino effect on margin methodologies, including SIMM.
However, other parameters can be both controlled and anticipated. This confirms the benefit of an holistic approach to risk inputs, margin exposure and collateral funding costs across a firm鈥檚 portfolio. 鈥淎n optimal optimisation process is not conducted ad hoc utilising isolated factor inputs,鈥� she says. 鈥淩ather, it requires a logical series of simulations, pre- and post-trade, for live and legacy portfolios.鈥�
In delivering this methodology, Marnhier-Foy believes that the primary advances will not be made simply by rolling out new tools. Rather, this demands a comprehensive rethink of the collateral paradigm and its related IT ecosystem. The final implementation phase of UMR, alongside the new ISDA SIMM 2.5 parameters, might be an ideal trigger for this development.
Macro backdrop
After an extended period of low interest rates and abundant liquidity supported by central bank asset purchase programmes, H2 2022 and the initial months of 2023 have delivered rising inflation and monetary tightening, with the expectation that central banks will step up the unwind of their asset purchase programmes (APPs) as the year progresses.
鈥淚n this environment, we have been focused as a service provider in helping triparty clients to make the most effective use of their collateral inventory, helping them to optimise collateral allocation and to minimise the friction associated with collateral transfers,鈥� says J.P. Morgan鈥檚 Gooden.
Against a background of high price volatility and strong SFT trading volumes, one feature has been a need to ensure high standards of operational efficiency across the SFT transaction lifecycle, including collateral settlement.
The market noted a sharp rise in gilt repo volumes during late September and early October, particularly following the spike in gilt yields after the UK mini-budget on 23 September. However, Gooden indicates that the bank did not experience a significant rise in settlement fail rates. 鈥淭he SFT transaction value chain and collateral settlement procedures are highly automated, and these high STP rates have been important in minimising settlement fails during recent periods of high market volatility and spikes in trading activity,鈥� he says.
However, if we consider a longer timeframe, taking in the uncertainties created by Russia's military action in Ukraine, there is evidence of disruption to settlement efficiency in some parts of the market. Gareth Jones, CEO of Euroclear GlobalCollateral, recounts a reduction in settlement efficiency 鈥渂y a couple of percentage points鈥� at the end of 2021 and this declined further with the Russian invasion of Ukraine in February 2022. Although settlement efficiency had improved by Q4 2022, it had not returned to where it was in the first half of 2021.
Speaking at a 网爆吃瓜 Finance Times Technology Symposium at the end of 2022, Jones explained that 鈥渢he reduction in settlement efficiency is typically associated with volatility and higher trading volumes, but this has been sustained for a while, which indicates that there is some scarcity of collateral and securities liquidity out there.鈥� Against this background, Jones indicates that Euroclear鈥檚 specialist borrowing programmes 鈥� GCA for HQLA and Autoborrow, which are linked to the firm鈥檚 settlement algorithm 鈥� recorded record volumes over the period.
Reflecting on this experience, the European 网爆吃瓜 Markets Authority (ESMA) notes how recent stresses linked to liability-driven investment (LDI) strategies that invest in GBP-denominated government bonds illustrate how quickly liquidity risks can crystallise. This sharp rise in gilt yields in late September and early October, in the wake of the UK mini-budget, accentuated liquidity pressures on heavily leveraged LDI funds. Margin requests surged on repo transactions collateralised by government bonds and interest-rate derivatives.
LDI funds attempted to sell sovereign bonds in their search for liquidity but the market was unable to absorb this volume of bond sales, prompting the Bank of England to intervene to support the sovereign bond market via a targeted short-term asset purchase programme.
With these developments, ESMA indicates in its recent Trends, Risks and Vulnerabilities Risk Monitor report (ESMA,10 February 2023) that its systemic stress indicator, a refinement of the ECB composite indicator of systemic stress, has hit levels higher than those witnessed during the pandemic, particularly owing to these high volatility levels in EU sovereign and corporate bond markets.
From this experience for LDI funds, a number of firms now recognise just how constrained they were with manual processes and the risks presented by these pinch points, observes HQLAX systems architect Martin O鈥機onnell. This presents major opportunities for vendors 鈥� opportunities that do not tend to come along very often. 鈥淚t is clear from this experience that firms need to invest in automation,鈥� he says. 鈥淭his is evident from successive years of regulatory adaptation and the investment that is necessary to eliminate the operational risk presented by manual processes.鈥�
For BNY Mellon鈥檚 Badger, bouts of market volatility, headline defaults and the shadow of global macro uncertainty has in many ways reinforced the core value of the triparty collateral management service which mitigates counterparty credit risk and provides operational efficiencies.
Institutions require greater access to liquidity through a more diverse range of funding sources to prepare for rising costs, increasing volatility, and to offset the risk of potential liquidity challenges with existing partners and channels. This is amplified by regulatory frameworks that put greater pressure on dealer balance sheets globally.
鈥淲e continue to observe a growth trend in collateral markets globally, including support for derivatives margin and repo activity,鈥� he says. 鈥淭he uncleared margin regulations have helped to grow our collateral network beyond its core financial institution base to include traditional and alternative asset managers, sovereign wealth managers and insurance companies.鈥�
BNP Paribas has been offering collateral management services as a middle-office collateral manager since the early 2010s, initially focusing primarily on OTC derivatives margining. 鈥淎s the success of the franchise has grown, it became apparent that we needed to support our clients beyond bilateral collateral,鈥� says J茅r么me Blais, co-head of triparty collateral services at BNP Paribas 网爆吃瓜 Services. More and more clients 鈥� especially on the buy-side 鈥� highlighted their growing appetite to have access to a triparty collateral solution for securities finance and derivatives transactions, while retaining the benefits of the full service package that BNP Paribas already offered as an asset servicer.
鈥淲e recognised at an early point that the sell-side was seeking two primary goals,鈥� says Blais. 鈥淥ne was to access additional liquidity providers that are using BNP Paribas as a custodian and depository bank. The second is to leverage triparty collateral management and benefit from enhanced efficiency, increased automation and reduced operational risk.鈥�
鈥淭his was a natural move for BNP Paribas as a service provider with a longstanding global footprint with both sell- and buy-side players,鈥� he says.
With an expanding community of firms now required under UMR to post IM and VM against their derivatives exposures, Gooden indicates that J.P. Morgan has built on the investments it has made in its triparty solution to enhance its service provision for the derivatives market.
鈥淐onfronted by high levels of pricing volatility and concerns around collateral scarcity, clients have been exploring opportunities to mobilise a wider range of collateral types to cover their SFT and derivatives exposures,鈥� explains Gooden. While some UMR counterparties continue to use cash to meet their variation margin requirements, others are mobilising a broader mix of securities to meet both IM and VM requirements, including more extensive use of corporate bonds as collateral.
鈥淏uy-side firms have been well-established users of triparty services for many years as cash providers through repo transactions,鈥� adds Gooden. 鈥淲ith UMR, a growing number of buy-side firms are now using triparty to help them to post IM in line with their UMR obligations. Through our triparty service, this enables firms to reuse collateral that they receive through repo transactions and to repost UMR-eligible securities as collateral to derivatives counterparties.鈥�
鈥淭his has created new efficiencies for buy-side clients, leveraging our triparty solution to support their financing relationships and adding the ability to post collateral bilaterally to UMR counterparties," says Gooden. "Bringing these two areas together creates valuable gains for buy-side firms through rehypothecation and other efficiency benefits.鈥�
Similarly, Blais indicates that BNP Paribas is helping more and more buy-side clients to access triparty collateral management 鈥� firms that would have struggled to do so otherwise. 鈥淚t can be a massive challenge for the buy-side in general, and for asset managers in particular, to engage with a separate custodian simply to enrol into a triparty collateral programme,鈥� he says.鈥漁ur buy-side clients can now enhance their collateral operations using our triparty collateral services as part of the full BNP Paribas suite of services to which they are already connected.鈥�
Blais also indicates that the bank鈥檚 positioning as a multi-local and global player has been important in helping its clients to adopt the solution more easily. 鈥淚n the case of UMR, for instance, our clients were quick to see the benefits of holding their collateral in their domestic market, being able to segregate their collateral under local law and to maintain their relationship with their domestic BNP Paribas branch, while benefiting from the product coverage of a global player.鈥�
Electronic collateral schedules
One parallel area where there has been significant progress is in creating electronic representations of collateral schedules and enabling collateral schedule negotiation to be managed digitally. 鈥淲e have evolved from word-based agreements, written in a text editor or spreadsheet, to supporting digitised eligibility templates via an online portal,鈥� says J.P. Morgan鈥檚 Gooden.
J.P. Morgan is also working with triparty clients to communicate collateral eligibility directly using APIs, enabling data transfer directly between collateral management systems. Collectively, these mechanisms offer machine-readable collateral schedules, improving STP rates and reducing the risk associated with counterparties managing collateralised lending relationships using outdated eligibility schedules.
These developments have allowed triparty clients to adopt a more granular focus in terms of how they allocate collateral across specific counterparties 鈥� optimising their collateral inventory on an ISIN by ISIN basis, for example, with the ability to refine these collateral preferences intraday if they wish to.
BNY Mellon released a digital collateral schedule platform, known as RULE, in 2019, aiming to replace labour-intensive paper-based collateral negotiation processes that previously took weeks to finalise. The RULE platform is designed to allow counterparties to negotiate schedules and receive feedback electronically in real-time, thereby enhancing operational and trading workflows.
鈥淭he platform has had a transformational impact on how our clients interact with each other,鈥� says Badger. 鈥淣early all collateral schedules are created and executed electronically, which enables clients to react quickly to changing market conditions and risk appetite, and schedule amendments to existing rule sets are implemented immediately after electronic execution. There is an electronic audit trail and RULE has made it much easier for the schedules to be shared internally with Treasury and Risk stakeholders.鈥�
This platform played a key role in helping the bank to implement the latest phases of UMR, Badger explains, 鈥渟treamlining the onboarding process, cutting the negotiation time down to days and even hours in some cases, allowing BNY Mellon to successfully open thousands to meet the regulatory deadlines鈥�. New features are consistently being added to this platform, he notes, such as the introduction of APIs and the ability to make bulk amendments.
Clearstream has developed an artificial intelligence-based collateral eligibility negotiation and screening tool in collaboration with Brussels-based fintech Intelli-Select.
As we outlined in greater detail in October 2022 in an interview in SFT 314, this collateral tool, named Own Selection Criteria with Automated Reasoning (OSCAR), utilises Intelli-Select鈥檚 software, applying artificial intelligence strategies to evaluate collateral eligibility profiles when working with collateral baskets.
This will accelerate the time required for users to develop and negotiate individual collateral baskets through use of AI techniques, including knowledge representation and reasoning (KRR), machine learning and structured natural language processing (NLP). The AI methodology has been developed by Intelli-Select in collaboration with its academic partners at KU Leuven.
This creates a digital version of a collateral schedule which can be agreed with trade counterparties through a smart online interface. This enables users to create collateral schedules simply 鈥� through typing information into the online portal that is then read and digitised by OSCAR using natural language processing 鈥� enabling the user to match these collateral eligibility criteria electronically with counterparties and to trade within a matter of minutes, when this process would previously have taken several hours or days.
鈥淭his solution extends flexibility to build and amend collateral schedules quickly and simply,鈥� says Marton Szigeti, Clearstream鈥檚 head of collateral, lending and liquidity solutions (also interviewed in SFT Issue 319, 24 Jan 2023). 鈥淚f a user wishes to switch an asset out of a series of collateral baskets, this can be executed using OSCAR without pages of physical documentation and without an elongated legal approvals process.鈥�
鈥淚n our experience, a collateral schedule delivered through an excel file, a flat file for example, could require many thousands of if-else statements to represent electronically using traditional computing logic,鈥� explains Intelli-Select co-founder and CEO Bart Coppens.
Through applying KRR, Coppens indicates that the platform is able to identify the user鈥檚 collateral eligibility criteria and exclusions through applying automated reasoning, significantly improving the speed and efficiency of creating and applying collateral schedules. By identifying collateral preferences through keywords entered into the user interface, OSCAR will suggest eligible assets from the user鈥檚 inventory that may be used to build and negotiate collateral baskets.
For J茅r么me Petit, EMEA market specialist manager at Adenza, transparency across the firm is key to managing collateral requirements efficiently. For example, the collateral schedules, the collateral inventory and the cost of funding all need to be clearly visible to the front office. This requires tools plugged into the trading application to deliver the necessary data 鈥� for instance pre-trade analytics and what-if margin analysis, along with tools to understand the impact on the firm's credit risk.
More broadly, the engine needs to be flexible, such that it can be configured to meet the different associated workflows, supporting the lifecycle for different types of objects, trade and settlement messaging, the payments and the collateral movements, along with associated dashboards to monitor and manage these workflows. As far as possible, these workflows should be automated so that firms can focus on managing exceptions and STP breaks. 鈥淚t is key to have this STP connectivity front-to-back across the trade lifecycle and to counterparties and utilities,鈥� concludes Petit. 鈥淲e also need to look for scalability. Adopting an integrated front-to-back solution is key to optimising inventory and ensuring optimal collateral decisions.鈥�
While the song remains broadly the same, the tempo has become distinctly more lively. Regulatory drivers, macroeconomic conditions and geopolitical uncertainties have each played a role in forcing firms to upgrade their collateral ecosystems and take an enterprise-level view of their collateral inventory and financing requirements.
Regulatory changes are forcing a new community of firms into the collateral world and requiring established players to minimise balance sheet cost and remove operational drag. With an expanding range of firms required to manage initial margin (IM) and variation margin (VM), as they have fallen into scope of Uncleared Margin Rules (UMR), these firms are looking for automation, better inventory management, as well as innovative new ways of managing these priorities.This is bringing new utilities to the market and presenting exciting opportunities for triparty and for other specialist vendors in the collateral gymnasium.
Comprehensive rethink
Sophie Marnhier-Foy, global head of product marketing at Adenza, indicates that the conjunction of higher volumes of UMR compliant trades, rising interest rates and increased standardised initial margin methodology (SIMM) weights and correlation has created a perfect storm for companies that are impacted.
In many cases, firms did not initially gauge the full impact of the UMR 鈥� partly as a consequence of the progressive compliance rule, where only new trades are in scope of the new regulation, and partly the result of UMR thresholds, where firms only came into scope when their aggregate average notional amount passed a specified level (for example, US$50 billion under Phase 5, US$8 billion under Phase 6). By the time that they recognised the full impact of this regulation, suggests Marnhier-Foy, it was often too late to quickly adapt their approach.
Eric Badger, BNY Mellon鈥檚 global head of sales and relationship management for clearance and collateral management, notes that, in the not-too-distant past, collateral mobility was limited and optimisation was principally a back-office function, essentially encompassing only a cheapest-to-deliver methodology. In contrast, optimisation is now more front-office focused, entailing complex decisions across a wide range of variables that extend beyond just security type, eligibility and counterparty.
In making this point, Badger reminds us that optimisation tends to be interpreted differently depending on where a firm sits in the trade lifecycle. 鈥淭raditionally, our focus has been on post-settlement optimisation,鈥� he says. 鈥淗owever we are well beyond the days of a one size fits all approach. Clients utilise a combination of our data driven and automated services in combination with vendor solutions and their own technology capabilities.鈥�
For J.P. Morgan鈥檚 head of collateral services for EMEA Graham Gooden, there is no doubt that optimisation as a discipline has advanced a long way over the past five to 10 years. 鈥淲hen we first ran our collateralisation optimisation engine in the early 2000s, it took up to a day to run the algorithm to completion,鈥� he says. 鈥淲e are now on our fourth or fifth generation optimisation engine and this is embedded in the triparty platform, providing optimisation of a client鈥檚 collateral inventory in close to real time.鈥�
Client requirements may differ substantially across buy- and sell-side firms regarding how they use this optimisation capability. 鈥淪ome users send details of their collateral inventory and collateral eligibility schedules directly to J.P. Morgan 鈥� via API or as a data file using secure FTP (SFTP) 鈥� using our optimisation services to provide analysis, often to a highly granular level, of how best to allocate these collateral holdings against their risk exposures and trading objectives,鈥� says Gooden.
Other clients may use a hybrid approach, where they source collateral and valuation services from one or multiple vendors, as well as using J.P. Morgan as a collateral agent. 鈥淚n this situation, we may receive the data file directly from the vendor,鈥� says Gooden. 鈥淲e have done a lot of configuration work with the leading collateral management vendors 鈥� in terms of managing eligibility schedules, data reconciliation etc 鈥� and this ensures good STP rates and high levels of operational efficiency in supporting these hybrid arrangements.鈥�
Looking across the industry, BNY Mellon鈥檚 Badger notes that clients are at substantially different stages of their optimisation journey. Some firms are already well advanced with central funding and optimisation teams and have the requisite technology in place to support it. Others are earlier in their journey, bringing different trading desks together and investing in modernising their systems.
This challenge is typically more complex when optimisation needs to be applied across multiple legal entities and products. Clients also differ significantly in terms of the constraints that they face, with some firms having more difficulties than others in bringing internal data and systems together.
For Adenza鈥檚 Marnhier-Foy, UMR has not just been a compliance exercise. 鈥淚t changes the collateral ecosystem and requires proactive optimisation,鈥� she explains. However, this again raises the question of what we mean by optimisation. There are many factors contributing to a final increase in funding costs. Some, she suggests, are exogeneous and cannot be controlled 鈥� for example, market volatility affecting the SIMM backtesting and resulting in higher margin numbers, or regulatory scrutiny of procyclical factors which may have a domino effect on margin methodologies, including SIMM.
However, other parameters can be both controlled and anticipated. This confirms the benefit of an holistic approach to risk inputs, margin exposure and collateral funding costs across a firm鈥檚 portfolio. 鈥淎n optimal optimisation process is not conducted ad hoc utilising isolated factor inputs,鈥� she says. 鈥淩ather, it requires a logical series of simulations, pre- and post-trade, for live and legacy portfolios.鈥�
In delivering this methodology, Marnhier-Foy believes that the primary advances will not be made simply by rolling out new tools. Rather, this demands a comprehensive rethink of the collateral paradigm and its related IT ecosystem. The final implementation phase of UMR, alongside the new ISDA SIMM 2.5 parameters, might be an ideal trigger for this development.
Macro backdrop
After an extended period of low interest rates and abundant liquidity supported by central bank asset purchase programmes, H2 2022 and the initial months of 2023 have delivered rising inflation and monetary tightening, with the expectation that central banks will step up the unwind of their asset purchase programmes (APPs) as the year progresses.
鈥淚n this environment, we have been focused as a service provider in helping triparty clients to make the most effective use of their collateral inventory, helping them to optimise collateral allocation and to minimise the friction associated with collateral transfers,鈥� says J.P. Morgan鈥檚 Gooden.
Against a background of high price volatility and strong SFT trading volumes, one feature has been a need to ensure high standards of operational efficiency across the SFT transaction lifecycle, including collateral settlement.
The market noted a sharp rise in gilt repo volumes during late September and early October, particularly following the spike in gilt yields after the UK mini-budget on 23 September. However, Gooden indicates that the bank did not experience a significant rise in settlement fail rates. 鈥淭he SFT transaction value chain and collateral settlement procedures are highly automated, and these high STP rates have been important in minimising settlement fails during recent periods of high market volatility and spikes in trading activity,鈥� he says.
However, if we consider a longer timeframe, taking in the uncertainties created by Russia's military action in Ukraine, there is evidence of disruption to settlement efficiency in some parts of the market. Gareth Jones, CEO of Euroclear GlobalCollateral, recounts a reduction in settlement efficiency 鈥渂y a couple of percentage points鈥� at the end of 2021 and this declined further with the Russian invasion of Ukraine in February 2022. Although settlement efficiency had improved by Q4 2022, it had not returned to where it was in the first half of 2021.
Speaking at a 网爆吃瓜 Finance Times Technology Symposium at the end of 2022, Jones explained that 鈥渢he reduction in settlement efficiency is typically associated with volatility and higher trading volumes, but this has been sustained for a while, which indicates that there is some scarcity of collateral and securities liquidity out there.鈥� Against this background, Jones indicates that Euroclear鈥檚 specialist borrowing programmes 鈥� GCA for HQLA and Autoborrow, which are linked to the firm鈥檚 settlement algorithm 鈥� recorded record volumes over the period.
Reflecting on this experience, the European 网爆吃瓜 Markets Authority (ESMA) notes how recent stresses linked to liability-driven investment (LDI) strategies that invest in GBP-denominated government bonds illustrate how quickly liquidity risks can crystallise. This sharp rise in gilt yields in late September and early October, in the wake of the UK mini-budget, accentuated liquidity pressures on heavily leveraged LDI funds. Margin requests surged on repo transactions collateralised by government bonds and interest-rate derivatives.
LDI funds attempted to sell sovereign bonds in their search for liquidity but the market was unable to absorb this volume of bond sales, prompting the Bank of England to intervene to support the sovereign bond market via a targeted short-term asset purchase programme.
With these developments, ESMA indicates in its recent Trends, Risks and Vulnerabilities Risk Monitor report (ESMA,10 February 2023) that its systemic stress indicator, a refinement of the ECB composite indicator of systemic stress, has hit levels higher than those witnessed during the pandemic, particularly owing to these high volatility levels in EU sovereign and corporate bond markets.
From this experience for LDI funds, a number of firms now recognise just how constrained they were with manual processes and the risks presented by these pinch points, observes HQLAX systems architect Martin O鈥機onnell. This presents major opportunities for vendors 鈥� opportunities that do not tend to come along very often. 鈥淚t is clear from this experience that firms need to invest in automation,鈥� he says. 鈥淭his is evident from successive years of regulatory adaptation and the investment that is necessary to eliminate the operational risk presented by manual processes.鈥�
For BNY Mellon鈥檚 Badger, bouts of market volatility, headline defaults and the shadow of global macro uncertainty has in many ways reinforced the core value of the triparty collateral management service which mitigates counterparty credit risk and provides operational efficiencies.
Institutions require greater access to liquidity through a more diverse range of funding sources to prepare for rising costs, increasing volatility, and to offset the risk of potential liquidity challenges with existing partners and channels. This is amplified by regulatory frameworks that put greater pressure on dealer balance sheets globally.
鈥淲e continue to observe a growth trend in collateral markets globally, including support for derivatives margin and repo activity,鈥� he says. 鈥淭he uncleared margin regulations have helped to grow our collateral network beyond its core financial institution base to include traditional and alternative asset managers, sovereign wealth managers and insurance companies.鈥�
BNP Paribas has been offering collateral management services as a middle-office collateral manager since the early 2010s, initially focusing primarily on OTC derivatives margining. 鈥淎s the success of the franchise has grown, it became apparent that we needed to support our clients beyond bilateral collateral,鈥� says J茅r么me Blais, co-head of triparty collateral services at BNP Paribas 网爆吃瓜 Services. More and more clients 鈥� especially on the buy-side 鈥� highlighted their growing appetite to have access to a triparty collateral solution for securities finance and derivatives transactions, while retaining the benefits of the full service package that BNP Paribas already offered as an asset servicer.
鈥淲e recognised at an early point that the sell-side was seeking two primary goals,鈥� says Blais. 鈥淥ne was to access additional liquidity providers that are using BNP Paribas as a custodian and depository bank. The second is to leverage triparty collateral management and benefit from enhanced efficiency, increased automation and reduced operational risk.鈥�
鈥淭his was a natural move for BNP Paribas as a service provider with a longstanding global footprint with both sell- and buy-side players,鈥� he says.
With an expanding community of firms now required under UMR to post IM and VM against their derivatives exposures, Gooden indicates that J.P. Morgan has built on the investments it has made in its triparty solution to enhance its service provision for the derivatives market.
鈥淐onfronted by high levels of pricing volatility and concerns around collateral scarcity, clients have been exploring opportunities to mobilise a wider range of collateral types to cover their SFT and derivatives exposures,鈥� explains Gooden. While some UMR counterparties continue to use cash to meet their variation margin requirements, others are mobilising a broader mix of securities to meet both IM and VM requirements, including more extensive use of corporate bonds as collateral.
鈥淏uy-side firms have been well-established users of triparty services for many years as cash providers through repo transactions,鈥� adds Gooden. 鈥淲ith UMR, a growing number of buy-side firms are now using triparty to help them to post IM in line with their UMR obligations. Through our triparty service, this enables firms to reuse collateral that they receive through repo transactions and to repost UMR-eligible securities as collateral to derivatives counterparties.鈥�
鈥淭his has created new efficiencies for buy-side clients, leveraging our triparty solution to support their financing relationships and adding the ability to post collateral bilaterally to UMR counterparties," says Gooden. "Bringing these two areas together creates valuable gains for buy-side firms through rehypothecation and other efficiency benefits.鈥�
Similarly, Blais indicates that BNP Paribas is helping more and more buy-side clients to access triparty collateral management 鈥� firms that would have struggled to do so otherwise. 鈥淚t can be a massive challenge for the buy-side in general, and for asset managers in particular, to engage with a separate custodian simply to enrol into a triparty collateral programme,鈥� he says.鈥漁ur buy-side clients can now enhance their collateral operations using our triparty collateral services as part of the full BNP Paribas suite of services to which they are already connected.鈥�
Blais also indicates that the bank鈥檚 positioning as a multi-local and global player has been important in helping its clients to adopt the solution more easily. 鈥淚n the case of UMR, for instance, our clients were quick to see the benefits of holding their collateral in their domestic market, being able to segregate their collateral under local law and to maintain their relationship with their domestic BNP Paribas branch, while benefiting from the product coverage of a global player.鈥�
Electronic collateral schedules
One parallel area where there has been significant progress is in creating electronic representations of collateral schedules and enabling collateral schedule negotiation to be managed digitally. 鈥淲e have evolved from word-based agreements, written in a text editor or spreadsheet, to supporting digitised eligibility templates via an online portal,鈥� says J.P. Morgan鈥檚 Gooden.
J.P. Morgan is also working with triparty clients to communicate collateral eligibility directly using APIs, enabling data transfer directly between collateral management systems. Collectively, these mechanisms offer machine-readable collateral schedules, improving STP rates and reducing the risk associated with counterparties managing collateralised lending relationships using outdated eligibility schedules.
These developments have allowed triparty clients to adopt a more granular focus in terms of how they allocate collateral across specific counterparties 鈥� optimising their collateral inventory on an ISIN by ISIN basis, for example, with the ability to refine these collateral preferences intraday if they wish to.
BNY Mellon released a digital collateral schedule platform, known as RULE, in 2019, aiming to replace labour-intensive paper-based collateral negotiation processes that previously took weeks to finalise. The RULE platform is designed to allow counterparties to negotiate schedules and receive feedback electronically in real-time, thereby enhancing operational and trading workflows.
鈥淭he platform has had a transformational impact on how our clients interact with each other,鈥� says Badger. 鈥淣early all collateral schedules are created and executed electronically, which enables clients to react quickly to changing market conditions and risk appetite, and schedule amendments to existing rule sets are implemented immediately after electronic execution. There is an electronic audit trail and RULE has made it much easier for the schedules to be shared internally with Treasury and Risk stakeholders.鈥�
This platform played a key role in helping the bank to implement the latest phases of UMR, Badger explains, 鈥渟treamlining the onboarding process, cutting the negotiation time down to days and even hours in some cases, allowing BNY Mellon to successfully open thousands to meet the regulatory deadlines鈥�. New features are consistently being added to this platform, he notes, such as the introduction of APIs and the ability to make bulk amendments.
Clearstream has developed an artificial intelligence-based collateral eligibility negotiation and screening tool in collaboration with Brussels-based fintech Intelli-Select.
As we outlined in greater detail in October 2022 in an interview in SFT 314, this collateral tool, named Own Selection Criteria with Automated Reasoning (OSCAR), utilises Intelli-Select鈥檚 software, applying artificial intelligence strategies to evaluate collateral eligibility profiles when working with collateral baskets.
This will accelerate the time required for users to develop and negotiate individual collateral baskets through use of AI techniques, including knowledge representation and reasoning (KRR), machine learning and structured natural language processing (NLP). The AI methodology has been developed by Intelli-Select in collaboration with its academic partners at KU Leuven.
This creates a digital version of a collateral schedule which can be agreed with trade counterparties through a smart online interface. This enables users to create collateral schedules simply 鈥� through typing information into the online portal that is then read and digitised by OSCAR using natural language processing 鈥� enabling the user to match these collateral eligibility criteria electronically with counterparties and to trade within a matter of minutes, when this process would previously have taken several hours or days.
鈥淭his solution extends flexibility to build and amend collateral schedules quickly and simply,鈥� says Marton Szigeti, Clearstream鈥檚 head of collateral, lending and liquidity solutions (also interviewed in SFT Issue 319, 24 Jan 2023). 鈥淚f a user wishes to switch an asset out of a series of collateral baskets, this can be executed using OSCAR without pages of physical documentation and without an elongated legal approvals process.鈥�
鈥淚n our experience, a collateral schedule delivered through an excel file, a flat file for example, could require many thousands of if-else statements to represent electronically using traditional computing logic,鈥� explains Intelli-Select co-founder and CEO Bart Coppens.
Through applying KRR, Coppens indicates that the platform is able to identify the user鈥檚 collateral eligibility criteria and exclusions through applying automated reasoning, significantly improving the speed and efficiency of creating and applying collateral schedules. By identifying collateral preferences through keywords entered into the user interface, OSCAR will suggest eligible assets from the user鈥檚 inventory that may be used to build and negotiate collateral baskets.
For J茅r么me Petit, EMEA market specialist manager at Adenza, transparency across the firm is key to managing collateral requirements efficiently. For example, the collateral schedules, the collateral inventory and the cost of funding all need to be clearly visible to the front office. This requires tools plugged into the trading application to deliver the necessary data 鈥� for instance pre-trade analytics and what-if margin analysis, along with tools to understand the impact on the firm's credit risk.
More broadly, the engine needs to be flexible, such that it can be configured to meet the different associated workflows, supporting the lifecycle for different types of objects, trade and settlement messaging, the payments and the collateral movements, along with associated dashboards to monitor and manage these workflows. As far as possible, these workflows should be automated so that firms can focus on managing exceptions and STP breaks. 鈥淚t is key to have this STP connectivity front-to-back across the trade lifecycle and to counterparties and utilities,鈥� concludes Petit. 鈥淲e also need to look for scalability. Adopting an integrated front-to-back solution is key to optimising inventory and ensuring optimal collateral decisions.鈥�
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