Tagging trades to the correct Master Agreement – also known as legal agreement linkage, master agreement stamping, or trade stamping – is a fundamental process for financial institutions engaged in derivatives trading. Inaccurate or incorrect Trade Tagging affects the amount of collateral the institution requires from its trading counterparties (for credit risk protection) and the amount of capital that must be set held to meet regulatory requirements. It impacts liquidity. It compromises regulatory reporting and the validity of capital requirement calculations. It undermines relationships with both counterparties and clients. Plus, of course, it leads to excessive and time-consuming rework to investigate trades that are not correctly managed in line with their terms (in some cases, unknowingly).
Some institutions have hundreds of thousands of trade tagging exceptions to manually investigate, which only represent the trades that are flagged as incorrect. There also exists an unknown number of trades that have unknowingly been incorrectly tagged representing a significant sleeping risk.
So why are the vast majority of financial institutions still sweeping the issue of inept and inadequate tagging of trades under the carpet? Why is no one taking responsibility for this critical issue? Why are credit, collateral, document, legal and data teams all expecting someone else to solve the problem?
As regulators step up their concerns, Eric Mueller, Managing Director and COO, and Emma Wooldridge, Consultant, D2 Legal Technology, outline the need for ownership, end to end visibility and collaboration between all the relevant stakeholders.
Dangerously Disingenuous
Financial institutions are aware of the problems associated with linking trades to the correct Master Agreement, such as the ISDA Master Agreement, the Global Master Repurchase Agreement (published by ICMA and SIFMA), the Global Master Securities Lending Agreement (published by ISLA), the EFET Gas and Power Agreements (published by European Federation of Energy Traders) and the NAESB (published by the North American Energy Standards Board). Most have more than a suspicion that poor process design and data governance across multiple business areas are leading to significant issues, affecting key aspects of every institution’s risk management – from liquidity to capital adequacy and collateral management.
Amazingly few banks, for example, can link trades to the right master trading agreement at the point of trade, relying instead on manual (or at best, semi-automated) post-trade business processes. Despite the fanfare of artificial intelligence and its use in the financial services area, trade tagging feels forgotten – as if it were too easy a problem to concern ourselves with. Yet this post-trade matching process can only be successful if data is complete and accurate. With data sourced from multiple locations, accuracy and completeness are rare. Effective trade tagging requires consolidating information from front-office trade data, post-trade confirmations, counterparty data, and legal agreement data. With inconsistent definitions and out of date information, data quality and governance, problems are not only widespread – they are inevitable.
The day-to-day and strategic implications of inadequate trade tagging are wide-reaching. How many collateral teams are enduring difficult conversations with clients due to an inability to make the right margin calls? How often are counterparty relationships soured due to inaccurate exposure information that prevents trading? What is the impact on the front office when the netting data set is polluted, or netting flags are switched off as a result of making incorrect calls? How often are regulators demanding improvements linked to inaccurate reporting of their Risk Weighted Asset (RWA)?
The issues are endemic and are adding very significant risk and cost, yet the problem is still downplayed by many organisations.
Head in the Sand
Indeed, far too many financial institutions appear to be in denial about the scale of the problem. Many organisations have invested in some form of automated trade linkage, for example, but is the business genuinely confident in the quality of the process? Many institutions have hundreds of thousands of exceptions that require teams of people to be diverted from other tasks to undertake complex and time-consuming investigations to achieve a manual match. Rework is demanding, requiring collaboration with multiple departments, including legal, credit, and documentation, in order to resolve inconsistencies.
In many cases there is enormous resistance to making changes to the data, with each department focused, understandably, on meeting its own objectives rather than recognising the importance of – and its part in – the complete, end-to-end process. Yet the result is daily firefighting, endless finger pointing and blame passing, and zero progress in achieving either better processes or data consistency.
This culture of lack of ownership and responsibility is also creating a very serious level of sleeping risk. With automated systems generating so many exceptions, there is a disturbing tendency to accept any match of trade to Master Agreement, even when there is a suspicion that the match is incorrect. The problems created by these false positives will only surface when hitting close out, typically at a time of financial and/or counterparty crisis. Discovering at this point that the institution doesn’t have adequate collateral or that there is no way to recoup owed monies is far too late and the market ramifications are extremely concerning.
Acknowledge the Problem
Any institution that still believes its processes for trade tagging are not a problem needs to answer three questions.
Who is responsible for the end-to-end process and the accuracy of data? Without ownership and governance, no financial institution will achieve the accuracy required to reduce costs and risk.
Is there a strategic drive to transform the accuracy of trade tagging, with good data and processes across the business? Or are problems with trade tagging dealt with on an isolated basis, often to reappear elsewhere across the business?
Are teams still working as siloes or is there effective collaboration and communication, supported by a forum to facilitate further improvements? Any cross-business process is only as good as the weakest link. Without constant vigilance, central oversight and strong collaboration between all stakeholders, including credit, collateral, legal, onboarding, trade, data and documentation, to ensure any data and system changes consider the impact on trade tagging, the process quality can quickly deteriorate.
Conclusion
There is no quick resolution to the problem of allocating trades to the correct Master Agreement. Improving the diverse underpinning data sources and creating an efficient, trusted trade tagging process will demand investment and cultural change. It will require an end to the blame game and a department or individual to step up and take ownership. It will need all stakeholders to engage and collaborate.
The first step, however, must be an acknowledgment that the current process is not only inadequate; it is adding both risk and cost to the business.