*Published in Securities Finance Times Technology Annual 2021

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Industry-wide standards are halfway there, but AcadiaSoft’s Roland Lichters believes the final stages of UMR provide a golden opportunity to adopt much needed standards across the board

Does standardisation in over-the-counter (OTC) derivatives matter? For years, regulators and industry organisations have lobbied for a higher degree of standardisation in the derivatives industry to create more transparency. While one could argue that the issue is far too complicated to tackle, the industry has slowly been making strides towards standardisation since the financial crisis. The adoption of industry-wide standards would provide important guardrails to prevent another financial crisis from happening in the future.

Lessons learned from the financial crisis

The financial crisis demonstrated how damaging the lack of standardisation was for the derivatives space. There was huge innovation in derivatives leading up to 2007, much of it aimed at the disaggregation of risk and the ability to move it around freely within the financial system. Around the same time, new instrument types and new asset classes emerged, particularly around credit, interest rates and equities. This allowed financial institutions to disaggregate risk and move it from one place to another where it would be best managed, but this also gave rise to increasing complexity. Here’s a prime example of the lack of standardisation endemic to the industry: it has been reported that there are over 250 different derivative types, but in fact no one actually knows the real figure because there is no comprehensive naming system for OTC derivatives.

One of the big issues that emerged during the crisis was the failure to anticipate the huge amount of counterparty risk that was being built up by the risk transfer. If risk is transferred from one institution to another, in effect the firm is transferring an obligation. If that obligation gets very large, that has a significant impact on its balance sheet and potentially its solvency, which ultimately affects the entire financial system. When there are no standards for counterparty risk or risk transfer, these impacts can go unnoticed until it is too late. As institutions started to fail in 2007, this is what brought us to the brink of collapse.

A shift towards standardisation

The financial crisis brought a new wave of industry regulations, including the Uncleared Margin Rules (UMR). UMR and other regulations and initiatives like SR 11-7, Basel IV, the European Market Infrastructure Regulation and the Targeted Review of Internal Models are regulatory responses aimed at least in part at standardisation, but barriers still exist towards achieving it.

The standardisation in the data representation of derivatives will likely be one of the last barriers to overcome, but it is one of the most important. Implementation of data standards will allow a new wave of transparency, interoperability sharing, cost reduction, and, ultimately, safety in the industry. As the final phases of UMR approach, we have an opportunity to migrate the industry to a common data set using an accessible and transparent open-source framework.

A market standard for data, and ultimately for pricing and valuing derivatives, would be beneficial for market participants and regulators alike. We have been working towards this goal for several years and are excited for the industry to embrace standardisation. Below are some initiatives and products AcadiaSoft and Quaternion have implemented that will help move the industry towards standardisation.

Open Source Risk Engine

Quaternion (now part of AcadiaSoft) first released the Open Source Risk Engine (ORE) in 2016. ORE makes complex financial risk more manageable by providing a transparent and powerful valuation and risk framework for financial derivatives. The goal of ORE is to:

• Provide a free open-source pricing and risk application, accessible to the end user, at a high level of technical sophistication allowing for full scalability and production usage
• Offer broad analytics covering valuation, market risk analysis, credit exposure simulation and XVA calculation
• Cover all relevant asset classes — interest rate, foreign exchange, inflation, equity and commodity derivatives
• Publish annual releases to take account of market changes and ORE user input

Importantly, end-user accessibility means that ORE can be downloaded and used out of the box, with trade data provided in ORE’s public XML format. ORE also comes with various examples and a detailed user guide that facilitates its adoption and ongoing application.

Many firms leverage ORE as a blueprint and extensible foundation for tailored pricing and/ or risk solutions. Once this is achieved, the full benefits of having a fully transparent framework for pricing and risk management kick in.

Firms that adopt ORE typically do so in the areas of:
• Derivatives and structured asset valuation
• XVA calculation and CSA pricing and decision making
• Collateral management and liquidity forecasting
• Model validation
• Market risk monitoring and management across the balance sheet
• Financial planning and controlling

AcadiaSoft’s SIMM calculation service (IM Risk Generator), as well as the SIMM backtesting and benchmarking service uses ORE (with extensions called ORE+) as a core component. The ORE+ extensions for that purpose comprise a wide range of additional financial instruments, with more analytics than ORE currently provides, performance enhancements and a web service integration layer.

Data standards and UMR

With Phases five and six for the uncleared margin rules coming into scope in September 2021 and 2022, respectively, and the vast number of firms that this impacts (AcadiaSoft expects upwards of 1,000 firms will be in scope for the last two phases of the regulations—compared to 75 firms in total in Phases one to four of UMR), an industry-wide market data standard could emerge on the back of the UMR requirements. Initiatives like the ISDA common domain model could add greater value to efforts in improving how data is used, shared, and stored.

To date, more than 50 per cent of all in-scope Phase 5 firms have adopted AcadiaSoft’s IM Risk Generator service. The IM Risk Generator service takes client trade data as an input and generates either an ISDA SIMM — or Schedulebased Common Risk Interchange Format (CRIF) file that forms the input to the initial margin calculation. In the case of an ISDA SIMM CRIF, a key component of the service is the calculation of the risk sensitivities that enable the ISDA SIMM calculation.

The CRIF file forms the input to the initial margin calculation — it contains the clients’ positions that are subject to UMR and its trade risk sensitivities, generated on a daily basis. A typical buy-side firm — even fairly large firms that are subject to these rules — simply does not have the resources available to manage this daily process.

On the regulatory front, firms need to demonstrate that SIMM is appropriate for their specific portfolios. Being able to demonstrate this in a standard model has a number of benefits for the industry. An increasing number of market participants are adopting the ORE XML trade format, as evidenced by the volume of financial institutions that have onboarded to AcadiaSoft’s SIMM service.

In addition to the SIMM calculation, several firms are required to perform quarterly ISDA SIMM™ backtesting and benchmarking for the regulators. The ORE/ORE+ analytics and methodology allow for a standardised data representation and reporting. This has been widely welcomed by regulators.

As the number of market participants that leverage the ORE framework increases, we see the potential to establish a standard for trade representation in the OTC derivatives market. The increased adoption also allows for expansion into additional analytics services on top of the ISDA SIMM related ones.

Moreover, adopting AcadiaSoft’s analytics services means adopting a consolidated market data feed process that is managed by AcadiaSoft and fuels the service analytics in ORE/ORE+. This leads to a somewhat more hidden standardisation of market data usage across the industry, which can open up further opportunities to provide standardised model calibrations for Valuation, Market Risk, Initial Margin, Credit Risk and Capital Requirements calculations in the future.

All of these pieces fit into the larger puzzle of creating industry-wide standards. Standardisation makes products safe, transparent and accessible. As the final phases of UMR approach, we are on the cusp of a widespread adoption of industry standards.

This is welcome news for regulators and businesses alike.

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