Post Trade
Executive summary
Quantile, an LSEG Post Trade Solutions business and a leading provider of multilateral optimisation services, has transitioned from a well-known, third-party pricing and risk system to Acadia’s Open Source Risk Engine (ORE). The move aimed to leverage ORE’s free-to-access framework for pricing and risk analysis so Quantile could reduce costs and dependencies on external vendors.
To ensure a smooth transition, Quantile extensively tested ORE including generating pricing and risk valuations for an array of metrics that are used in its optimisation services. Quantile received extensive support and advice from Acadia’s team of experts, working together to ensure that ORE was implemented to best align with Quantile’s needs.
By leveraging QuantLib, a well-established open-source library, Quantile’s team found a familiar foundation that aided ORE adoption. They benefited from ORE’s extensive guidance documents, which includes ready-made use cases to streamline the integration process.
Background
Quantile was founded in 2017 to reduce the size, risk and complexity of the derivatives market. Now part of LSEG, Quantile offers a suite of market-leading post trade optimisation solutions for dealer banks, regional banks and buy-side firms. To deliver its optimisation services, Quantile required a robust solution to price and validate financial instruments.
Initially, Quantile opted for a plug-and-play approach, relying on a well-known, third-party quantitative analytics tool to meet its pricing and calibration needs. However, once implemented, the workflow proved difficult to maintain operationally and required a lot of manual intervention which made the process inefficient. The support offered by the third-party was also sparse, and the recurring license fees and support costs quickly stretched the available budget.
With both flexibility and cost in mind, Quantile sought an alternative solution for its pricing and risk analytics requirements.
Exploring an alternative possibility – ORE
First released in 2016, ORE is a free-to-access simulation engine which creates an environment to run risk scenarios and generate portfolio pricing. Based on QuantLib, the widely recognised and open-source library for quantitative finance, ORE offers an advanced, reliable end-to-end pricing and risk solution for firms.
ORE is regularly updated to incorporate the latest developments in simulation models, financial instruments and pricing engines, ensuring it remains cutting-edge. It is offered to the community for free as part of a commitment to enhance the transparency of risk analytics and improve accessibility to next-generation financial tools.
| At a glance: key advantages of Open Source Risk Engine (ORE) | |
|---|---|
| Cost | ORE provides the equivalent functionality to other major pricing and analytics vendors free of charge and without licensing fees. |
| Consultancy | Access to world-class sector experts who collaborate with your team on an ongoing basis. |
| Support | Full weight of LSEG behind ORE’s implementation with a dedicated day-to-day team working on it. |
| Transparency | The open source nature of ORE enables teams to get “under the hood” of the software and understand it on a granular level, essential in this highly regulated sector. |
| Customisability | ORE enables users to own, extend and tailor it for their exact requirements. |
| Resources | Extensive documentation powered by the open source community enables users to streamline learning by leveraging existing insights. |
| API | ORE can be accessed via a usable Python API which allows automatic execution of generated scripts. |
| Familiarity | ORE is based on industry-renowned QuantLib, enabling easier adoption. Engineers’ familiarity with QuantLib (and therefore ORE) also broadens the pool of talent when hiring. |
| Updates | ORE receives multiple updates a year to ensure it reflects the latest developments. |
| Commercial sponsorship/guarantee | Support for firms that require a sponsorship/guarantee from a commercial entity when using open source software is available (tailored Service Level Agreements available to purchase from Acadia) |
| Quality guarantee | As part of LSEG, ORE undergoes a rigorous model validation process, subject to LSEG’s internal Model Risk Management Policy and related Governance procedures. This also applies for each new version that gets released. |
Implementation
Quantile’s engineering team implemented ORE to calculate present value and risks for hedge trades, as well as validate data submitted by clients to improve delivery of its optimisation services.
Following initial efforts to improve market data calibration and yield curve construction, which ran smoothly, the team then leveraged ORE’s extensive pricing models to price interest rate derivatives and compute risk sensitivities across multiple asset classes.
Given their familiarity with QuantLib, which is also free to use, Quantile’s engineers were able to use both libraries. While QuantLib was sufficient for some tasks, ORE’s advanced capabilities in risk modelling and analysis enhanced their pricing and risk valuation toolkit.
From initial adoption to full implementation, Quantile transitioned to ORE’s free-to-access solution within a year. This timeline included a parallel testing phase, where Quantile’s team ran processes alongside the legacy system to validate ORE’s performance. As ORE did not require an additional license fee, Quantile was able to run both systems concurrently until it was confident to decommission the legacy providers service.
For firms bound by long-term contracts, adopting ORE involves minimal financial risk as it is free to access. This enables a phased and gradual approach to support seamless implementation, allowing teams to explore its full potential before transitioning.
Conclusion
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