Rapid model development for valuation of exotic option instruments and integration into a 3rd party vendor system
The Commonwealth Bank (CBA) is Australia's leading provider of integrated financial services including retail banking, premium banking, business banking, institutional banking, funds management, superannuation, insurance, investment and sharebroking products and services.
Developing pricing model source code with the objective of having it operate in a production environment requires that the code be both highly computationally efficient and robust. These critically important criteria require that in-house developers possess a high degree of specialization in sophisticated numerical techniques in order to write such highly optimized and efficient code. Furthermore, developing such pricing code is a time consuming effort requiring weeks and/or months to complete.
SciFinance provides CBA with a cost-effective and robust derivatives pricing model development technology that allows for the rapid development of exotic pricing models that can easily and efficiently be integrated into a third-party vendor system.
Through the use of SciFinance, CBA:
- Has reduced model development time, effectively freeing up scarce quant resources.
- Can efficiently access many sophisticated numerical techniques that are indispensable for generating pricing model code that is fast as well as being numerically stable.
- Can quickly develop and test pricing model codes for new schemes.
Speeding up pricing compex instruments in the cloud
Reval is a leading derivative risk management and hedge accounting software-as-a-service (SaaS) provider. In order to quickly develop new structured products and vastly speed up Monte Carlo based derivatives for its SaaS customers, Reval chose SciFinance® from SciComp, used in conjunction with GPU hardware from NVIDIA.
Reval has been adding complex structured instruments to it's flagship SaaS product, Reval®. These instruments included Dual Currency bonds, Power Reverse Dual Currency bonds, Inverse Floaters and CMS Steepeners, all with embedded caps and floors and call/put options as well as Range Accruals and Principal Protected Notes. Reval needed to find a way to improve the development time for these instruments.
These types of derivatives are priced using Monte Carlo simulation, which requires running between 20,000 to 50,000 trials and uses a great deal of CPU time. Implementing a Monte Carlo framework in a SaaS environment adds extra stress to CPU usage at month-end closing and at times of high system usage. A 50,000 trial simulation of a complex instrument can take up to 60 seconds to run in a conventional hosted environment. Even with dedicated analytics servers, this can cause unacceptable response times as analytics servers are shared across hundreds of clients.
Reval teamed with SciComp to implement a combined hardware and software solution. The results were a faster derivatives model development cycle and accelerations of 100X faster than serial code for derivative valuations in the SaaS environment.