SciFinance® is a complete solution that automates coding and delivers source code (C/C++/CUDA) for derivatives pricing and risk model development. SciFinance increases the productivity and efficiency of quantitative developers while reducing development time and enhancing risk management.

Using a high-level language and patented technology, SciFinance enables you to create an unlimited variety of derivatives pricing models across all asset classes quickly and easily. SciFinance automatically generates source code that is optimized globally across functions, consistent and well documented in a fraction of the time it would take to code and debug by hand. Now you can formulate, test and refine alternative derivatives pricing models and risk strategies at unprecedented speed. Design, generate, test and integrate your models into many different work environments.
Unlike typical modeling systems, SciFinance is not an inflexible set of library routines that offers imprecise or limited functionality for defining your derivatives pricing and risk models. Rather, SciFinance provides a concise, flexible, and extensible language to specify models in terms that best match your financial instrument, often with a few simple keywords. You get the derivatives pricing model you need, tailored to your precise specifications.
SciFinance components include SciPDE and SciMC, SciCalibrator and SciIntegrator.
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SciFinance® automates pricing and risk model development
SciPDE™ and SciMC™ are the core SciFinance modules
SciGPU™ achieves blazing fast performance with CUDA and OpenMP
SciCalibrator™ provides pricing model calibration
SciIntegrator™ eases integration
A resource site with examples, documentation and more...
Watch the SciFinance Parallel Computing movie:
Webinar: Automatic GPU computing for derivative pricing models
NEWS
Reval Speeds Up Pricing Complex Instruments in the Cloud with SciFinance
"We were looking for a cost-effective and easy-to-deploy solution to improve the pricing of complex derivative instruments using PDEs or Monte Carlo simulation in our SaaS product. We found it with SciFinance and GPU-enabled models, without having to become experts in parallel coding or CUDA."
"...the only thing you need to add to get GPGPU acceleration is literally 'CUDA'; it's a single keyword, not a fundamentally different way to formulate the math equations. This allows SciComp's customers to save even more time while also improving accuracy."
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