Ash Analytics deploys innovative technology to revolutionize actuarial work.
Actuaries are responsible for safeguarding a company's financial security. They model financial risk, design sustainable products, and ensure claims will be paid decades in the future. However, most actuaries still rely on overburdened Excel models or proprietary, closed source software with limited flexibility. As a result, vast quantities of insurance data often go unused.
It doesn't have to be this way.
Technology companies are embracing advances in machine learning, cloud computing, and specialized, high performance hardware. Ash Analytics helps insurance companies deploy the latest innovative technology from Silicon Valley to modernize actuarial workflows.
Partner with Ash Analytics to modernize and expand your actuarial capabilities.
Develop your team's Python skills with a workshop focused on specific actuarial applications.
Update existing Excel models using simple, fast, open source Python.
Create streamlined analytics pipelines for your data, from small to big and everything in between.
Organize, store, and access your data easily with robust solutions that scale from gigabytes to petabytes.
Implement interactive reporting dashboards to visualize and communicate complex model results.
Build high-performance, robust regulatory models with full audit trails and change control management.
Deploy the latest machine learning frameworks like Tensorflow & PyTorch to learn more from your data.
Reduce capital expenses and pay only for what you use. Run complex financial models on clusters that automatically scale to meet demand.
Learn more about the technology used by Ash Analytics.
Autograd is a Python library that automatically differentiates numpy code. Here I use it to demonstrate how Taylor Series can be used to fit polynomial functions to complex underlying curves.
Using PyTorch to implement four methods of calculating European put option price and greeks. I'll demonstrate how automatic differentiation can be used to calculate option greeks, and measure the time it takes for each implementation.
Automatic differentiation can be used to calculate the sensitivities, or "greeks", of a stock option, even if we use monte carlo techniques to calculate option price. Many exotic options can only be priced using monte carlo techniques, so automatic differentiation may be able to provide more accurate sensitivities in less time than traditional methods.
Jason Ash, FSA, founded Ash Analytics to transform how actuaries work.
Jason is a former Milliman consulting actuary whose fascination with technology led him to San Francisco. He has since worked for two financial technology companies, and now seeks to apply the same innovations to traditional actuarial work.
Jason is a frequent industry speaker and author whose articles have been featured in The Actuary magazine. He also writes about puzzles, probability, Bayesian modeling, and visualization on his website, www.jtash.com.