1000x Faster Monte Carlo Simulations

I've written before about using the right, simple, tool for solving a problem, rather than going after the shiny new thing.

One such example: On a previous project, we achieved great success using relatively simple machine-learning models to achieve massive speedups in the complex simulations that a large insurance company or financial institution would run to manage the risk of their portfolio.

Massive here means that, instead of spending 80 hours for a complete run, it now takes a couple of minutes. This is, of course, a massive unlock. You can either save the time and use it elsewhere or spend the same amount of time doing a much more thorough analysis. These sorts of risk calculations are often required by regulators, with hefty penalties if reporting doesn't happen on time.

Despite this success, the technique, as far as we can tell, is not widely adopted. That's why we've decided to run a short, free webinar on the topic. It will take place this October at 10 a.m. Pacific Time, which corresponds to 1 p.m. Eastern Time and 7 p.m. Central European Time.

Who is this for?

• People interested in applying machine learning to financial and other statistical simulations

• Insurance analysts, quants, and actuaries tired of long runtimes

• Risk modelers who want to integrate machine learning into existing workflows

• Analytics and data science teams pushing against time, compute, or compliance pressure

Check out the event page and register for free here and tell your friends in finance and insurance.