On the way to solving one of the most difficult problems in financial engineering, our researchers were confronted with a major open problem in the more general field of stochastic calculus. Solving this more general problem allowed us to solve the original financial engineering problem, but also opened up a world of other applications including the area of credit risk.
Credit and Loss modeling have deep histories and many evolutions. Here at QuanteFi, we have developed an AI/ML solution that start with over 5000 variables across over 50 years of historical data.
Our research includes a combination of multiple default data sources with extensive histories. Our scores are validated regularly and demonstrate a high level of accuracy.
As a fully automated model, it is not as reliable as you'll find with the major business credit rating agencies, however it is pretty close, a lot cheaper, we cover most public companies in the US and have plans to expand globally.
Check out our simple to use API at RapidAPI or AWS Marketplace.
Monte Carlo and Survival Analysis
A New Paradigm
Monte Carlo is a method often used by financial institutions to simulate market conditions. In effect, it produces noisy data. Machine Learning is a method to find the underlying signal in noisy data. By using Monte Carlo in a smarter way, QuanteFi developed a model that can make the same estimates that are made by Monte Carlo simulations in a nano fraction of the time.