Overview
Computations and simulations provide clients and courts insights into complex issues
Bates White specializes in computational modeling that helps clients and courts assess damages and understand complex statistical and economic issues. Computational modeling uses advanced software to study and analyze complex economic systems, often involving numerous economic agents (e.g., firms, customers, regulators) interacting with each other in a wide variety of real-world scenarios. Computational modeling can be used to test economic theory against real-world data.
At Bates White, we use computational modeling to
- Efficiently model complex statistical and economic systems
- Uncover nuanced insights
- Evaluate statistical power and robustness of modeling estimations
- Run hundreds of thousands of scenarios in insurance allocation matters for modeling complex choice-of-law issues. This parallelization helps our clients reach settlements more expeditiously.
Case highlights
We have calculated damages in numerous residential mortgage-backed securities (RMBS) matters by forecasting future loan performance of thousands of mortgages underlying RMBS and analyzing the impact of mortgage performance on RMBS. Learn more about matters where we’ve done this:
- Bates White client Ambac obtains $1.84 billion settlement with Bank of America
- Bates White client obtains $995 million settlement with JPMorgan Chase
- Mastr Adjustable Rate Mortgages Trusts 2006-OA2, 2007-1, 2007-3 v. UBS Real Estate Securities
- In matters related to corporate insurance allocation, we have designed tools for modeling complex choice-of-law issues, including disputes related to occurrence theory, non-cumulation, and insolvency. These tools run hundreds of thousands of scenarios in parallel and then draw on the results to help our clients gain a broad overview of the disputed issues and reach settlements more expeditiously.
- Bates White uses high-performance computing to generate confidence intervals and prediction intervals for cancer incidence forecast models. This process strengthens the liability estimation and forecast in personal-injury tort and bankruptcy litigation.
Tools and technologies
Learn more about the tools we use for computational modeling and how we ensure the quality of the results here.