Guy Carpenter has advanced its capital modelling capabilities with the addition of an automation enhancing functionality – MetaRisk 10 – that supports firms in one of the most important capital management considerations, the Best Capital Adequacy Ratio (BCAR).
The new addition to the firm’s platform for building and updating models supports A.M. Best’s new stochastic-based Best’s Capital Adequacy Ratio (BCAR).
MetaRisk incorporates open-source IronPython scripting with its proprietary MetaRisk ModelBuilder to offer a better user experience and improved speed and efficiency, as well as enabling “hours clauses” modelling.
It creates models via loading parameters from common external applications such as SQL or Microsoft® Excel®, improving the performance of MetaRisk’s suite of risk and capital modeling tools.
Steve White, Chief Actuary and Head of Enterprise Analytics for Guy Carpenter, said that while MetaRisk has featured elements of automation for years, MetaRisk 10 “brings automation to the forefront, making our UX more efficient than ever. Companies can now build or update models in mere minutes, saving them hundreds of accumulated hours in parameterization time.”
MetaRisk 10 now empowers one of the most stringent capital hurdle a company faces from rating agency and regulatory requirements – stochastic BCAR analysis.
By adding support for stochastic-based BCAR calculations, MetaRisk 10 increases modeling transparency and allows for “what-if” scenarios.
“Being able to accurately model stochastic BCAR scores is becoming a necessity for management teams looking to conduct planning and financial forecasting with confidence,” said Tom Hettinger, Strategic Advisory Leader for Guy Carpenter.
MetaRisk 10’s hours clauses modelling, enables companies to structure ideal coverage in a competitive reinsurance market; its timeline simulation combined with the new ability to stress test different “hours clauses” allows analysts to better define the impact of reinsurance, said Guy Carpenter.
The enhanced modelling platform is said to offer “seamless integration” of challenging complexities in capital modelling such as policy year and accident year data allowing for appropriate treatment of both risks attaching and losses occurring reinsurance contracts and enhanced correlation methods such as integrating aggregate correlation and common shock within the timeline-based framework.
