This release significantly updates the company database and enhances CoMeta’s integrated underwriting functionality that allows you to calculate insured losses for a company.
This release leverages Praedicat’s expertise in data science to incorporate approximately 3,000 new algorithmically generated company profiles. Algorithmically profiled companies represent an automated, data science-based process that combines data from multiple sources to suggest likely links between a company, an industrial/commercial activity, and use of a Litagion® agent in that activity by the company. CoMeta now represents not only the Fortune 1000 analyst profiled companies with US liability exposure but also a large fraction of the large, medium and small capitalized companies on the NYSE and the NASDAQ stock exchanges and the largest private companies in a broad range of industries.
With this release and the recent release of Oortfolio v2.0, we have enhanced the quantitative underwriting functionality for companies in CoMeta along with the ground-up loss exceedance probability curves for Litagion agents, companies, and NAICS industries. CoMeta’s quantitative features are powered by an enhanced Nekomodel™, Praedicat’s breakthrough forward-looking liability catastrophe model. The enhanced Nekomodel now supports 46 Litagion agents and presents a range of possible outcomes for policies written on the occurrence policy form. This release will also smooth sampling errors in the tails of the Nekomodel simulation.
Expansion of company profiles with the introduction of algorithmically profiled companies
A new company filter on the Companies page called Filter by Company Profile allows you to filter the company list for algorithmically profiled companies or analyst profiled companies. Algorithmically profiled companies are represented by a placeholder dartboard whereas analyst profiled companies are represented by a company-specific dartboard summarizing the company’s risk of litigation attributable to Litagion agents they manufacture or incorporate into their products.
Algorithmically profiled companies provide valuable information by algorithmically linking a company with Litagion agents, but the capabilities of an algorithmically profiled company are limited compared to analyst profiled companies in CoMeta. For example, algorithmically profiled companies are not represented in company clash maps or quadrant charts. However, company underwriting mode is available for many algorithmically profiled companies.
Enhanced underwriting capabilities for the occurrence policy form
This release introduces a range of possible outcomes for company policies written on the occurrence policy form. Within the underwrite mode for a company in CoMeta, there are now two occurrence policy trigger types – Occurrence (High) and Occurrence (Low) to generate insured losses. Ground-up losses are also available for both Occurrence (High) and Occurrence (Low) policy forms.
Due to the many ways occurrence losses can be allocated in court, the Occurrence (High) and Occurrence (Low) trigger types are provided to represent two possible scenarios of allocation, as described in further detail in the following section.
Alternative implementations of the integrated occurrence and occurrence policy forms
Modeling losses stemming from the Bermuda form requires a model of the insured’s decision to declare an integrated occurrence encompassing a set of related claims. In this release of CoMeta, this decision (informally referred to as “batching”) is now modeled as a function of “liability risk,” the likelihood that a plaintiff will prevail in court. Once liability risk exceeds a certain level for a set of related claims, the model assumes affected insureds will choose to declare an integrated occurrence. The model further assumes that all policies written in years subsequent to the batching decision will exclude that risk from coverage, regardless of the policy form.
Modeling losses stemming from the occurrence form requires an assumption of how losses attributable to the same underlying event (or “occurrence”) will be allocated across available policy years. In this release, users now have available a range of estimated losses from the occurrence form, representing the range of common loss allocation methods used in various jurisdictions. This range is described by two alternative estimates of losses, called Occurrence (High) and Occurrence (Low). Occurrence (High) assumes that losses are allocated evenly across policy years between the current policy year (2017) and the year in which the risk is excluded from future coverage (the “batching” year). Occurrence (Low) assumes that losses are allocated evenly across policy years between the year of first exposure (which is typically many years prior to the current policy year) and the batching year.
Please reach out to your client success manager to receive a more detailed methodology description.