The World’s Scientific Community Is Our Emerging Risk Group

Praedicat converts the corpus of peer-reviewed science into industry and company exposures for underwriting.

Praedicat mines peer-reviewed science journals.

Identify the hazards of concern to scientists.
Characterize commercial exposures.

Praedicat models the state and evolution of scientific literatures to characterize the risk.

BIG DATA

Millions of Peer Reviewed Articles

Praedicat mines the corpus of today’s science to anticipate tomorrow’s claims.

Over 22 Million Journal Articles

We use Millions of peer-reviewed journal articles — unstructured text data which we mine and map. Risk emerges from the metadata.

Algorithmic Risk — Praedicat relies on the world’s community of toxicologists, epidemiologists, and bioscientists to algorithmically identify emerging risks. Our patented “saliency” algorithm combs through the corpus of peer-reviewed science for new hypotheses that chemicals, products and substances might cause bodily injury. The risks are automatically prioritized by the energy and intensity of new attention the risks receive, and are tracked over time as they mature.

BIG DATA

CoMeta’s assessment of risk is based on proprietary algorithms that extract information on litagion® agents from over 10,000 peer-reviewed journals and from regulatory documents. The scientific information is regularly updated to reflect the most recent developments in science, allowing users to track how each litagion agent’s science-based risk evolves over time.

Praedicat's algorithms are mining hundreds of literatures, such as those exploring harms from cell phones, nanomaterials, benzene, and BPA. Dynamic metadata is extracted to inform risk modeling.

2847 peer-reviewed articles

About BPA causing bodily injury since 1960

442 in 2014 alone

85% found harmful effects

18.8% have been studies on humans

3/4 have found harmful effects

Risk Modeling

Praedicat builds exceedance probability curves out of the metadata for the emerging risks using modeling based in empirical law and economics.

The risk models are based on an event set of over 10,000 potential future mass litigation events. These hypothetical torts, or “latent mass actions,” are based on the commercial settings scientists identify as presenting the riskiest human exposures to litagion agents.

Commercial Footprint

Every litagion agent’s litigation-exposed industrial footprint is mapped to specific exposed companies using multiple administrative databases and a range of additional authoritative databases.

Correlated Risks

We profiles 1000s of companies which are complex and dynamic creatures often consisting of dozens, or even hundreds of industries and thousands of products and services. With science-based risk, the companies can be related in surprising ways.

A Unique Window

We mine multiple administrative databases about the activities of companies and map their commercial footprint. We overlay the two maps, science and corporate, to create a unique window into risk.