Financially
Quantify
Cyber Risk

Kovrr enables (re)insurers to
predict and price cyber risk.

Cyber Risk
Selection &
Underwriting

Quantify Cyber Risk

Portfolio
Exposure
Management

Manage accumulated cyber risk. Stress test your book with catastrophic scenarios

Why kovrr

01

Data, Data, Data

Kovrr has developed its own proprietary data sources and partnered with many third party data providers to compile a diverse industry exposure database.

This enables (re)insurers using the platform to model and assess their cyber exposure based on different levels of data granularity input
02

Transparent Modeling

Kovrr provides insurance professionals unique visibility into its modeling methodologies and the underlying data.
03

Customized Platform

There is no one size fits all cyber risk model. Cyber risk models must be aligned to (re)insurers’ insured assets and directly map to potential liabilities, derived from the insurance coverages.

With Kovrr, (re)insurers can receive their own fully optimized models utilizing data that closely corresponds with the geography, industry, type of businesses, etc. With these models, (re)insurers  can differentiate their offerings in the market.

How we do it

Learn more
01

Real-time Cyber Threat Landscape Monitoring

Kovrr monitors hundreds of countries, millions of ongoing monitored incidents, activity of hundreds of top leading cybercrime groups, dozens of nation-backed advanced persistent threats (APT) actors  and thousands of individuals operating in the cyber space on a global basis in real-time.

Intelligence exposure data, claims incidents data and access to a variety of 3rd party data providers. to build advanced AI machine learning engines to predict and price cyber risk. We create risk models from cyber incidents, intelligence exposure data, claims incidents data and access to a variety of 3rd party data providers.
02

Cyber Modeling Framework

Our platform calculates aggregated exposure and pinpoints the relevance and exposure to current cyber threats. The events are run through damage functions, providing an accurate summary of the financial damage affecting the (re)insurers portfolio.

The result of these simulations are summarized in a yearly loss table (YLT), represented by exceedance probability(EP) curves.
03

Industry Exposure Database

Kovrr has developed its own proprietary data sources and partnered with third party data providers that have the best visibility in their respective cyber domains.

By doing this, Kovrr has built the largest and most granular industry exposure database containing  firmographic and technographic details of millions of businesses worldwide.