An insurance risk engine like no other
We've built and trained Kompreno to provide insights into financial lines risks such as Directors & Officers, Employers Practice Liability and Mergers & Acquisitions.
Kompreno is not just another AI tool. It’s been developed by seasoned industry insiders with over 50 years insurance industry experience.
It helps you develop a superior understanding of risk, so you can separate deals into the good, the bad and the ugly.
Kompreno is stand alone and ready for you to use. Unlike many solutions it is API first and works seamlessly with legacy systems.
Get an instant summary of all the important information about a risk. Decide immediately if it suits your risk appetite.
Drill down and understand financial metrics, compare with other companies and even use your own indicators.
A world class modeling environment helps you understand the underlying frequency of events and compare by company or industry.
How much is it going to cost if a claim occurs. Kompreno tells you and allows you to understand your best and worse case scenarios.
We use Bayesian modeling techniques to run millions of simulations. Kompreno's interactive environment allows you to manipulate deals on the fly.
Kompreno has sophisticated portfolio analysis tools built in. Understand dangerous aggregations but also new opportunities. Scan the market for complementary deals.
Describe Data's founders are industry insiders with a wealth of industry experience.
Formerly the Head of Data & Analytics at Barnett Waddingham Michael has worked in actuarial and IT roles. He brings a business-first approach to the use of machine learning and is as well advises businesses on how to establish data science functions.
Gerard has many years’ experience building and managing technology platforms for international companies in reinsurance and insurance. He combines a passion for technology with international business experience and a pragmatic approach to getting results.
A physicist with a MSc in high performance computing and a PhD in quantitative finance Michael uses time series analysis and Bayesian methods to help insurance companies with problems that traditional actuarial approaches struggle with.
