Reinsurance Company

reinsurance company data feature lake

REINSURANCE COMPANY USE CASE

Background:

Considerable information asymmetries exist in the reinsurance marketplace, making it very different from capital markets.   Significant value can be created by leveraging these asymmetries.  To effectively diversify the considerable risk in insuring against catastrophic events, for example, takes great underwriting skill and sufficient market scale. This is, in part, because such risk is characterized by a small number of very large losses, the occurrence of which are both unpredictable and infrequent driving the long tail of frequency distributions, and as such are heavily capital consumptive.


Objective:

Effectively capture and quantify more sources of exposure to any catastrophic risk.


Approach:

The Nitrogen.ai Data Feature Lake makes relevant data available to assist in leveraging these asymmetries through data sharing.  We effectively manage data as features across a wide range of external data.   By providing trustworthy governance and making it safe and efficient to share data among collaborators, the N.ai platform can be used to define and understand this asymmetry to achieve competitive advantage.    In addition, the ability to monetize data among non-competitive entities extends the discovery power of the data feature lake.


Outcome:

The Nitrogen.ai Data Feature Lake makes relevant data available to assist in leveraging these asymmetries through data sharing.  We effectively manage data as features across a wide range of external data.   By providing trustworthy governance and making it safe and efficient to share data among collaborators, the N.ai platform can be used to define and understand this asymmetry to achieve competitive advantage.    In addition, the ability to monetize data among non-competitive entities extends the discovery power of the data feature lake.