The team at Concirrus are always looking for ways to improve the services we offer to our clients and this article covers the predictive pricing capabilities available within Quest Marine.
In short, there is now too much information to process in the time scale required.
Data aggregation platforms can consolidate large, varied data sets, whilst Machine Learning algorithms can segment and analyse the vast quantity of data aggregated.
Using Machine Learning algorithms at scale, you can segment vast data sets to a granular level of detail and find specific trends for more accurate predictions. Moreover, the process can be automated which gives a huge capability to benefit the industry.
Using new and traditional modelling methods two vessels may appear identical based on static rating factors alone.
However, individual vessel behaviour can impact the Expected Loss value for each ship using the Quest Marine Pricing Module.
Highlighting the unique behavioural differences between two assets reinforces how a behavioural view on risk improves decision making. The impact on pricing can be dramatic, leading to a better understanding of what appropriate cover looks like for new prospects, as well as the positioning of existing accounts within a portfolio.
Influential factors are the elements of risk that contribute to an expected loss valuation. Within Quest Marine, users can view influential factors at both vessel and account level.
Underwriters and Brokers have improved clarity to help with negotiation, consultation, warranties, and renewals through influential factors.
Using the influential factors the industry can help Insureds to mitigate risk more effectively.
A forecast is conducted by utilising the expected loss of an account (net of the deductible) and applying the brokerage, internal expenses, and profit load to derive a premium valuation. This premium is then compared to the written premium for the account to derive a percentage difference, known as the adequacy. The adequacy of an account will clearly show whether an account is technically under, or overpriced.
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