2017•Unpublished venueRequires access

Insurance premium optimization using motor insurance policies — A business growth classification approach

Daniel Muller, Yiea-Funk Te

Open publisher page 7 citations

Abstract

The most common business insurance is the general liability insurance, providing businesses with coverage for damage caused to others, as a result of their business operations. In this paper, we investigate how changes to the main insurance premium driver, a company's insured revenue, can be estimated using a random forest classification. We find that information about a business customer from its motor vehicle insurance policy, can be used to classify shrinking, stable and growing businesses. The integration of the model into an insurance CRM system, may provide an economical useful solution for traditional insurance companies to increase insurance premiums in an efficient way by only reaching out to the most promising companies to do business with.

About this research paper

What this paper is about

The most common business insurance is the general liability insurance, providing businesses with coverage for damage caused to others, as a result of their business operations. In this paper, we investigate how changes to the main insurance premium driver, a company's insured revenue, can be estimated using a random forest classification. We find that information about a business customer from its motor vehicle insurance policy, can be used to classify shrinking, stable and growing businesses. The integration of the model into an insurance CRM system, may provide an economical useful solution for traditional insurance companies to increase insurance premiums in an efficient way by only reaching out to the most promising companies to do business with.

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OpenAlex reports 7 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

The most common business insurance is the general liability insurance, providing businesses with coverage for damage caused to others, as a result of their business operations. In this paper, we investigate how changes to the main insurance premium driver, a company's insured revenue, can be estimated using a random forest classification. We find that information about a business customer from its motor vehicle insurance policy, can be used to classify shrinking, stable and growing businesses. The integration of the model into an insurance CRM system, may provide an economical useful solution for traditional insurance companies to increase insurance premiums in an efficient way by only reaching out to the most promising companies to do business with.

Key concepts: Business, Insurance policy, Business interruption insurance, Revenue, Auto insurance risk selection, Liability insurance, General insurance, Actuarial science

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