MOTIVATION
Predictive models must indicate the impact of major business decisions accurately. In the case of selling an insurance product to potential customers, it becomes all the more important. Today, many InsurTech institutions employ Conversion Modeling techniques for predictive whether an insurance quotation will lead to a successful purchase. They use customer and sales data to predict whether a quoted price is acceptable to customers. Accurate prediction of conversion helps companies understand the impact of proposed pricing options and retain a loyal customer portfolio.
Approach:
InsurTech experts need to balance the impact of a proposed pricing plan on customer attraction with top-line growth. They must keep a keen eye for ensuring profitability of their institution without driving customers away.
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Toolset:
RubiStudio – Data Exploration, Data Joiner, Merger, Statistical Hypothesis, Code Fusion
RubiML – Clustering models, Silhouette Score – Code Fusion
Rubisight – Story and Dashboard.
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Skillset:
Business Reporting
Machine Learning
Domain Knowledge
Data wrangling
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Dataset:
The dataset throws light on customers’ interest in buying home policies from a particular site and includes information on specific coverage, sales, customers, property, and location.
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OUTCOMES