Use Cases

Pricing Insurance with Machine Learning

uc challenge iconGreyChallenges

Nowadays, prospects can quickly compare different P&C insurance plans. Usually, they prefer those with the lowest price. Insurance companies must thus be capable of selecting attractive prices, but at the same time, be able to define the correct price-to-risk structure. Wrong predictions can lead to lower market share, and even worse, to significant monetary losses.

uc solution iconGreyOpportunity

LogicPlum can provide organizations with efficient models that help analyze the cost-risk relationship. By automating the process, organizations can create updated algorithms that will guarantee the correct pricing. As a result, adverse selection is reduced, competitive advantage improves, and risk becomes more manageable.

uc team iconGreyWhy LogicPlum

By using LogicPlum’s platform, insurance companies can increase effectiveness and reduce unnecessary costs. The model building process is automated, and it considers a wide range of algorithms: from Linear Models to Deep Learning, effectively ensuring that the resulting model is optimal.

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