Price Optimization

Insurance

Price optimization techiniques focus on finding the price that maximizes a defined cost function (or company’s margin), considering many factors like flexibity of prices, location of the customer, seasonal effects, special events and competitor pricing.
Price automation without machine learning is based on pre-defined pricing rules, while with machine learning implies training a model capable of automatically pricing items adapting to changes in the environment in a much richer and dynamic way.

Benefits for the company

With AI, insurance providers can dynamically monitor the marketplace, boost their understanding of risks to cover, and offer the best risk-adjusted prices. This enables them to stay competitive and retain the trust and accounts of their existing customers.

Feasability

High

Type of expertise/ AI domain

Bayesian Approach, Price Elasticity, Market basket Penetration and Reinforcement Learning Model

Internal data required

Pricing History, Purchases

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