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Solution for setting optimal strategy between premium volume and target profit. The solution is based on:

• Building basic mathematical model using GLM.
  • Evaluation of key risk drivers of insurance portfolio.
  • GLM model development.
  • Construction of zero profitability tariff.
• Building a regional segmentation based GPS smoothing.
  • Using GPS locations for smoothing of the claim data in portfolio.
  • Use of cluster analysis for grouping similar risk together.
  • Embedding the regional segmentation into standard GLM model.

• Extension of portfolio data with external data set
  • Extension of portfolio data with external data – possible sources:
    • Census data – statistical office
    • Public databases for entrepreneurs (turnover, payment morale, etc.)
  • Evaluation of key risk drivers of insurance portfolio (cluster analysis).
  • Embedding external data variables into standard GLM model.

• Modeling of new business incomes:
  • Evaluation of key drivers influencing policyholder’s conversions to insurance portfolio.
  • GLM model development.
• Modeling of policyholders lapse rate:
  • Evaluation of key drivers influencing policyholder’s lapse rate at anniversary.
  • GLM model development.
• Development of price optimization tool for management of new business rate-book and sales incetives:
  • Combining the policyholders probability of conversion to insurance portfolio with risk valuation (profitability) in one optimization tool which maximizes premium volume with given limits of profits.
  • Solution P&L impact evaluation.
• Development of price optimization tool for management of renewal offers:
  • Combining the policyholders probability of lapse rate with risk valuation (profitability) in one optimization tool which maximizes profit with given limits of lapse rate.
  • Solution P&L impact evaluation.